Published April 14, 2021
| Version v1
Conference paper
Open
Usefulness and Impact of Big Data in Libraries: An Opportunity to Implement Embedded Librarianship
Description
The concept of Big Data has been extensively considered as a technological modernisation in Library & Information centres. According to IDC, data volume is set to increase exponentially and envisages a data volume of over 160 zettabytes by the year 2025. Size is the first, and at times, the only dimension that leaps out at the mention of Big Data. Big Data is defined as information overload due to the volume, velocity, variety, variability & veracity of the data which must be processed to get value and better visualisation. Big Data contains the answer to several valuable questions related to patterns, trends & associations of user behaviour. It plays a major role in helping libraries to clearly understand the changing user needs, accordingly, reshape & restructure their services & procedures. The primary focus of this study was to explore the concept of Big Data in a library environment, steps to introduce Big Data in libraries and the use of Big Data in providing library services using the concept of data life cycle developed by DataONE. The main influential components to perform this study was the capabilities of Big Data analytics, the need & usefulness of Big Data practices, its significant utilisation in libraries and discuss some globally taken practical initiatives. The study highlights the important role of Big Data analytics capabilities to uncover new challenges of information utilisation, consequently helps a librarian to fulfil his role as an Embedded Librarian, both in theoretical & practical terms.
Files
Content Pages -- TIECML Proceedings.pdf
Additional details
References
- Al-Barashdi, H., & Al-Karousi, R. (2019). Big Data in academic libraries: literature review and future research directions. Journal of Information Studies & Technology (JIS&T), 2018(2). https://doi.org/10.5339/jist.2018.13
- Ball, R. (2019). Big Data and Their Impact on Libraries. American Journal of Information Science and Technology, 3(1), 1. https://doi.org/10.11648/j.ajist.20190301.11
- Blummer, B., & Kenton, J. M. (2019). Big Data and Libraries: Identifying Themes in the Literature. Internet Reference Services Quarterly, 23(1-2), 15–40. https://doi.org/10.1080/10875301.2018.1524337
- CCSDS. (2012). CCSDS Recommended Practice for an OAIS Reference Model (Recommended Practice, Issue 2, p. 20). CCSDS Secretariat. https://public.ccsds.org/Pubs/650x0m2.pdf
- Chesnut, M. T., Henderson, S. M., Schlipp, J., & Zai, R. (2009). Value-added library resources and services through Blackboard. Kentucky Libraries, 73(1), 6–12.
- DataONE. (n.d.). Data Life Cycle | DataONE. Retrieved January 10, 2021, from https://old.dataone.org/data-life-cycle#:~:text=The%20DataONE%20data%20life%20cycle%20has%20eight%20components%3A
- DDS. (2021). The Importance of Libraries (and Librarians) to the Data Science Movement. https://www.discoverdatascience.org/resources/data-science-and-librarians/#:~:text=Libraries%20can%20support%20data%20scientists
- Figa, E., Bone, T., & Macpherson, J. R. (2009). Faculty-Librarian Collaboration for Library Services in the Online Classroom: Student Evaluation Results and Recommended Practices for Implementation. Journal of Library & Information Services in Distance Learning, 3(2), 67–102. https://doi.org/10.1080/15332900902979119
- Gibbons, S. (2013). Techniques to understand the changing needs of library users. IFLA Journal, 39(2), 162–167. https://doi.org/10.1177/0340035212472846
- Hamad, F., Fakhuri, H., & Abdel Jabbar, S. (2020). Big Data Opportunities and Challenges for Analytics Strategies in Jordanian Academic Libraries. New Review of Academic Librarianship, 1–24. https://doi.org/10.1080/13614533.2020.1764071
- Hamad, F., Tbaishat, D., & Al-Fadel, M. (2016). The role of social networks in enhancing the library profession and promoting academic library services: A comparative study of the University of Jordan and Al-Balqaa' Applied University. Journal of Librarianship and Information Science, 49(4), 397–408. https://doi.org/10.1177/0961000616656043
- HESA. (2019). HESA - Experts in higher education data and analysis. https://www.hesa.ac.uk/
- IFLA. (2018). A concept data science framework for libraries. https://www.ifla.org/files/assets/big-data/publications/a_concept_data_science_framework_for_libraries.pdf
- Impact. (2016, April 7). The 7 V's of Big Data. https://impact.com/marketing-intelligence/7-vs-big-data/
- Jain, A. (2016, September 17). The 5 V's of Big Data. Watson Health Perspectives. https://www.ibm.com/blogs/watson-health/the-5-vs-of-big-data/
- Jantti, M. (2016). Libraries and Big Data. In Quality and the Academic Library: Reviewing, Assessing and Enhancing Service Provision (pp. 267–273). Chandos Publishing. https://doi.org/10.1016/b978-0-12-802105-7.00026-9
- Jisc. (n.d.). Jisc: Powering world-class education and research. https://www.jisc.ac.uk/
- Kesselman, M. A., & Watstein, S. B. (2009). Creating Opportunities: Embedded Librarians. Journal of Library Administration, 49(4), 383–400. https://doi.org/10.1080/01930820902832538
- Kaladhar, A., Naick, B. R. D., & Rao, K. S. (2018). Application of Big Data Technology to Library data: A review. International Journal of Library and Information Studies, 8(2), 25–30. http://www.ijlis.org/img/2018_Vol_8_Issue_2/25-30.pdf
- Kamupunga, W., & Chunting, Y. (2019). Application of Big Data in Libraries. International Journal of Computer Applications, 178(16), 34–38. https://doi.org/10.5120/ijca2019918955
- Kiran, R. (2019, December 20). What are the Characteristics of Big Data? | 5V's, Types, Benefits. https://www.edureka.co/blog/big-data-characteristics/
- Lenny, D. (2001). Application Delivery Strategies (p. 949). META Group Inc. http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf
- Lillard, L. L. (2003). Personalized instruction and assistance services for distance learners: Cultivating a research relationship. Research Strategies, 19(3-4), 204–212. https://doi.org/10.1016/j.resstr.2004.11.003
- MarketsandMarkets. (2020, March). Big Data Market by Component, Deployment Mode, Organization Size, Business Function (Operations, Finance, and Marketing and Sales), Industry Vertical (BFSI, Manufacturing, and Healthcare and Life Sciences), and Region - Global Forecast to 2025. https://www.marketsandmarkets.com/Market-Reports/big-data-market-1068.html
- Martin. (2011). Big Data, BI, digital preservation and the cloud. https://www.martinsights.com/?p=745
- Nunns, J. (Ed.). (2015, May 6). 10 of the most popular Big Data tools for developers. Computer Business Review. https://www.cbronline.com/big-data/10-of-the-most-popular-big-data-tools-for-developers-4570483/
- Olendorf, R., & Wang, Y. (2017). Big Data in Libraries. In S. C. Suh & T. Anthony (Eds.), Big Data and Visual Analytics (pp. 191–202). Springer International Publishing. https://doi.org/10.1007/978-3-319-63917-8_11
- Pearlman, S. (2018). What is Data Processing? Definition and Stages - Talend Cloud Integration. https://www.talend.com/resources/what-is-data-processing/
- Reinsel, D., Gantz, J., & Rydning, J. (2018). The Digitization of the World From Edge to Core. https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf
- Sengupta, S. (2016). Big Data: The Next Big Opportunity For Librarians. International Conference on Contemporary Innovations in Library Information Science, Social Science & Technology for Virtual World, 89–91. http://eprints.rclis.org/34349/1/final-proceeding-iicclist16-2s-view-50-51.pdf
- Shepley, S. E. (2009). Building a Virtual Campus: Librarians as Collaborators in Online Course Development and Learning. Journal of Library Administration, 49(1-2), 89–95. https://doi.org/10.1080/01930820802312821
- Shumaker, D. (2009). Who let the librarians out? Embedded librarianship and the library manager. Reference & User Services Quarterly, 48(3), 239–257.
- Sonawane, A. S. (2018). Big Data: Application in Libraries. International Journal of Scientific Research in Multidisciplinary Studies, 4(1), 22–23. https://www.isroset.org/pdf_paper_view.php?paper_id=529&6-LI-01.pdf
- Sugimoto, C. R., Ding, Y., & Thelwall, M. (2012). Library and information science in the Big Data era: Funding, projects, and future [a panel proposal]. Proceedings of the American Society for Information Science and Technology, 49(1), 1–3. https://doi.org/10.1002/meet.14504901187
- Tableau Software. (2018). Tableau: Business Intelligence and Analytics Software. https://www.tableau.com/
- Wang, C., Xu, S., Chen, L., & Chen, X. (2016, June). Exposing library data with Big Data technology: A review. 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS). https://doi.org/10.1109/icis.2016.7550937