Variable Precision Rough Set

Variable Precision Rough Set Model (VPRS)

VPRS Model
Variable Precision Rough Sets
Approximate Rough Set Model
Değişken Hassasiyetli Kaba Küme Modeli

Variable Precision Rough Set (VPRS) is an extension of classical rough set theory introduced by Wojciech Ziarko in 1993 to handle real-world data that inevitably contains noise and misclassification. By introducing a precision parameter u controlling the allowable degree of overlap between equivalence classes and a target concept, VPRS relaxes the strict subset requirement of standard rough sets, enabling the induction of approximate classification rules from noisy or inconsistent datasets.

u ∈ [0, 0.5) controlling allowed misclassification rate

Relaxes exact inclusion requirement of classical rough sets

Ziarko, W. (1993). Variable precision rough set model. Journal of Computer and System Sciences, 46(1), 39–59.


Variable Rate Application

VRA
variable rate technology
site-specific application
prescription-based application

1980s–1990s (early GPS-integrated field trials; widely adopted 1990s)

Variable Rate Application (VRA) is a precision agriculture technique that adjusts the quantity of inputs — such as fertilisers, pesticides, seeds, or water — across different zones of a field based on georeferenced soil and crop data. Rather than applying a uniform rate across an entire field, VRA delivers the right input, at the right rate, in the right location, improving resource efficiency and reducing environmental impact in crop production systems.

Precision agriculture technology and process

Georeferenced spatial data (soil samples, yield maps, remote sensing imagery)

Stafford, J. V. (2000). Implementing Precision Agriculture in the 21st Century. Journal of Agronomy and Crop Science, 185(1), 1–26.

Pierpaoli, E., Carli, G., Pignone, E., & Rinaldi, M. (2013). The Drivers of Precision Agriculture Technologies Adoption: A Literature Review. Procedia Technology, 8, 61–69.

precision-agriculture gis-mapping soil-sampling remote-sensing yield-mapping site-specific-crop-management


Variance Inflation Factor

VIF
Variance Inflation Index
Multicollinearity Inflation Factor
Varyans Enflasyon Faktörü

The Variance Inflation Factor (VIF) is a scalar diagnostic statistic proposed by Donald Marquardt (1970) that quantifies how much the variance of an estimated regression coefficient increases due to linear dependence—multicollinearity—among the predictors in an ordinary least squares model. It is routinely applied in econometrics, social science, and biomedical research whenever analysts suspect that two or more independent variables move together closely enough to destabilize coefficient estimates.

VIF > 10 commonly flags severe multicollinearity

Marquardt, D. W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics, 12(3), 591–612.


Variance Reduction for Monte Carlo

Variance Reduction Techniques for Monte Carlo Simulation (AV, CV, IS)

Monte Carlo Varyans Azaltma Teknikleri (AV, CV, IS)

Hammersley & Morton (antithetic variates, 1956); Lavenberg & Welch (control variates, 1981); importance sampling roots in Kahn & Marshall (1953)

Variance reduction techniques are a family of methods that improve the efficiency of Monte Carlo simulation by achieving the same estimation accuracy with fewer random draws. Developed incrementally from the 1950s onward — with antithetic variates attributed to Hammersley and Morton, control variates formalised by Lavenberg and Welch, and importance sampling rooted in Kahn and Marshall — the family includes antithetic variates (AV), control variates (CV), importance sampling (IS), and stratification, each exploiting a different structural property of the target quantity to lower estimator variance without introducing bias.

Simulation variance-reduction technique family

Antithetic Variates (AV), Control Variates (CV), Importance Sampling (IS), Stratification

Achieve the same estimation accuracy as standard Monte Carlo with fewer simulation runs

Ross, S.M. (2012). Simulation (5th ed.). Academic Press.

Glasserman, P. (2003). Monte Carlo Methods in Financial Engineering. Springer.

monte-carlo-simulation quasi-monte-carlo bootstrap-simulation markov-chain-monte-carlo stochastic-differential-equations


Variant Calling

SNP calling
genotyping from sequencing
mutation detection
variant detection

Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)

Variant calling is the computational process of identifying positions in a sequenced genome that differ from a reference sequence — including single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and structural variants. It transforms aligned sequencing reads into an interpretable catalogue of genetic differences, forming the foundation for population genetics, disease-gene discovery, and clinical genomics applications.

Aligned next-generation sequencing reads (BAM/CRAM files)

McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., ... & DePristo, M. A. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297–1303.

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., ... & Durbin, R. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25(16), 2078–2079.

sequence-alignment genome-wide-association-study copy-number-variation-analysis rna-seq-differential-expression epigenome-wide-association-study single-cell-variant-calling


Variational Autoencoder

Değişkensel Otokodlayıcı (VAE)
VAE
auto-encoding variational Bayes
deep latent variable model

The Variational Autoencoder (VAE) is a deep generative latent-variable model, introduced by Diederik Kingma and Max Welling in 2014, that encodes data as a probability distribution in a latent space and samples from that distribution to generate new examples. It is used for data generation, anomaly detection, and feature learning.

Deep generative latent-variable model (encoder–decoder)

Generative modelling, dimensionality reduction, anomaly detection

Kingma, D. P. & Welling, M. (2014). Auto-Encoding Variational Bayes. International Conference on Learning Representations (ICLR).

Higgins, I. et al. (2017). beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. International Conference on Learning Representations (ICLR).

generative-adversarial-network diffusion-model score-based-diffusion pca autoencoder


Variational Inference with Measurement Error

Variational Bayesian Inference for Models with Measurement Error

variational Bayes measurement error model

approximate Bayesian inference under measurement error

Building on Blei et al. (2017) for VI and Carroll et al. (2006) for measurement error frameworks

Variational inference with measurement error is a scalable Bayesian approach that simultaneously estimates model parameters and latent true covariates when observed variables are contaminated by noise. Rather than sampling the posterior via MCMC, it finds the closest tractable distribution to the true posterior by maximising the evidence lower bound (ELBO), making it applicable to large datasets where full MCMC is too costly.

Continuous, binary, or count outcomes with error-contaminated covariates or responses

Blei, D. M., Kucukelbir, A., & McAuliffe, J. D. (2017). Variational inference: A review for statisticians. Journal of the American Statistical Association, 112(518), 859–877.

Carroll, R. J., Ruppert, D., Stefanski, L. A., & Crainiceanu, C. M. (2006). Measurement Error in Nonlinear Models: A Modern Perspective (2nd ed.). Chapman & Hall/CRC.


Variational Inference with Missing Data

Variational Bayesian Inference with Missing Data

VI with missing data
variational EM with missing data
VB missing data
mean-field VI for incomplete data

Ghahramani & Jordan; Wainwright & Jordan (formal foundations)

Variational inference with missing data is a scalable Bayesian approach that simultaneously approximates the posterior over latent variables and model parameters while imputing missing observations. Instead of integrating over all possible values of the missing entries exactly, it posits a tractable approximate distribution and optimises it to be as close as possible to the true joint posterior, yielding fast, principled inference even in high-dimensional incomplete datasets.

Incomplete / partially observed continuous or categorical data

Ghahramani, Z. & Jordan, M. I. (1994). Supervised learning from incomplete data via an EM approach. In Cowan, J. D., Tesauro, G. & Alspector, J. (Eds.), Advances in Neural Information Processing Systems 6 (pp. 120–127). Morgan Kaufmann.

Wainwright, M. J. & Jordan, M. I. (2008). Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1(1–2), 1–305.

variational-inference bayesian-inference-with-missing-data mcmc-with-missing-data gibbs-sampling-with-missing-data expectation-maximization mean-field-approximation


Variational Inference

VI
variational Bayes
VB
mean-field variational inference
ELBO optimisation
variational approximation

Variational inference (VI) is a family of techniques that turn Bayesian posterior computation into an optimisation problem. Instead of drawing samples from the exact posterior — as Markov chain Monte Carlo does — VI posits a simpler, tractable family of distributions and finds the member of that family closest to the true posterior by maximising the evidence lower bound (ELBO). Introduced in its modern graphical-model form by Jordan, Ghahramani, Jaakkola and Saul (1999) and given a comprehensive statistical treatment by Blei, Kucukelbir and McAuliffe (2017), VI is now the standard scalable inference engine in probabilistic machine learning.

posterior approximation / scalable inference

approximate posterior distributions / ELBO lower bound

Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., & Saul, L. K. (1999). An introduction to variational methods for graphical models. Machine Learning, 37(2), 183–233.

Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer. (Chapter 10: Approximate Inference.)

mcmc bayesian-regression hierarchical-bayes expectation-propagation latent-dirichlet-allocation


Variational Mode Decomposition

VMD
Adaptive Signal Decomposition
Variational Signal Decomposition
Varyasyonel Mod Ayrıştırma

Konstantin Dragomiretskiy & Dominique Zosso

Variational Mode Decomposition (VMD) is a fully adaptive, non-recursive signal decomposition method introduced by Konstantin Dragomiretskiy and Dominique Zosso in 2014. It decomposes a real-valued input signal into a discrete number of sub-signals, called intrinsic mode functions (IMFs), each with a specific sparsity in the frequency domain. Unlike Empirical Mode Decomposition, VMD frames decomposition as a variational optimization problem solved via the Alternating Direction Method of Multipliers (ADMM), yielding robust and physically meaningful components.

Adaptive variational signal decomposition algorithm

Output: K band-limited intrinsic mode functions (IMFs)

Dragomiretskiy, K., & Zosso, D. (2014). Variational mode decomposition. IEEE Transactions on Signal Processing, 62(3), 531–544.


Variational Quantum Eigensolver

The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the lowest eigenvalue (ground state energy) of a quantum Hamiltonian. Introduced by Peruzzo et al. in 2014, it exploits the variational principle to combine the power of quantum circuits with classical optimization to solve chemistry and materials science problems on near-term quantum devices.

Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213.

McClean, J. R., Romero, J., Aspuru-Guzik, A. (2016). The theory of variational hybrid quantum-classical algorithms. New Journal of Physics, 18, 023023.

Cao, Y., Romero, J., Aspuru-Guzik, A. (2021). Potential of quantum computing for drug discovery. IBM Journal of Research and Development, 62, 6:1-6:20.


Vasculitis Damage Index

Vasculitis Damage Index for Systemic Vasculitis

VDI
Vasculitis Permanent Organ Damage Score

The VDI is a clinician-assessed measure of permanent organ damage in patients with systemic vasculitis, including ANCA-associated vasculitis (AAV), polyarteritis nodosa, and other necrotising vasculitides. Introduced by Exley et al. (2003), VDI captures cumulative irreversible damage across organ systems, complementing disease activity measures (such as the Birmingham Vasculitis Activity Score). Systemic vasculitis is characterised by inflammation of blood vessel walls, leading to ischaemia and permanent tissue damage. VDI acknowledges that damage accrues over time and is largely irreversible, making it a prognostically important measure distinct from transient inflammatory activity.

Exley AR, Bacon PA, Luqmani RA, Kitas GD, Gordon C, Pusey CD, Savage CO. Development and initial validation of the Vasculitis Damage Index (VDI) for systemic vasculitis. Arthritis & Rheumatism. 2003;48(7):2146-2157.


VCG Mechanism

Vickrey Mechanism
Generalized Vickrey Auction
Truthful Mechanism

William Vickrey, Edward Clarke, Theodore Groves

The Vickrey-Clarke-Groves (VCG) Mechanism is a truthful mechanism design solution that allocates resources and determines payments to incentivize participants to reveal their true valuations. Building on William Vickrey's 1961 sealed-bid auction work and extended by Clarke and Groves, VCG ensures that reporting truth is a dominant strategy for all participants, achieving allocative efficiency while maximizing total surplus.

Vickrey, W. (1961). Counterspeculation, auctions, and competitive sealed bids. The Journal of Finance, 16(1), 8-37.

Clarke, E. H. (1971). Multipart pricing of public goods. Public Choice, 11(1), 17-33.

bayesian-nash-equilibrium first-price-auction principal-agent-model nash-equilibrium


VECM

vector error correction model
error correction model
cointegration model
VECM (Vektör Hata Düzeltme Modeli)

The Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework.

Maximum likelihood (Johansen) on the cointegrated VAR

Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276.

var-model ardl-bounds-test arima ols-regression


Vector Autoregression

VAR
VAR model
vector autoregressive model
multivariate autoregression

Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.

Multiple stationary time series (continuous)

Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.

Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.

structural-var vector-error-correction-model arima-model granger-causality-test johansen-cointegration-test arma-model


Vector Error Correction Model

VECM
error correction VAR
cointegrated VAR
vector equilibrium correction model

The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.

Multivariate time-series; cointegrated I(1) variables

Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.

Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59(6), 1551–1580.

vector-autoregression structural-var johansen-cointegration-test engle-granger-cointegration-test granger-causality-test arima-model


VECTOR-NORMALIZATION

VECTOR-NORMALIZATION (Vector (L2) Normalization) is a normalization multi-criteria decision-making (MCDM) method introduced by Hwang, C. L. Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Euclidean norm-based column normalization

Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin


Vegas Monte Carlo

VEGAS algorithm
adaptive importance sampling
multidimensional integration

VEGAS is an adaptive Monte Carlo algorithm for numerical integration of multidimensional functions, particularly useful for high-dimensional integrals common in particle physics calculations. By adaptively refining the sampling distribution to concentrate points in high-contribution regions, VEGAS dramatically improves integration efficiency compared to naive Monte Carlo.

Lepage, G. P. (1978). A new algorithm for adaptive multidimensional integration. Journal of Computational Physics, 27(2), 192–203.

Lepage, G. P. (1980). VEGAS: an adaptive multidimensional integration program. Cornell University preprint CLNS-80/447.

Nagy, M., & Nagy, I. (2005). Application of VEGAS integration algorithm for calculation of penetration depth in superconductors. Journal of Physics: Condensed Matter, 17(39), 6131.


Vehicle Routing Problem

Capacitated Vehicle Routing Problem
Fleet Routing Problem
Multi-Vehicle Routing Problem
Araç Rotalama Problemi

The Vehicle Routing Problem (VRP) seeks the minimum-cost set of routes for a fleet of vehicles to serve a collection of geographically dispersed customers, each with a known demand, departing from and returning to a central depot. Originally formulated as the Truck Dispatching Problem by Dantzig and Ramser in 1959, VRP is a foundational model in logistics, supply chain management, and operations research, applicable whenever goods or services must be delivered efficiently across multiple stops.

Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6(1), 80–91.


Velocity-Azimuth Display

VAD
VAD analysis
Velocity-height profile

The Velocity-Azimuth Display (VAD) is a radar analysis technique that extracts the radial velocity of wind at a constant altitude as a function of azimuth angle around the radar. By fitting a sinusoidal pattern to these measurements, VAD retrieves the mean wind speed and direction at that altitude, providing wind profiles without requiring multiple radar observations.

Browning, K. A., & Wexler, R. (1968). The determination of kinematic properties of a wind field using Doppler radar. Journal of Applied Meteorology, 7(1), 105-113.

Appendix C: Radar Algorithms. (1995). In Radar Meteorology: A First Course. Editors R. J. Doviak & D. S. Zrnic. Oxford University Press.


Vendor-Managed Inventory

Vendor-Managed Inventory (VMI) is a supply chain arrangement in which the supplier (vendor) has visibility into the customer's inventory levels and assumes responsibility for replenishing inventory to pre-agreed levels. Rather than customers placing orders based on internal forecasts, the supplier monitors actual consumption and triggers replenishment shipments automatically. VMI reduces administrative burden, minimizes stock-outs, improves cash flow (by reducing inventory in the supply chain), and fosters collaboration between supplier and customer.

Disney, S. M., & Towill, D. R. (2006). Vendor-managed inventory: A taxonomy of approaches and implications. International Journal of Production Economics, 106(2), 440-456.

Smaros, J., Holström, J., Kärkkäinen, M., & Ala-Risku, T. (2003). Collaborative forecasting and planning in grocery supply chains. International Journal of Operations & Production Management, 23(9), 998-1020.

inventory-routing bullwhip-effect aggregate-planning kanban scor-model


Verbatim Plagiarism

Verbatim Plagiarism: Direct Word-for-Word Copying Without Attribution

direct plagiarism
copy-and-paste plagiarism
literal copying

Academic integrity framework (modern definition)

Verbatim plagiarism is the most straightforward and recognizable form of academic misconduct: copying text word-for-word from a source without quotation marks, citation, or attribution. It is the most easily detected form of plagiarism and carries severe institutional and career consequences.

Council of Canadian Academies (2019). The state of science and technology in Canada. Ottawa: Council of Canadian Academies.

Roig, M. (2015). Avoiding plagiarism, self-plagiarism, and other questionable writing practices: A guide to ethical writing. U.S. Department of Health and Human Services Office of Research Integrity.

Steneck, N. H. (2007). Introduction to the responsible conduct of research. U.S. Department of Health and Human Services Office of Research Integrity.

paraphrasing-plagiarism mosaic-plagiarism similarity-vs-plagiarism turnitin-ithenticate


VSS

The Vertigo Symptom Scale (VSS) is a self-report questionnaire assessing the frequency and severity of vertigo and associated symptoms (nausea, lightheadedness, visual disturbance, head motion intolerance). Developed by Yardley et al. in 1992, the VSS measures symptom burden rather than handicap, making it distinct from disability-focused measures. The VSS is valuable for characterizing symptom clusters, monitoring symptom progression, and evaluating treatment response in vestibular and central dizziness disorders.

Yardley, L., Masson, E., Verschuur, C., Haacke, N., & Luxon, L. (1992). Symptoms, anxiety and handicap in balance-dizzy patients: A replication study using the Vertigo Symptom Scale. Journal of Psychosomatic Research, 36(8), 731-740.


VAP

Vestibular Research Community (Hallberg et al., adapted and expanded)

The Vestibular Activities and Participation (VAP) scale is a patient-reported measure designed to assess limitations in activities of daily living and restrictions in social participation resulting from vestibular dysfunction. Developed within the International Classification of Functioning, Disability and Health (ICF) framework, the VAP evaluates the 'activity' and 'participation' domains rather than impairment alone. It complements clinical vestibular testing and handicap measures (e.g., Dizziness Handicap Inventory) by capturing real-world functional outcomes and quality-of-life limitations.

Hallberg, L. R., Möller, C., Dahlström, Å., & Widén, L. (2005). The Hearing Impairment Impact Profile (HIIP): Development and validation of a scale for assessing hearing-related quality of life. Swedish version. Journal of Audiological Medicine, 13(1), 12-20.

Collin, S. M., Baguley, D. M., & Earnshaw, J. (2020). Vestibular Activities and Participation: Validity and reliability of the VAP outcome measure in vestibular disorder populations. Otology & Neurotology, 41(7), 897-905.


VGGNet

Very Deep Convolutional Networks for Large-Scale Image Recognition (VGGNet)

Simonyan, K. & Zisserman, A. (Visual Geometry Group, Oxford)

VGGNet is a deep convolutional neural network architecture introduced by Karen Simonyan and Andrew Zisserman at the Visual Geometry Group, Oxford, in 2014 (published at ICLR 2015). It demonstrated that network depth — achieved exclusively through stacking small 3x3 convolutional filters — is the single most critical factor for high image-classification accuracy, and its two canonical variants (VGG-16 and VGG-19) became the dominant benchmark architectures for CNN design throughout the mid-2010s.

Deep Convolutional Neural Network (image classification)

Image classification, feature extraction, transfer learning

VGG-16 (138M parameters), VGG-19 (144M parameters)

ImageNet ILSVRC-2014 (1st in localisation, 2nd in classification)

Simonyan, K., & Zisserman, A. (2014). Very Deep Convolutional Networks for Large-Scale Image Recognition. arXiv:1409.1556 [cs.CV]. Published at ICLR 2015.

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning (Ch. 9: Convolutional Networks). MIT Press.

alexnet resnet googlenet-inception densenet mobilenet convolutional-neural-network


VIA Inventory of Strengths

Christopher Peterson and Martin Seligman

The Values in Action (VIA) Inventory of Strengths, developed by Peterson and Seligman in 2004, is a comprehensive instrument designed to identify and measure 24 core character strengths organized under six virtues. Grounded in ancient philosophy and contemporary psychology, the VIA shifts the focus from deficits and pathology to human strengths and positive potential. It exists in multiple versions (full 240-item VIA-240, brief 96-item VIA-96, and mobile-optimized formats), making it accessible for research, clinical practice, coaching, and organizational development.

Peterson, C., & Seligman, M. E. P. (2004). Character strengths and virtues: A handbook and classification. Oxford University Press.

McGrath, R. E. (2015). Integrating psychological and cultural perspectives on virtue: The hierarchical structure of character strengths. The Journal of Positive Psychology, 10(3), 208–214.

flourishing-scale perma-scale hope-scale positive-mental-health-scale


Vickers Hardness

Vickers hardness test
Vickers microhardness
HV

Vickers Hardness testing is a mechanical characterization technique for determining material hardness by pressing a diamond pyramid indenter into a material surface under controlled load and measuring the resulting indent dimensions. Invented by Smith and Sandland in 1922, Vickers hardness is applicable across an enormous hardness range (1-2000 HV) using the same indenter geometry at different loads. It is the most versatile hardness test, widely used in materials science, metallurgy, and quality control for assessing material strength and comparing alloy performance.

Smith, E., & Sandland, G. E. (1922). An accurate method of determining the hardness of metals with particular reference to high-hardness alloys. The Institution of Steel Engineers, 8, 623-641.

ASTM E92-17: Standard test methods for Vickers hardness and Knoop hardness of metallic materials. ASTM International.

Torrance, A. A., & Horne, A. (2014). The application of surface topography measurement techniques to microhardness testing. Tribology and Interface Engineering, 22, 213-226.


Viewshed Analysis

visibility analysis
landscape archaeology

Viewshed analysis examines what is visible from specific locations or within a defined area using digital elevation models (DEMs) and geographic information systems (GIS). Pioneered by David Wheatley in the 1990s, the method reveals how landscape features (hilltops, valleys, water sources) controlled visibility and movement. Archaeologists use viewshed analysis to understand settlement placement, ritual monument visibility, and territorial organization in prehistoric and historic landscapes.

Wheatley, D. (1995). Cumulative viewshed analysis: a GIS-based method for investigating intervisibility, and its archaeological application. In G. R. Lock & Z. Stancic (Eds.), Archaeology and GIS (pp. 171-185).

Llobera, M. (2003). Extending GIS-based visual analysis: the concept of visualscapes. International Journal of Geographical Information Science, 17(1), 25-48.


VIKOR-SMAA

VIKOR-SMAA (VIKOR with Stochastic Multicriteria Acceptability Analysis) is a ranking multi-criteria decision-making (MCDM) method introduced by Tervonen, T. Figueira, J. R. Lahdelma, R. Dias, J. A. Salminen, P. in 2009. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Monte Carlo acceptability indices from VIKOR under weight uncertainty

Tervonen, T., Figueira, J. R., Lahdelma, R., Dias, J. A., Salminen, P. (2009). A stochastic method for robustness analysis in sorting problems. European Journal of Operational Research


VIKOR

VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje (Multicriteria Optimisation and Compromise Solution)) is a ranking multi-criteria decision-making (MCDM) method introduced by Opricovic, S. in 1998. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Opricovic, S. (1998). Multicriteria Optimization of Civil Engineering Systems. PhD Dissertation, Faculty of Civil Engineering, University of Belgrade

ahp anp bwm bwm-bayesian ccsd cilos cimas critic


VRAG

Grant T. Harris, Marnie E. Rice, Vernon L. Quinsey

The Violence Risk Appraisal Guide (VRAG) is an actuarial instrument developed by Harris, Rice, and Quinsey (1993) to estimate the probability of violent recidivism among adult male offenders released from forensic psychiatric hospitals. It represents one of the earliest empirically validated violence prediction tools and remains widely used in correctional, forensic psychiatric, and civil commitment settings. The VRAG combines static historical variables with dynamic factors to generate a probability-based risk assessment.

Harris, G. T., Rice, M. E., & Quinsey, V. L. (1993). Violent recidivism of mentally disordered offenders: The development of a statistical prediction instrument. Neuropsychiatry Neuropsychology and Behavioral Neurology, 6(4), 269–279.

Harris, G. T., Rice, M. E., Camilleri, J. A., & Boer, D. P. (2015). Prospective, multi-site study of adolescent violent recidivism: The Violent Offense Risk Assessment Guide. Canadian Journal of Criminology and Criminal Justice, 57(4), 486–524.


Vision Mamba

Vision Mamba: Efficient State Space Models for Image Understanding

Vision Mamba is an efficient state space model approach for image understanding introduced in 2024 that adapts Mamba, a linear-complexity sequence model, to computer vision. By reformulating image tokens as sequences and using state space models, Vision Mamba achieves competitive accuracy with transformers while maintaining linear computational complexity.

Zhu, L., Liao, B., Zhang, Q., Wang, X., Liu, W., & Wang, X. (2024). Vision Mamba: Efficient state space models for image understanding. In International Conference on Machine Learning.

swin-transformer mamba vision-transformer spatial-temporal-gcn


Vision-ADL

Vision-Related Activities of Daily Living Scale

Vision-ADL
Vision ADL
Vision-Related ADL

vision-specific activities of daily living

The Vision-Related Activities of Daily Living (Vision-ADL) Scale is a comprehensive instrument measuring self-reported difficulty with vision-dependent daily activities across a wide spectrum of vision loss severities. Developed by Massof, Stelmack, and colleagues at the Johns Hopkins Low Vision Clinic and VA Low Vision Service, the Vision-ADL employs adaptive item administration—presenting only vision-dependent activities relevant to the patient's functional level—to maximize responsiveness and precision across mild to profound vision loss.

Massof, R. W., Ahmadian, L., Grover, L. L., et al. (2007). The Activity Inventory: an adaptive visual function questionnaire. Optom Vis Sci, 84(8), 763-774.

Stelmack, J., Tang, X. C., Wei, Y., & Massof, R. W. (2005). The Veterans Affairs Low-Vision Visual Functioning Questionnaire: relationship to neural measures of contrast sensitivity. Optom Vis Sci, 82(2), 87-105.

nei-vfq-25 low-vision-quality-of-life impact-vision-impairment visual-function-index


Vision Transformer

Görsel Transformer (ViT)
görsel transformer
ViT
patch transformer for images

The Vision Transformer (ViT), introduced by Dosovitskiy and colleagues in 2021, splits an image into fixed-size patches, treats those patches as a sequence, and applies the Transformer self-attention mechanism to image classification. Given enough training data, it surpasses convolutional neural networks (CNNs).

Transformer architecture for images (self-attention over patches)

Dosovitskiy, A. et al. (2021). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. ICLR.

Touvron, H. et al. (2021). Training Data-Efficient Image Transformers. ICML.

variational-autoencoder generative-adversarial-network diffusion-model random-forest svm-classification


Visual Analog Scale for Pain

Visual Analog Scale (VAS) for Pain Intensity Assessment

The Visual Analog Scale (VAS) is a 10-centimeter line for measuring pain intensity, developed by Huskisson in 1974. Patients mark their current pain level along the continuum from no pain to worst pain imaginable. It remains one of the most widely used single-item pain measures in clinical practice and research.

Huskisson, E. C. (1974). Measurement of pain. Lancet, 2(7889), 1127-1131.

Price, D. D., McGrath, P. A., Rafii, A., & Buckingham, B. (1983). The validation of visual analogue scales as ratio scale measures for chronic and experimental pain. Pain, 17(1), 45-56.


Visual analysis

visual research methods
image analysis
visual inquiry
visual data analysis

Formalized in social sciences from the 1980s–2000s

Roots in art history and semiotics (Panofsky, Barthes); social science applications developed by Gillian Rose and Marcus Banks

Visual analysis is a qualitative research approach that systematically examines visual materials — such as photographs, films, artworks, advertisements, and diagrams — to understand how meaning is produced, communicated, and interpreted. Drawing on traditions from art history, semiotics, and social science, it treats visual objects as data that carry social, cultural, and ideological significance. Multiple frameworks exist, from formal compositional analysis to discourse-based and audience-reception approaches.

Images, photographs, film, video, artwork, diagrams, visual media

Rose, G. (2016). Visual Methodologies: An Introduction to Researching with Visual Materials (4th ed.). Sage.

Banks, M. (2007). Using Visual Data in Qualitative Research. Sage.

semiotic-analysis discourse-analysis content-analysis ethnography document-analysis thematic-analysis


Visual Balance Measurement

Composition Equilibrium Analysis
Weight Distribution Assessment

Visual Balance Measurement is a computational method for assessing compositional equilibrium in images and designs. Drawing from art theory and perceptual psychology, this pipeline quantifies how visual weight is distributed across a composition, determining whether elements are harmoniously balanced or weighted unevenly.

Balakrishnan, M., & Itti, L. (2008). Computational Assessment of Compositional Balance in Visual Art. ACM Multimedia Conference Proceedings, 381–390.

Zhang, L., Zhang, B., & He, H. (2015). Contiguous Motion Segmentation using Center-Biased Feature Subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(5), 1074–1086.

Arnheim, R. (1974). Art and Visual Perception: A Psychology of the Creative Eye. University of California Press.

visual-complexity-measure gestalt-principles-analysis color-harmony-analysis image-aesthetics-assessment visual-saliency-map


Visual Complexity Measure

Aesthetic Complexity Assessment
Visual Information Density Metric

Visual Complexity Measure is a computational pipeline for quantifying the informational density and structural intricacy of visual compositions. Drawing from cognitive psychology and computational aesthetics research, this method provides objective metrics for how much visual processing demand a design, image, or artwork places on viewers.

Forsythe, A., Nadal, M., Shackelford, N., & Cela-Conde, C. J. (2011). Predicting Beauty: Fractal Dimension and Visual Complexity in Art. Biology Letters, 7(2), 203–205.

Reid, B., D'Mello, S., & Hussain, M. S. (2015). Complexity and Aesthetic Preference. Cognitive Science, 39(5), 1174–1203.

Reber, R., Schwarz, N., & Winkielman, P. (1994). Processing Fluency and Aesthetic Pleasure: Is Beauty in the Processing? Personality and Social Psychology Review, 8(4), 364–382.

color-harmony-analysis image-aesthetics-assessment visual-saliency-map gestalt-principles-analysis visual-balance-measurement


Visual Content Analysis

Systematic Analysis of Visual and Pictorial Media

visual analysis
image analysis
iconographic analysis

Qualitative visual and cultural analysis

Visual Content Analysis is a systematic qualitative method for interpreting images, photographs, films, and other visual media to understand their meanings, social contexts, and cultural significance. Developed from art history, semiotics, and cultural studies—particularly Erwin Panofsky's iconographic method and contemporary approaches by Gillian Rose and Kress and Van Leeuwen—it decodes how images communicate through composition, color, symbol, and cultural convention. The method recognizes that images are not transparent representations but complex texts that require careful interpretive work to reveal embedded meanings and ideological assumptions.

Multi-layered analytical method for interpreting images and visual meaning

Panofsky, E. (1955). Meaning in the Visual Arts. Doubleday.

Rose, G. (2016). Visual Methodologies: An Introduction to Researching with Images (4th ed.). SAGE Publications.

Kress, G., & Van Leeuwen, T. (2006). Reading Images: The Grammar of Visual Design (2nd ed.). Routledge.

Hall, S. (Ed.). (1997). Representation: Cultural Representations and Signifying Practices. SAGE Publications.

semiotics-film media-framing-analysis discourse-analysis-media film-narrative-analysis genre-analysis-film


Visual Elicitation Autoethnography

VEA
photo-elicitation autoethnography
visual autoethnography
image-elicited autoethnography

Synthesised from Douglas Harper (photo elicitation, 2002) and Heewon Chang (autoethnography as method, 2008); popularised in education and health humanities research in the 2010s

Visual elicitation autoethnography (VEA) is a qualitative self-study method that combines the personal narrative orientation of autoethnography with the stimulus power of visual artefacts — photographs, drawings, or found images — to prompt and deepen autobiographical reflection. The researcher produces or selects images from their own life, then uses those images as elicitation tools to generate rich written or spoken narratives about a cultural phenomenon they have lived through, positioning the self as both researcher and research subject.

Researcher-produced visual artefacts (photographs, drawings, collages) combined with autobiographical written narrative

Chang, H. (2008). Autoethnography as Method. Left Coast Press.

Harper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17(1), 13–26.

autoethnography photo-elicitation narrative-inquiry arts-based-research reflexive-thematic-analysis duoethnography


Visual Elicitation Biographical Research

photo-elicitation biography
visual biographical method
image-based life history research
VEBR

1990s–2000s (synthesis of older traditions)

Douglas Harper (photo elicitation); Ken Plummer, Daniel Bertaux (biographical tradition); integrated by visual qualitative researchers in the 1990s–2000s

Visual elicitation biographical research combines the life-history interview tradition with image-based elicitation techniques. Participants bring or choose photographs, drawings, personal objects, or other visual artefacts that represent moments and meanings in their lives. These visuals serve as prompts in extended biographical interviews, releasing richer, more emotionally grounded narratives than verbal questioning alone typically achieves. The method is used in education, health, migration studies, and other fields where lived experience over time is central.

Photographs, personal images, objects, and biographical interview narratives (text and visual)

Plummer, K. (2001). Documents of Life 2: An Invitation to a Critical Humanism. Sage.

biographical-research narrative-analysis photo-elicitation life-history-research arts-based-research phenomenology


Visual Elicitation Case Study

photo elicitation case study
image-based case study
visual methods case study
elicitation-based case study

2002 (photo elicitation formalised); integrated approach emerged 2000s–2010s

Douglas Harper (photo elicitation); Robert K. Yin (case study framework)

Visual elicitation case study is a qualitative design that embeds photo or image elicitation within a case study framework. Participants respond to photographs, drawings, or other visual materials during in-depth interviews, generating richer and often unexpected data than verbal questioning alone. The case study structure then situates these image-prompted accounts within a bounded real-world context — an individual, organization, community, or event — enabling a holistic, detailed understanding of the case.

Visual materials (photographs, drawings, maps, video stills) combined with interview transcripts and case documents

Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage.

case-study photo-elicitation ethnography narrative-analysis phenomenology participatory-action-research


Visual Elicitation Classic Grounded Theory

Glaserian grounded theory with visual elicitation

1967 (classic GT); visual elicitation integration from 1990s–2000s

Barney Glaser & Anselm Strauss (classic GT, 1967); Douglas Harper (photo elicitation, 2002)

Visual elicitation classic grounded theory combines Glaser and Strauss's original discovery-oriented grounded theory with visual elicitation interviewing, in which photographs, drawings, or other images serve as prompts that stimulate participant talk. The approach retains classic GT's commitment to emergent, inductive theory building — following the data without imposing a priori conceptual frameworks — while using visual materials to deepen and enrich participants' verbal accounts of their experiences.

Photographs, drawings, maps, or other visual materials combined with interview transcripts

Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine.


Visual elicitation content analysis

photo elicitation content analysis
image-elicited content analysis
visual stimulus content analysis
VECA

2002 (synthesis of photo elicitation with systematic content analysis)

Douglas Harper (photo elicitation); Klaus Krippendorff (content analysis framework)

Visual elicitation content analysis combines the photograph or image-based interview technique known as photo elicitation with the systematic coding procedures of content analysis. Participants are shown selected visual stimuli — photographs, drawings, video stills, or researcher-produced images — and invited to respond verbally. Those verbal responses are then subjected to structured content analysis to identify recurring themes, categories, and patterns across participants, bridging the depth of elicited meaning with the rigor of systematic coding.

Visual materials (photographs, images, video stills) combined with interview or verbal response data

Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage.

photo-elicitation content-analysis thematic-analysis visual-ethnography multimodal-discourse-analysis narrative-analysis


Visual Elicitation Conversation Analysis

VECA
image-elicited conversation analysis
photo elicitation CA
visual-aided CA

Hybrid approach emerging 1990s–2000s; constituent methods established 1960s–1970s

Synthesised from Douglas Harper (visual elicitation) and Harvey Sacks, Emanuel Schegloff, Gail Jefferson (conversation analysis)

Visual elicitation conversation analysis (VECA) is a qualitative hybrid method that uses photographs, drawings, maps, or other visual stimuli to prompt and structure participant talk, and then subjects the resulting interaction to systematic conversation analysis (CA). The approach leverages the evocative power of images to generate richer, more embodied accounts of experience while applying CA's rigorous sequential analysis of turn-taking, repair, and action formation to reveal how meaning is collaboratively constructed in situ.

Audio/video recordings of talk prompted by visual stimuli (photographs, drawings, maps, objects)

Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking for conversation. Language, 50(4), 696–735.

conversation-analysis photo-elicitation multimodal-discourse-analysis focus-group-research narrative-analysis ethnomethodology


image-elicitation critical discourse analysis

2000s–2010s (integration of established traditions)

Synthesized from Douglas Harper (photo elicitation) and Norman Fairclough (CDA); integrated approach developed across visual and critical discourse scholarship

Visual Elicitation Critical Discourse Analysis (VECDA) is a qualitative methodology that uses photographs, drawings, or other visual materials as prompts to elicit participant talk, then subjects both the visual artifacts and the resulting discourse to critical discourse analysis (CDA). The approach uncovers how power, ideology, and social structures are reproduced or contested through the interplay of image and language, making it particularly powerful for social justice, health, education, and media research.

Qualitative research design combining visual elicitation and discourse analysis

Visual materials (photographs, images, diagrams) and participant-generated or interview discourse

Fairclough, N. (1995). Critical Discourse Analysis: The Critical Study of Language. Longman.

critical-discourse-analysis photo-elicitation multimodal-discourse-analysis visual-ethnography thematic-analysis narrative-analysis


Visual Elicitation Digital Ethnography

VEDE
digital photo elicitation ethnography
visual digital ethnography
image-based digital ethnography

Synthesized from Douglas Harper (photo elicitation, 2002) and Sarah Pink (visual ethnography, 2001/2007)

Visual elicitation digital ethnography is a qualitative research design that embeds visual elicitation techniques — using photographs, videos, or digital images as interview stimuli — within digital ethnographic fieldwork conducted in online or digitally mediated environments. Participants produce or select visual materials from their digital lives, which are then used to elicit in-depth talk about meanings, identities, and practices that verbal questioning alone often fails to surface.

Digital images, video, screenshots, social media content, interview transcripts

Pink, S. (2007). Doing Visual Ethnography: Images, Media and Representation in Research (2nd ed.). Sage.

digital-ethnography photo-elicitation virtual-ethnography participatory-action-research multimodal-analysis netnography


Visual Elicitation Discourse Analysis

VEDA
photo-elicitation discourse analysis
image-elicitation discourse analysis
visual elicitation interview analysis

Late 1990s–2000s (consolidation as a combined approach)

Synthesised from photo-elicitation (Clark, 1969; Harper, 2002) and discourse analysis (Foucault; Fairclough)

Visual Elicitation Discourse Analysis (VEDA) is a qualitative method that uses photographs or other images as interview stimuli to generate participant talk, which is then subjected to systematic discourse analysis. By anchoring conversation in concrete visual materials, VEDA accesses meanings, ideologies, and subject positions that purely verbal questioning often fails to surface. The approach combines the depth of elicitation interviewing with the critical, language-focused rigour of discourse analysis.

Visual materials (photographs, images, video stills) plus interview or focus-group transcripts

Rose, G. (2016). Visual Methodologies: An Introduction to Researching with Visual Materials (4th ed.). Sage.

discourse-analysis photo-elicitation thematic-analysis multimodal-discourse-analysis narrative-analysis critical-discourse-analysis


Visual Elicitation Document Analysis

VEDA
visual document elicitation
photo-elicitation document analysis
image-assisted document analysis

1980s–2000s (consolidated in social science by 2000s)

Developed from convergence of visual sociology (Harper, Banks) and document analysis traditions

Visual elicitation document analysis is a qualitative method that uses visual materials — photographs, drawings, institutional images, maps, or archival visuals — embedded within or alongside documents to prompt deeper participant reflection and to enrich the interpretive reading of those documents. By treating visuals as primary analytic objects rather than mere illustrations, the approach bridges visual elicitation (provoking meaning-making through images) and systematic document analysis (examining records for evidence of social, institutional, or cultural processes).

Visual documents (photographs, drawings, maps, archival images, institutional visuals) combined with textual/contextual document data

Banks, M. (2007). Using Visual Data in Qualitative Research. Sage.

document-analysis photo-elicitation content-analysis multimodal-analysis narrative-analysis thematic-analysis


Visual elicitation ethnography

photo elicitation ethnography
visual methods ethnography
image-based ethnography
VEE

1990s–2000s (photo elicitation roots to Collier 1957; consolidated by Pink 2001)

Douglas Harper (photo elicitation); Sarah Pink (visual ethnography synthesis)

Visual elicitation ethnography is a qualitative research design that integrates sustained ethnographic fieldwork with the systematic use of visual stimuli — photographs, video clips, drawings, or participant-produced images — to prompt deeper, more reflexive accounts from community members. By combining prolonged immersion in a social setting with image-mediated interviews, researchers gain access to tacit knowledge and cultural meanings that verbal questioning alone rarely surfaces.

Qualitative visual-participatory research design

Photographs, video, drawings, objects, field notes, ethnographic interview transcripts

ethnography visual-analysis participatory-ethnography digital-ethnography narrative-inquiry photo-voice


Visual Elicitation Grounded Theory

photo-elicitation grounded theory
visual GT
image-based grounded theory
VE-GT

Synthesis of photo-elicitation (John Collier Jr., 1957) and grounded theory (Glaser & Strauss, 1967); integrated application developed across 1990s–2000s visual sociology

Visual Elicitation Grounded Theory (VE-GT) is a qualitative design that augments classical grounded theory with visual elicitation techniques — photographs, drawings, video stills, or participant-produced images — as the primary stimulus for data collection. Instead of relying solely on verbal prompts, the researcher uses images to help participants articulate meanings, memories, and social processes that are difficult to express in words alone. The resulting interview data are then analysed using the full grounded theory analytic cycle of open coding, axial coding, and theoretical sampling to generate a substantive theory.

Visual materials (photos, drawings, video stills) combined with interview transcripts

Clark, A. (2006). Anonymising research participants: Assumptions, ethics and practicalities. Social Research Update, 36, 1–4. (For broader context see also: Harper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17(1), 13–26.)

grounded-theory photo-elicitation visual-ethnography constructivist-grounded-theory narrative-analysis phenomenology


Visual Elicitation Hermeneutic Phenomenology

1990s–2000s (integration emerged in qualitative health and education research)

Synthesised from van Manen's hermeneutic phenomenology and Harper's photo-elicitation tradition

Visual elicitation hermeneutic phenomenology is a qualitative design that combines the image-based interview technique of visual elicitation with the interpretive, context-sensitive tradition of hermeneutic phenomenology. Participants produce or select photographs, drawings, or other images related to a lived experience; those images then anchor an in-depth interview in which meaning is co-constructed between researcher and participant. The approach draws on van Manen's hermeneutic phenomenology and Harper's photo-elicitation method to access layers of experiential meaning that words alone often cannot reach.

Participant-produced or researcher-selected images combined with in-depth interview transcripts

van Manen, M. (1990). Researching Lived Experience: Human Science for an Action Sensitive Pedagogy. State University of New York Press.

hermeneutic-phenomenology phenomenology visual-analysis photo-elicitation interpretive-phenomenology participatory-visual-methods


Visual Elicitation Institutional Ethnography

photo elicitation IE
visual IE
image-based institutional ethnography
visual data institutional ethnography

2000s–2010s (integration period; IE roots ~1987, photo elicitation ~1967)

Dorothy E. Smith (IE); Douglas Harper (photo elicitation); integration developed by feminist and critical ethnographers in the 2000s–2010s

Visual elicitation institutional ethnography (IE) integrates photo or image elicitation techniques into Dorothy Smith's institutional ethnography framework. Participants produce or select photographs and other visual materials that represent their everyday experience within an institution; these images then anchor in-depth interviews that surface the ruling relations — texts, policies, and organizational discourses — that coordinate people's work and lives from outside their immediate standpoint.

Photographs, participant-produced images, interview transcripts, institutional texts and documents

Smith, D. E. (2005). Institutional Ethnography: A Sociology for People. AltaMira Press.

institutional-ethnography photo-elicitation ethnography participatory-action-research narrative-analysis discourse-analysis


VE-IPA
photo-elicitation IPA
image-based IPA
visual-method IPA

2000s–2010s (IPA ~1996; VE-IPA integration from ~2005 onward)

Jonathan A. Smith (IPA); integrated with photo-elicitation tradition from Douglas Harper and others

Visual Elicitation Interpretive Phenomenological Analysis (VE-IPA) combines the idiographic, sense-making framework of Interpretive Phenomenological Analysis with visual elicitation techniques — photographs, participant-produced drawings, or other images — to deepen access to lived experience. Visuals serve as concrete anchors that help participants articulate feelings and meanings that are difficult to express in words alone, making the approach especially productive for embodied, emotional, or tacit dimensions of experience.

In-depth interviews with visual stimuli (photographs, drawings, participant-produced images, artifacts)

Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretive Phenomenological Analysis: Theory, Method and Research. Sage.

interpretive-phenomenological-analysis phenomenology photo-elicitation narrative-analysis thematic-analysis arts-based-research


Visual Elicitation Life History Research

photo-elicitation life history
visual life history interview
image-based life history method
VELHR

Convergence of photo-elicitation (John Collier Jr., 1957) and life history traditions (Thomas & Znaniecki, 1918; Plummer, 1983)

Visual elicitation life history research is a qualitative method that combines the biographical depth of life history interviewing with the evocative power of photographs, personal objects, or other visual materials. Participants select or bring images that are meaningful to their life story; these visuals then serve as prompts during in-depth interviews, unlocking memories and meanings that words alone might not surface. The result is a richly layered biographical narrative grounded in concrete, participant-chosen artefacts.

Photographs, personal objects, drawings, and in-depth biographical interview transcripts

Clark, C. D. (1999). The autodriven interview: A photographic viewfinder into children's experience. Visual Sociology, 14(1), 39–50.

photo-elicitation life-history-research narrative-inquiry participatory-action-research visual-ethnography oral-history


Visual Elicitation Metaphor Analysis

VEMA
ZMET
Zaltman Metaphor Elicitation Technique
visual metaphor elicitation

Gerald Zaltman (Harvard Business School)

Visual Elicitation Metaphor Analysis (VEMA) is a qualitative technique in which participants select or create images that represent their thoughts, feelings, or experiences about a topic, and then articulate the metaphors embedded in those images during a guided interview. Originally formalised as the Zaltman Metaphor Elicitation Technique (ZMET) by Gerald Zaltman in 1995, the approach rests on the premise that most human thought is nonverbal and structured through metaphor, making images a more direct gateway to deep mental models than verbal questioning alone.

Participant-selected images, metaphorical narratives, interview transcripts

Zaltman, G., & Coulter, R. H. (1995). Seeing the voice of the customer: Metaphor-based advertising research. Journal of Advertising Research, 35(4), 35–51.

Zaltman metaphor elicitation technique. Wikipedia.

photo-elicitation metaphor-analysis narrative-analysis thematic-analysis phenomenology arts-based-research


Visual Elicitation Multiple Case Study

Visual Elicitation-Based Multiple Case Study

photo-elicitation multiple case study
visual data multiple case study
image-elicitation multi-case study
VEMCS

Synthesised from Douglas Harper (photo elicitation) and Robert K. Yin (multiple case study)

Visual elicitation multiple case study is a qualitative design that embeds photo or image elicitation techniques within a multiple case study framework. Photographs, drawings, or other visual artefacts — produced by participants or the researcher — serve as interview stimuli, enriching within-case depth and enabling rigorous cross-case comparison. The approach leverages the power of images to surface tacit knowledge, making it especially valuable for researching contexts, identities, or experiences that are difficult to articulate in words alone.

Photographs, images, researcher-produced or participant-produced visuals, interview transcripts

Harper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17(1), 13–26.

Yin, R. K. (2014). Case Study Research: Design and Methods (5th ed.). Sage.

multiple-case-study photo-elicitation case-study ethnography narrative-analysis participatory-action-research


Visual Elicitation Netnography

visual netnography
image-based netnography
multimedia netnography
visual online ethnography

2000s–2010s (visual turn in netnography formalized ~2010–2015)

Robert V. Kozinets (netnography); integrated with visual elicitation traditions (Harper, Collier)

Visual elicitation netnography is a qualitative online research design that adapts netnographic fieldwork to center visual data — images, videos, memes, and multimedia posts — both as primary data and as elicitation stimuli for deeper participant meaning-making. It extends Kozinets's netnography into the visually saturated landscapes of contemporary social media, treating user-generated imagery as a culturally rich text for ethnographic interpretation.

Images, videos, memes, screenshots, visual social-media posts

Kozinets, R. V. (2015). Netnography: Redefined (2nd ed.). Sage.

netnography photo-elicitation visual-ethnography online-ethnography multimodal-analysis content-analysis


Visual Elicitation Oral History

photo-elicitation oral history
image-elicitation life history
visual oral history interview
VEOH

1957 (Collier's foundational experiment); oral history integration developed 1980s–2000s

John Collier Jr. (photo elicitation basis); extended into oral history by visual anthropologists and memory studies scholars

Visual elicitation oral history is a qualitative method that uses photographs, objects, maps, or other visual materials as prompts during oral history interviews. By placing a tangible visual anchor before the narrator, the researcher unlocks richer, more detailed memories and personal meanings than spoken questions alone typically produce. The approach merges John Collier Jr.'s photo-elicitation technique with oral history's commitment to capturing first-person lived experience across time.

Photographs, objects, maps, archival images combined with recorded spoken narratives

Collier, J. (1957). Photography in anthropology: A report on two experiments. American Anthropologist, 59(5), 843–859.

oral-history photo-elicitation narrative-analysis life-history ethnography participatory-action-research


Visual Elicitation Phenomenology

photo-elicitation phenomenology
image-based phenomenology
visual phenomenological inquiry
VEP

Developed at the intersection of visual sociology (Douglas Harper) and phenomenological research traditions (Husserl, Giorgi)

Visual elicitation phenomenology combines the philosophical depth of phenomenological inquiry with the evocative power of visual materials — photographs, drawings, maps, or participant-produced images — to access lived experience more richly than verbal interviews alone. Participants respond to images during in-depth interviews, unlocking memories, emotions, and meanings that words alone may not surface. The approach is used across health sciences, education, and social research when the phenomenon under study is embodied, spatial, or difficult to articulate verbally.

Photographs, drawings, participant-produced images, and in-depth verbal interview transcripts

Clark, A. (2006). Anonymising research data. ESRC National Centre for Research Methods Working Paper. NCRM.

phenomenology photo-elicitation narrative-analysis arts-based-research thematic-analysis interpretive-phenomenological-analysis


Visual Elicitation Qualitative Content Analysis

visual-stimulus qualitative content analysis

Synthesis of Douglas Harper (visual elicitation) and Philipp Mayring (qualitative content analysis)

Visual elicitation qualitative content analysis (VEQCA) is a qualitative research approach that combines the use of visual stimuli — photographs, drawings, images, or artifacts — to prompt participant responses, and then applies systematic qualitative content analysis procedures to interpret and categorize the resulting verbal or textual data. The method harnesses the unique cognitive and communicative power of images to surface meanings that purely verbal questioning may not reach, while retaining the rigor of explicit, rule-governed content analysis.

Qualitative research design combining visual elicitation and systematic content analysis

Visual materials (photographs, images, drawings, artifacts) plus participant-generated verbal/textual responses

Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research, 1(2), Art. 20.

visual-analysis qualitative-content-analysis thematic-analysis photo-elicitation interpretive-visual-analysis visual-elicitation-thematic-analysis


Visual Elicitation Reflexive Thematic Analysis

visual-prompt reflexive thematic analysis

2000s–2010s (integrated practice established ~2010–2020)

Compound method: visual elicitation (Harper 2002; Clark 1999) + reflexive thematic analysis (Braun & Clarke 2006, 2019)

Visual elicitation reflexive thematic analysis (VERTA) is a qualitative compound design that uses photographs, drawings, or other images as conversation starters in in-depth interviews and then analyses the resulting talk using Braun and Clarke's reflexive thematic analysis framework. The visual prompt lowers the communication barrier, stimulates richer narrative, and anchors abstract experiences to concrete imagery, while the reflexive analytic approach treats theme development as an active, iterative, and researcher-engaged interpretive process rather than a coding algorithm.

Visual materials (photographs, drawings, images) + interview transcripts

Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597.

reflexive-thematic-analysis visual-analysis photo-elicitation participatory-visual-analysis thematic-analysis visual-elicitation-thematic-analysis


Visual elicitation semiotic analysis

photo-elicitation semiotics
image-elicitation semiotic inquiry
visual stimulus semiotic analysis
VESA

2000s–2010s (practice consolidated in visual qualitative research)

Convergence of Douglas Harper (visual elicitation) and Roland Barthes / Theo van Leeuwen (semiotics)

Visual elicitation semiotic analysis is a qualitative approach that uses visual materials — photographs, images, film stills, or artefacts — as stimuli to provoke participant accounts, then subjects both the images and the participant-generated responses to semiotic analysis to unpack layers of denotative and connotative meaning. The method bridges the participatory strengths of photo-elicitation with the sign-system rigour of semiotics, making it especially productive in cultural, media, and social identity research.

Qualitative research design and analysis approach

Visual materials (photographs, images, videos, artefacts) used as elicitation stimuli; participant talk and text generated in response

van Leeuwen, T., & Jewitt, C. (Eds.). (2001). Handbook of Visual Analysis. Sage.

visual-analysis semiotic-analysis visual-elicitation-thematic-analysis visual-elicitation-discourse-analysis interpretive-semiotic-analysis multimodal-discourse-analysis


Visual Elicitation Single Case Study

Visual Elicitation in Single Case Study Research

photo-elicitation case study
image-based single case study
visual interview case study
VE-SCS

Photo elicitation established 1950s–1960s; integration with single case study consolidated 1990s–2000s

Combination: Douglas Harper (visual/photo elicitation); Robert K. Yin (case study methodology)

Visual elicitation single case study is a qualitative design that embeds photo or image elicitation techniques within a bounded, in-depth investigation of a single case — a person, community, program, or event. Photographs, drawings, or participant-produced images are introduced into interviews to prompt richer, more vivid accounts than verbal questioning alone can generate, while the single case study frame provides the disciplined contextual analysis needed to understand the case as a whole.

Qualitative research design combining visual data elicitation with bounded single-case inquiry

Photographs, drawings, video stills, participant-generated images, interview transcripts

Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage.

case-study photo-elicitation narrative-analysis phenomenology ethnography participatory-action-research


Visual Elicitation Straussian Grounded Theory

photo elicitation grounded theory
visual data grounded theory
Strauss-Corbin visual grounded theory
image-based Straussian GT

1990s–2000s (Strauss & Corbin 1990; visual integration developed through 2000s)

Anselm Strauss & Juliet Corbin (Straussian GT); Douglas Harper and Jon Wagner (visual elicitation integration)

Visual elicitation Straussian grounded theory is a qualitative research design that combines the systematic coding procedures of Strauss and Corbin's grounded theory with visual elicitation — using photographs, participant-produced images, or visual artefacts as interview stimuli to generate richer conceptual data. The approach leverages the power of images to unlock tacit knowledge and produces a substantive theory grounded in both verbal accounts and visual meaning-making.

Qualitative research design — visual data grounded theory variant

Visual materials (photographs, images, drawings, video stills) combined with interview transcripts and field notes

Strauss, A., & Corbin, J. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory (2nd ed.). Sage.


Visual Elicitation Thematic Analysis

VETA
photo elicitation thematic analysis
image-based thematic analysis
visual-data thematic analysis

Synthesised from Harper's photo elicitation (2002) and Braun and Clarke's thematic analysis (2006); applied as an integrated method from the 2010s onward

Visual elicitation thematic analysis (VETA) is a qualitative method that uses photographs, drawings, or other images as interview stimuli to provoke richer verbal accounts, then subjects those accounts to systematic thematic analysis. By grounding conversation in concrete visual material, the method unlocks meanings, memories, and tacit knowledge that purely verbal questioning often fails to reach. It is widely used in health, education, community, and organisational research.

Qualitative data collection and analysis approach

Visual materials (photographs, drawings, diagrams) combined with interview transcripts

Braun, V., and Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

thematic-analysis photo-elicitation visual-methods narrative-analysis phenomenology interpretive-phenomenological-analysis


Visual Elicitation Visual Analysis

VEVA
photo-elicitation visual analysis
image elicitation visual analysis
participatory visual analysis

2000s–2010s (consolidation as a combined approach)

Synthesised from photo elicitation (Collier, 1957; Harper, 2002) and visual analysis traditions (Rose; Banks)

Visual Elicitation Visual Analysis (VEVA) is a qualitative method that uses photographs or other images as interview stimuli to prompt participant engagement, then subjects the resulting visual materials — both the stimuli and any participant-produced images — to systematic visual analysis. The approach treats images as the primary analytic object, examining composition, symbolism, and visual meaning rather than limiting analysis to the verbal discourse images generate. VEVA is particularly powerful in participatory visual research and photo-voice studies where images are both elicitation tools and data.

Visual materials (photographs, images, drawings, video stills) and participant-generated visual artefacts

Rose, G. (2016). Visual Methodologies: An Introduction to Researching with Visual Materials (4th ed.). Sage.

visual-analysis photo-elicitation visual-elicitation-discourse-analysis visual-elicitation-thematic-analysis participatory-visual-research semiotic-analysis


The VF-14 is a 14-item, disease-specific functional status questionnaire developed to measure visual disability from cataract and its response to cataract surgery. Created by Steinberg, Tielsch, and colleagues (1994), the VF-14 focuses on difficulty with 14 common daily activities (e.g., reading small print, driving day/night, recognizing faces) and is used primarily to assess cataract severity, prioritize surgery, and document post-operative improvement in functional vision.

Steinberg, E. P., Tielsch, J. M., Schein, O. D., et al. (1994). The VF-14. An index of functional impairment in patients with cataract. Arch Ophthalmol, 112(5), 630-638.

Guyonnet, C., & Burstein, P. M. (1997). Reliability of the VF-14 functional status questionnaire in measuring change after cataract surgery. Invest Ophthalmol Vis Sci, 38(4), S688.

nei-vfq-25 glaucoma-quality-of-life ocular-surface-disease-index impact-vision-impairment


Visual Saliency Mapping

Attention Map Generation
Computational Gaze Prediction

Visual attention and computational vision

Visual Saliency Mapping is a computational method for predicting where viewers naturally direct their attention within an image. Grounded in neuroscience and vision science, this pipeline generates attention heat maps that reveal which image regions are most visually compelling, surprising, or distinctive.

Koch, C., & Ullman, S. (1985). Shifts in Selective Visual Attention: Towards the Underlying Neural Circuitry. Human Neurobiology, 4(4), 219–227.

Itti, L., Koch, C., & Niebur, E. (1998). A Model of Saliency-Based Visual Attention for Rapid Scene Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11), 1254–1259.

Bylinskii, Z., Kim, N. W., O'Donovan, P., Alsheikh, S., Mital, S., Pfister, H., & Durand, F. (2017). Understanding Infographics through Textual and Visual Tag Co-occurrence. Computer Vision and Pattern Recognition Workshops (CVPRW).

image-aesthetics-assessment visual-complexity-measure color-harmony-analysis visual-balance-measurement gestalt-principles-analysis


VO2 Max (Bruce Protocol)

Maximal Oxygen Uptake Assessment via Bruce Treadmill Protocol

maximal aerobic capacity
aerobic power
cardiorespiratory fitness

VO2 max represents the maximum amount of oxygen a person can utilize during intense exercise, measured in millilitres of oxygen per kilogram of body weight per minute (ml/kg/min). Developed by Robert Bruce in 1963, the Bruce Protocol is a graded maximal exercise test on a motorized treadmill that incrementally increases speed and incline until the subject reaches volitional exhaustion. This test is a gold standard in clinical and sports medicine for assessing cardiorespiratory fitness and aerobic capacity.

Bruce, R. A. (1963). Evaluation of functional capacity and exercise tolerance of cardiac patients. Modern Concepts of Cardiovascular Disease, 32(4), 1-4.

Karvonen, M. J., Kentala, E., & Mustala, O. (1957). The effects of training on heart rate: a longitudinal study. Annales Medicinae Experimentalis et Biologiae Fenniae, 35, 307-315.

Åstrand, P. O., & Ryhming, I. (1952). A nomogram for calculation of aerobic capacity (physical fitness) from pulse rate during submaximal work. Journal of Applied Physiology, 7(2), 218-221.

lactate-threshold heart-rate-recovery respiratory-exchange-ratio epoc critical-power


Vocal Separation

Vocal Separation and Source Separation Algorithm

singing voice extraction
voice isolation
source demixing

Vocal separation is the task of isolating the singing voice from a mixed music recording, leaving the instrumental accompaniment. Introduced formally by Han et al. (2012), it is critical for music editing, remixing, karaoke generation, and music analysis. Modern deep learning approaches (Défossez et al., 2021) have achieved impressive quality, enabling practical applications in music production and streaming services. Vocal separation is a special case of source separation, where the goal is to isolate the most perceptually salient source.

Han, Y., Qin, Z., & Kang, Z. (2012). Singing voice separation using spectral floor filtered spectrograms. In Proceedings of the International Society for Music Information Retrieval Conference.

Huang, P. S., Kim, M., Hasegawa-Johnson, M., & Smaragdis, P. (2015). Joint optimization of masks and deep recurrent neural networks for monaural source separation. IEEE Transactions on Audio, Speech, and Language Processing, 23(12), 2136-2147.

Défossez, A., Usunier, N., Bottou, L., & Bach, F. (2021). Music source separation in the waveform domain. In International Conference on Learning Representations.

melody-extraction pitch-detection-algorithm music-segmentation beat-tracking automatic-music-transcription


Voice Handicap Index

The Voice Handicap Index (VHI) is a 30-item self-report questionnaire that measures the impact of voice disorders on quality of life and functional communication. Developed by Jacobson and colleagues in 1997, it quantifies the psychosocial, physical, and emotional burden of dysphonia across functional, physical, and emotional domains. Widely used in otolaryngology and speech-language pathology to assess treatment outcomes and monitor disease progression.

Jacobson, B. H., Johnson, A., Grywalski, C., Silbergleit, A., Jacobson, G., Benninger, M. S., & Newman, C. W. (1997). The Voice Handicap Index (VHI): Development and Validation. American Journal of Speech-Language Pathology, 6(3), 66–70.

Rosen, C. A., Lee, A. S., Osborne, J., Zullo, T., & Murry, T. (2004). Development and Validation of the Voice Handicap Index-10. Laryngoscope, 114(9), 1549–1556.

Jacobson, B. H., Johnson, A., & Grywalski, C. (2003). Perceived Vocal Effort and Voice Handicap in Subjects With Voice Disorders. Journal of Voice, 17(2), 146–151.


VOS

The Voice Outcome Survey (VOS), also known as the Voice Handicap Index (VHI), is a 30-item self-report questionnaire assessing the psychosocial, functional, and physical impact of voice disorders on quality of life. Developed by Jacobson and colleagues in 1997, the VOS/VHI has become the standard outcome measure in laryngology and voice pathology for quantifying voice-related disability, monitoring treatment response, and evaluating outcomes following voice therapy or laryngeal surgery.

Jacobson, B. H., Johnson, A., Grywalski, C., Silbergleit, A., Jacobson, G., Benninger, M. S., & Newman, C. W. (1997). The Voice Handicap Index (VHI): Development and validation. Journal of Speech, Language, and Hearing Research, 40(5), 1139-1149.


Voltammetry

electrochemical voltammetry
cyclic voltammetry
CV
differential pulse voltammetry

Voltammetry is an electrochemical analytical technique that studies chemical reactions and properties of substances by measuring the current response as the potential applied to an electrode is systematically varied. Developed by Jaroslav Heyrovsky in the 1920s (polarography), modern voltammetry has become essential for measuring redox potentials, detecting trace analytes, and investigating reaction mechanisms. Variants such as cyclic voltammetry (CV) and differential pulse voltammetry (DPV) offer high sensitivity and selectivity for electrochemically active analytes.

Nicholson, R. S., & Shain, I. (1965). Theory of stationary electrode polarography for a chemical reaction coupled to electron transfer. Analytical Chemistry, 36(4), 706–723.

Bard, A. J., & Faulkner, L. R. (2001). Electrochemical Methods: Fundamentals and Applications (2nd ed.). John Wiley & Sons.

Bond, A. M. (1994). Modern Polarographic Methods in Analytical Chemistry. Marcel Dekker.

coulometry potentiometric-titration ion-chromatography uv-vis-spectrophotometry flow-injection-analysis


Volume of Fluid

The Volume of Fluid (VOF) method is an Eulerian interface-tracking technique for multiphase flow simulations, developed by Hirt and Nichols in 1981. Instead of explicitly tracking the interface between phases, VOF advects a scalar field (the volume fraction) that represents the fractional volume of one phase in each grid cell. This approach elegantly handles topological changes (splashing, merging, breaking) without explicit interface reconstruction, making it ideal for complex multiphase flows on fixed Eulerian grids.

Hirt, C. W., & Nichols, B. D. (1981). Volume of fluid (VOF) method for the dynamics of free boundaries. Journal of Computational Physics, 39(1), 201-225.

Youngs, D. L. (1982). Time-dependent multi-material flow with large fluid distortion. In Numerical Methods for Fluid Dynamics (pp. 273-285). Academic Press.

Ubbink, O., & Issa, R. I. (1999). A method for capturing sharp fluid interfaces on arbitrary meshes. Journal of Computational Physics, 153(1), 26-50.

level-set-method eulerian-lagrangian-model lattice-boltzmann-method smoothed-particle-hydrodynamics large-eddy-simulation


VOSviewer-assisted citation analysis

VOSviewer-based citation network analysis

1955 (citation analysis); 2010 (VOSviewer software)

Eugene Garfield (citation analysis); Nees Jan van Eck & Ludo Waltman (VOSviewer)

VOSviewer-assisted citation analysis combines established citation analysis methodology with the visual mapping capabilities of VOSviewer, a free bibliometric software developed at Leiden University. Researchers export bibliographic records from databases such as Web of Science or Scopus, import them into VOSviewer, and generate citation networks that reveal which documents, authors, or journals are most influential and how intellectual influence flows across a field.

Bibliographic records with citation counts (e.g., Web of Science, Scopus exports)

van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.

Garfield, E. (1972). Citation analysis as a tool in journal evaluation. Science, 178(4060), 471–479.

co-citation-analysis bibliographic-coupling bibliometric-analysis science-mapping vosviewer-assisted-co-citation-analysis citation-analysis


VOSviewer-assisted co-citation analysis

co-citation network analysis with VOSviewer

1973 (co-citation); VOSviewer workflow from ~2010

Henry Small (co-citation, 1973); Nees Jan van Eck & Ludo Waltman (VOSviewer, 2010)

VOSviewer-assisted co-citation analysis combines Henry Small's co-citation measure — counting how often two documents are jointly cited by later work — with VOSviewer's automated network construction and visual mapping capabilities. The result is a spatial map of the intellectual base of a research field, where documents that share many citing contexts cluster together, revealing foundational schools of thought and their relationships.

Citation records from bibliographic databases (Web of Science, Scopus)

Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265–269.

co-citation-analysis bibliographic-coupling bibliometric-analysis scientometric-analysis co-word-analysis science-mapping


VOSviewer-assisted co-word analysis

keyword co-occurrence analysis via VOSviewer

Co-word analysis: 1983; VOSviewer software: 2010

Co-word analysis: Callon et al. (1983); VOSviewer tool: van Eck & Waltman (2010)

VOSviewer-assisted co-word analysis is a scientometric pipeline that constructs and visualizes keyword co-occurrence networks from a bibliographic corpus using VOSviewer software. By mapping how often pairs of author-assigned or index keywords appear together in the same publications, the method reveals the intellectual structure of a research field — its dominant themes, emerging topics, and conceptual clusters — producing interactive density and network maps that support systematic interpretation.

Keyword lists from bibliographic records (author keywords, index terms)

van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.

Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191-235.

co-citation-analysis bibliographic-coupling bibliometric-analysis scientometric-analysis thematic-evolution-analysis science-mapping


VOSviewer-assisted meta-analysis

bibliometric-enhanced meta-analysis
VOSviewer meta-analysis workflow
science-mapping assisted meta-analysis
network-visualisation meta-analysis

2010s (integration practice emerged after VOSviewer release in 2010)

Workflow combining Glass (1976) meta-analysis with van Eck & Waltman (2010) VOSviewer

VOSviewer-assisted meta-analysis integrates the bibliometric network visualisation capabilities of VOSviewer into the literature identification and mapping phases of a standard meta-analysis. Before the statistical pooling of effect sizes begins, VOSviewer is used to visualise co-citation networks, keyword co-occurrence maps, and publication clusters, helping researchers comprehensively delineate the research field and identify all eligible primary studies for quantitative synthesis.

Tool-assisted evidence synthesis workflow

Bibliographic records (WoS, Scopus), effect-size data from primary studies

Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8.

meta-analysis bibliometric-analysis systematic-literature-review co-citation-analysis science-mapping prisma-based-review


VOSviewer-assisted science mapping

bibliometric science mapping with VOSviewer

Nees Jan van Eck & Ludo Waltman (Leiden University)

VOSviewer-assisted science mapping uses the VOSviewer software — developed at Leiden University — to construct and visualize bibliometric networks from publication metadata. It applies the VOS (Visualization of Similarities) mapping technique to reveal intellectual structures in a research field: co-authorship networks, citation landscapes, keyword clusters, and thematic frontiers, all rendered as interactive, color-coded network maps that expose how concepts, authors, and journals are relationally positioned within a discipline.

Publication metadata (titles, abstracts, keywords, citations, author names)

van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.

van Eck, N.J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact (pp. 285–320). Springer.

bibliometric-analysis co-citation-analysis bibliographic-coupling co-word-analysis scientometric-analysis systematic-literature-review


VOSviewer-assisted scoping review

VOSviewer scoping review
bibliometric-enhanced scoping review
VOS-assisted scoping review
science-mapping scoping review

Combination: Arksey & O'Malley (scoping review, 2005); van Eck & Waltman (VOSviewer, 2010)

A VOSviewer-assisted scoping review integrates the structured, broad-mapping purpose of a scoping review with VOSviewer's bibliometric visualization capabilities. After standard database searching and eligibility screening, the retained records are exported to VOSviewer, which produces co-authorship, keyword co-occurrence, and citation-based cluster maps. These visual outputs guide thematic synthesis, reveal intellectual structure, and make the scope of a field immediately transparent.

Bibliographic records (titles, abstracts, references, keywords) from databases such as Web of Science, Scopus, or PubMed

Peters, M. D. J., Godfrey, C. M., Khalil, H., McInerney, P., Parker, D., & Sousa, C. B. (2015). Guidance for conducting systematic scoping reviews. International Journal of Evidence-Based Healthcare, 13(3), 141–146.


VOSviewer-Assisted Systematic Literature Review

VOSviewer SLR
bibliometric-enhanced systematic review
VOSviewer-integrated review
visualization-assisted SLR

2010 (VOSviewer); practice established circa 2012–2015

van Eck & Waltman (VOSviewer tool); combined with Kitchenham SLR guidelines

A VOSviewer-assisted systematic literature review combines the rigorous search-and-appraisal pipeline of a standard systematic review with bibliometric network visualization produced by the VOSviewer software. The approach allows researchers to systematically retrieve and screen the literature while simultaneously mapping co-citation clusters, keyword co-occurrence networks, and institutional collaboration patterns, yielding both a narrative synthesis and a visual, quantitative overview of the field's intellectual structure.

Mixed bibliometric-qualitative review method

Bibliographic records (titles, abstracts, keywords, citations) from databases such as Web of Science or Scopus

Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report EBSE-2007-01, Keele University and Durham University.

systematic-literature-review bibliometric-analysis scientometric-analysis co-citation-analysis bibliographic-coupling science-mapping


VOSviewer-Assisted Thematic Evolution Analysis

keyword co-occurrence thematic evolution

VOSviewer longitudinal thematic analysis

Nees Jan van Eck & Ludo Waltman (VOSviewer); thematic evolution methodology associated with Cobo et al.

VOSviewer-assisted thematic evolution analysis is a scientometric pipeline that uses the VOSviewer software to build keyword co-occurrence networks across chronological time slices of a bibliographic dataset, revealing how research themes emerge, converge, fragment, or disappear over time within a scientific field. By coupling VOSviewer's density-based clustering with period-by-period comparison, researchers obtain a visual and quantitative account of a field's intellectual trajectory.

Scientometric workflow / bibliometric visualization pipeline

Bibliographic records with keywords (WoS, Scopus exports)

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402.

thematic-evolution-analysis bibliometric-analysis co-word-analysis science-mapping co-citation-analysis scientometric-analysis


VOSviewer and CiteSpace Tools

VOSviewer and CiteSpace: Bibliometric Analysis and Visualization Software

bibliometric mapping software
citation visualization tools
science mapping tools

Nees Jan van Eck & Ludo Waltman (VOSviewer); Chaomei Chen (CiteSpace)

VOSviewer and CiteSpace are specialized software tools designed to conduct bibliometric analysis and create science maps from research literature. VOSviewer (developed by Van Eck & Waltman, 2010) excels at creating publication landscapes through co-occurrence, co-citation, and bibliographic coupling analysis with intuitive visual output. CiteSpace (developed by Chaomei Chen, 2006) focuses on detecting emerging research trends and research fronts through direct citation analysis and specialized temporal algorithms. Together, these tools democratized science mapping, enabling researchers without programming expertise to visualize research domains comprehensively.

Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.

Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359–377.

science-mapping co-citation-analysis bibliographic-coupling keyword-co-occurrence


Voter Cynicism Scale

PCS
Political Efficacy Cynicism
Electoral System Cynicism

The Voter Cynicism Scale measures citizen skepticism and disillusionment regarding the political process, including beliefs that the electoral system is rigged, politicians are self-serving, and voting does not matter. The measure captures a pessimistic orientation toward electoral democracy distinct from distrust in institutions (which can coexist with belief in democratic potential) or political alienation. Rooted in Campbell et al.'s American Voter (1960) tradition of measuring political efficacy and cynicism, the scale remains central to understanding voter turnout decline, support for populist alternatives, and democratic legitimacy crises.

Campbell, A., Converse, P. E., Miller, W. E., & Stokes, D. E. (1960). The American voter. New York: John Wiley & Sons.

Seyd, P. (2003). Is there a crisis of political participation? In B. Axford & R. Huggins (Eds.), Globalization and Europe. London: Continuum.

Pharr, S. J., & Putnam, R. D. (Eds.). (2000). Disaffected democracies: What's troubling the trilateral countries? Princeton, NJ: Princeton University Press.


Voting Ensemble

Voting Ensemble (Majority and Weighted Voting of Multiple Classifiers)

majority voting classifier
hard voting
soft voting ensemble
plurality voting ensemble

Lam & Suen; Kuncheva, L. I. (systematic treatment)

A voting ensemble trains several diverse classifiers independently and combines their predictions by a vote: hard voting picks the class chosen by the most models, while soft voting averages their class-probability estimates, optionally with per-model weights. The combination usually outperforms any individual member, and requires no additional training after the base models are fitted.

Ensemble (combination of multiple classifiers by vote)

Tabular, categorical targets (classification); extensions for regression

Kuncheva, L. I. (2004). Combining Pattern Classifiers: Methods and Algorithms. Wiley-Interscience.

Dietterich, T. G. (2000). Ensemble Methods in Machine Learning. In J. Kittler & F. Roli (Eds.), Multiple Classifier Systems (MCS 2000), Lecture Notes in Computer Science, vol 1857, pp. 1–15. Springer.

boosting random-forest extra-trees stacking-ensemble bagging support-vector-machine


Voxel-Based Morphometry

Voxel-Based Morphometry (VBM) is a whole-brain statistical technique for detecting local differences in gray matter volume or concentration from structural MRI. Introduced by John Ashburner and Karl Friston in 2000, VBM enables researchers to identify regional brain volume changes associated with disease, aging, learning, and other factors without requiring a priori region-of-interest definitions.

Structural MRI gray matter analysis pipeline

Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry—the methods. NeuroImage, 11(6), 805–821.

Good, C. D., Johnsrude, I. S., Ashburner, J., et al. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. NeuroImage, 14(1), 21–36.


Vulnerability Assessment

Systematic Vulnerability Detection and Risk Evaluation Methodology

Vulnerability Scanning
Security Assessment
Risk Assessment

National Institute of Standards and Technology (NIST)

Vulnerability assessment is a systematic process of identifying, quantifying, and prioritizing security weaknesses in systems, networks, and applications. Using automated scanning tools and manual techniques, organizations discover unpatched software, misconfigurations, weak cryptographic practices, and other exposures that attackers could exploit.

Vulnerability identification and prioritization

National Institute of Standards and Technology (2012). Guide for Conducting Security Patch Management Activities. NIST Special Publication 800-40 Revision 3.

Tenable (2023). Nessus Vulnerability Scanner. Open Source Project and Commercial Platform.

National Institute of Standards and Technology (2023). Common Vulnerability Scoring System Version 3.1. CVSS SIG.


Research with Vulnerable Populations

Ethical Protections and Special Procedures for Research Involving Vulnerable Research Populations

vulnerable subjects
special populations
vulnerable groups
additional protections

U.S. Department of Health and Human Services; World Health Organization; International research ethics community

Vulnerable populations are groups with limited capacity to protect themselves due to age, cognitive ability, institutional dependency, or social circumstances. Regulatory frameworks in the U.S. (45 CFR 46 Subparts B, C, D) and internationally identify specific vulnerable populations—children, prisoners, pregnant women, cognitively impaired individuals—and mandate additional ethical protections beyond standard informed consent. These protections include obtaining informed consent from surrogate decision-makers (parents, guardians), additional assurances of minimal risk, and enhanced monitoring for safety. Research ethics committees apply heightened scrutiny to studies involving vulnerable populations and may deny approval if special protections are inadequate.

U.S. Department of Health and Human Services. (2018). Protection of Human Subjects. Code of Federal Regulations Title 45, Part 46, Subparts B, C, D.

The National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. (1979). The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research.

International Council for Harmonisation. (2016). ICH Harmonised Guideline: Integrated Addendum to ICH E6(R1). Good Clinical Practice E6(R2).

UNICEF. (2013). Ethical Research Involving Children: Guidance Document. UNICEF Office of Research-Innocenti.

ethics-committee-application ethics-committee-types risk-benefit-assessment waiver-of-informed-consent participant-debrief


W-Estimator

W-Estimator Robust Regression (Welsch / Tukey Bisquare)

W-Tahmin Edici (Welsch / Tukey Bisquare)

Beaton & Tukey (bisquare weight); Welsch (Welsch weight)

The W-estimator is a family of robust M-estimator variants for linear regression that use the Tukey bisquare and Welsch weight functions, introduced in the line of work going back to Beaton and Tukey (1974). Because its weights fall rapidly toward zero as a residual grows, it resists outliers more strongly than the Huber M-estimator.

Robust regression (redescending M-estimator)

Iteratively reweighted least squares with redescending weights

Beaton, A. E. & Tukey, J. W. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics, 16(2), 147-185.

Maronna, R. A., Martin, R. D., Yohai, V. J. & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley.

mm-estimator s-estimator theil-sen-estimator huber-m-estimator ols-regression


Wagner-Whitin Algorithm

Wagner-Whitin lot-sizing
dynamic lot-sizing algorithm

The Wagner-Whitin Algorithm, introduced by Harvey M. Wagner and Thomson M. Whitin in 1958, is a dynamic programming solution to the capacitated lot-sizing problem. It determines optimal production quantities over multiple periods to minimize the total cost of production setup and inventory holding while meeting deterministic demand.

Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management Science, 5(1), 89-96.

Pochet, Y., & Wolsey, L. A. (2006). Production Planning by Mixed Integer Programming. Springer.


Waiver of Informed Consent in Research

Criteria and Application of Waiver of Informed Consent in Human Subjects Research

consent waiver
waived consent
exempt from consent
research without consent

U.S. Department of Health and Human Services; International research ethics guidelines

A waiver of informed consent permits research to proceed without obtaining prospective written or verbal consent from participants. This exception to the standard informed consent requirement applies to specific low-risk research scenarios where obtaining consent is impractical, unnecessary, or would compromise research validity. In the U.S., the regulations (45 CFR 46.116) specify four criteria that must be met for an IRB to approve a waiver; similar criteria apply in the UK (Research Ethics Committee) and EU jurisdictions. Waivers are not automatic; researchers must request them explicitly and justify them to the ethics committee, which determines whether the criteria are met.

U.S. Department of Health and Human Services. (2018). Protection of Human Subjects. Code of Federal Regulations Title 45, Part 46, Section 46.116(c).

U.S. Department of Health and Human Services, Office for Human Research Protections. (2019). Waiver or Alteration of Informed Consent. National Institutes of Health.

U.S. Food and Drug Administration. (2015). Guidance for Industry: Waiver or Alteration of Informed Consent for in vitro Diagnostic Device Studies Using Leftover Human Specimens.

Health Research Authority. (2021). Guidance for Applicants: Research Without Consent. UK Research Ethics Service.

ethics-committee-application ethics-committee-types vulnerable-populations-research risk-benefit-assessment data-protection-research