Published May 15, 2023 | Version 2.1
Technical note Open

Common Impact Data Standard Version 2.1

Authors/Creators

  • 1. Common Approach
  • 1. Impact Management Project
  • 2. z Centre for Social Services Engineering, University of Toronto,
  • 3. Common Approach to Impact Measurement
  • 4. Logical Outcomes
  • 5. threshold.world and b.world
  • 6. Salesforce Nonprofit Cloud
  • 7. Salesforce
  • 8. Riddl
  • 9. Common Approach
  • 10. Carleton University

Description

An Ontology for Representing Impact

The Common Impact Data Standard (Data Standard) is a standardized way to represent a social purpose organization’s impact model (i.e. a theory of change, logic model, outcome chain, etc.) and the effects of their work on people and the planet. 

The purpose of the Common Impact Data Standard is to create a shared data model with which to capture, export, and import data about impact measurement. The standard is essentially a set of detailed descriptions of how data should be structured to allow interoperability with other aligned software products. This approach allows data to be moved between applications without any additional mapping.

Files

Common Approach_Common Impact Data Standard v2.1.pdf

Files (14.6 MB)

Additional details

Related works

Cites
Technical note: 10.5281/zenodo.4295989 (DOI)

References

  • Fox, M., Chionglo, J.F., and Fadel, F.G., (1993), "A Common Sense Model of the Enterprise", Proceedings of the 2nd Industrial Engineering Research Conference , pp. 425-429, Norcross GA: Institute for Industrial Engineers.
  • Fox, M.S., Barbuceanu, M., Gruninger, M., and Lin, J., (1998), "An Organisation Ontology for Enterprise Modeling", In Simulating Organizations: Computational Models of Institutions and Groups, M. Prietula, K. Carley & L. Gasser (Eds), Menlo Park CA: AAAI/MIT Press, pp. 131-152.
  • Fox, M.S., (2013), "A Foundation Ontology for Global City Indicators", Working Paper, Enterprise Integration Laboratory, University of Toronto, Revised 13 October 2017.
  • Fox, M.S. (2015) "The Role of Ontologies in Publishing and Analyzing City Indicators", Computers, Environment and Urban Systems, Vol. 54, pp. 266-279.
  • Horridge, M., Drummond, N., Goodwin, J., Rector, A. L., Stevens, R., & Wang, H. (2006, November). The Manchester OWL syntax. In OWLed (Vol. 216).
  • Poblet, M., Casanovas, P., & Rodríguez-Doncel, V. (2019). Introduction to Linked Data. In Linked Democracy (pp. 1-25). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-030-13363-4_1
  • Rijgersberg, H., Wigham, M., and Top, J.L., (2011), "How Semantics can Improve Engineering Processes: A Case of Units of Measure and Quantities", Advanced Engineering Informatics, Vol. 25, pp. 276-287.
  • Ralser, T., (2008). Organizational Value/Nonprofit ROI. ROI For Nonprofits: The New Key to Sustainability (pp. 51–66). Hoboken, New Jersey: Wiley.