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Data For Good

Data for Good is a technology enhanced social movement that aims to bring the power of data and data science to solving social problems. Volunnteers with data science and related skills work with nonprofits that are addressing today's most serious issues. This is an exciting new area of social change practice. There are interesting commonalities with civic technology, citizen science and data activism.


Bloomberg Data4gd  https://www.bloomberg.com/company/d4gx/

Center for Civic Media MIT https://civic.mit.edu/

Data for Black Lives  http://d4bl.org/

Data For Good  https://dataforgood.ca/

Data Kind https://www.datakind.org/

The Data Culture Group https://dataculturegroup.org/

Engagement Lab at Emerson College  https://elab.emerson.edu/

NYU GovLab  http://www.thegovlab.org/

Radical AI Podcast  https://www.radicalai.org/

SAS Data for Good  https://www.sas.com/en_us/data-for-good.html


Abebe, R., Barocas, S., Kleinberg, J., Levy, K., Raghavan, M., & Robinson, D. G. (2020, January). Roles for computing in social change. In Proceedings of the 2020 conference on fairness, accountability, and transparency (pp. 252-260).

Alemanno, A. (2018). Big Data for Good: Unlocking Privately-Held Data to the Benefit of the Many. European Journal of Risk Regulation: EJRR, 9(2), 183-191.

Alvarado Garcia, A., Young, A. L., & Dombrowski, L. (2017). On Making Data Actionable: How Activists Use Imperfect Data to Foster Social Change for Human Rights Violations in Mexico. Proceedings of the ACM on Human-Computer Interaction, 1(CSCW), 1-19.

Alvarado Garcia, A., Britton, M. J., Doshi, D. M., De Choudhury, M., & Le Dantec, C. A. (2021). Data Migrations: Exploring the Use of Social Media Data as Evidence for Human Rights Advocacy. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), 1-25.

Alvarado Garcia, A., & Le Dantec, C. A. (2018). Quotidian Report: Grassroots Data Practices to Address Public Safety. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1-18.

Angarita, M. A. M., & Nolte, A. (2020, September). What do we know about hackathon outcomes and how to support them?–A systematic literature review. In International Conference on Collaboration Technologies and Social Computing (pp. 50-64). Springer, Cham.

Auerbach, J., Barton, H., Blunt, T., Chaganti, V., Ghai, B., Meng, A., ... & Flores, P. (2017). Using data science as a community advocacy tool to promote equity in urban renewal programs: An analysis of Atlanta's anti-displacement tax fund. arXiv preprint arXiv:1710.02454.

Aula, V., & Bowles, J. (2023). Stepping back from Data and AI for Good–current trends and ways forward. Big Data & Society, 10(1), 20539517231173901.

Bixler, R. P., Zappone, M., Li, L. R., & Atshan, S. (2018). Unpacking the role of data in philanthropy: Prospects for an integrated framework. The Foundation Review, 10(2), 8.

Bull, P., Slavitt, I., & Lipstein, G. (2016). Harnessing the power of the crowd to increase capacity for data science in the social sector. arXiv preprint arXiv:1606.07781.

Catlett C, Ghani R (2015) Big data for social good Big Data 3:1, 1–2, DOI: 10.1089/big.2015.1530.

Chartier, T. (2017). Data for Good: Tracking Trillion-Dollar Problems. Math Horizons, 24(4), 18-21.

Choi, J., & Tausczik, Y. (2017, February). Characteristics of collaboration in the emerging practice of open data analysis. In Proceedings of the 2017 ACM conference on computer supported cooperative work and social computing (pp. 835-846).

Cukier, K., & Mayer-Schoenberger, V. (2013). The rise of big data: How it's changing the way we think about the world. Foreign Aff., 92, 28

Dencik, L., Hintz, A., & Cable, J. (2016). Towards data justice? The ambiguity of anti-surveillance resistance in political activism. Big Data & Society, 3(2), DOI 2053951716679678.

De Russis, L., Kumar, N., & Mathur, A. (2020, September). Data4Good: Designing for Diversity and Development. In Proceedings of the International Conference on Advanced Visual Interfaces (pp. 1-2).

Diesner, J. (2015). Small decisions with big impact on data analytics. Big Data & Society, 2(2), 2053951715617185.
Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A. (2020). Computational Social Science and Sociology. Annual Review of Sociology, 46.

Erete, S., Ryou, E., Smith, G., Fassett, K. M., & Duda, S. (2016, February). Storytelling with data: examining the use of data by non-profit organizations. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (pp. 1273-1283). ACM.

Espinoza, M. I., & Aronczyk, M. (2021). Big data for climate action or climate action for big data?. Big Data & Society, 8(1), 2053951720982032.

Evans, B. J., & Krumholz, H. M. (2018). People-powered data collaboratives: fueling data science with the health-related experiences of individuals. Journal of the American Medical Informatics Association, 26(2), 159-161.

Falk Olesen, J., & Halskov, K. (2020, July). 10 Years of Research With and On Hackathons. In Proceedings of the 2020 ACM Designing Interactive Systems Conference (pp. 1073-1088).

Farmer, J., McCosker, A., Albury, K., & Aryani, A. (2023). Data for Social Good: Non-Profit Sector Data Projects (p. 127). Springer Nature.

Fruchterman, J. (2016). Using data for action and for impact. Stanford Social Innovation Review, 20.

Green, B. (2021). Data science as political action: Grounding data science in a politics of justice. Journal of Social Computing2(3), 249-265.

Gupta, K., Ripberger, J., & Wehde, W. (2018). Advocacy group messaging on social media: Using the narrative policy framework to study Twitter messages about nuclear energy policy in the United States. Policy Studies Journal, 46(1), 119-136.

Gutiérrez, M. (2018). Proactive Data Activism. In Data Activism and Social Change (pp. 49-105). Palgrave Pivot, Cham.

Gutiérrez, M. (2018). Data activism and social change. New York: Palgrave Macmillan.

Hager, G. D., Drobnis, A., Fang, F., Ghani, R., Greenwald, A., Lyons, T., ... & Tambe, M. (2019). Artificial intelligence for social good. arXiv preprint arXiv:1901.05406.

Happonen, A., Minashkina, D., Nolte, A., Angelica, M., & Angarita, M. (2020, May). Hackathons as a company–University collaboration tool to boost circularity innovations and digitalization enhanced sustainability. In AIP Conference Proceedings (Vol. 2233, No. 1, p. 050009). AIP Publishing LLC.

Heeks, R. & Renken, J. (2018) Data justice for development: what would it mean?, Information Development, 34(1), 90-102

Hellmann, D., Maitland, C., & Tapia, A. (2016, February). Collaborative analytics and brokering in digital humanitarian response. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (pp. 1284-1294). ACM.

Hou, Y., & Wang, D. (2017). Hacking with NPOs: collaborative analytics and broker roles in civic data hackathons. Proceedings of the ACM on Human-Computer Interaction, 1(CSCW), 53.

Howson, C., Beyer, M.A. Idoine, C.J, .Jones, L.C.  (2018). How to Use Data for Good to Impact Society.  Gartner. G00355735  https://www.gartner.com/doc/3880666/use-data-good-impact-society

Johnson, J. A. (2014). From open data to information justice. Ethics and Information Technology, 16(4), 263-274.

Kagan, D., Chesney, T., & Fire, M. (2019). Using Data Science to Understand the Film Industry's Gender Gap. arXiv preprint arXiv:1903.06469.
Kamstra, P., Farmer, J., McCosker, A., Gardiner, F., Dalton, H., Perkins, D., ... & Bagheri, N. (2022). A novel mixed methods approach for integrating not-for-profit service data via qualitative Geographic Information System to explore authentic experiences of ill-health: A case study of rural mental health. Journal of Mixed Methods Research, 15586898221135291.

Kannengießer, S. (2019). Reflecting and acting on datafication–CryptoParties as an example of re-active data activism. Convergence, 1354856519893357.

Karusala, N., Wilson, J., Vayanos, P., & Rice, E. (2019). Street-Level Realities of Data Practices in Homeless Services Provision. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-23.

Kennedy, H. (2018). Living with data: Aligning data studies and data activism through a focus on everyday experiences of datafication. Krisis: Journal for Contemporary Philosophy, (1).

Khovanskaya, V., Sengers, P., & Dombrowski, L. (2020, April). Bottom-Up Organizing with Tools from On High: Understanding the Data Practices of Labor Organizers. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-13).

Kim, S., Mankoff, J., & Paulos, E. (2015, April). Exploring barriers to the adoption of mobile technologies for volunteer data collection campaigns. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 3117-3126). ACM.

Kinsella, B. (2021) Data Science for Social Good Volunteer Motivations and Limitations: An Exploratory Survey, Chance, 34:3, W86-W95, DOI: 10.1080/09332480.2021.1981055

Kolkowska, E., Susha, I., & van Loenen, B. (2017). Data sharing mechanisms and privacy challenges in Data Collaboratives: Delphi study of most important issues. In TILTing perspectives 2017, Regulating a connected world, Tilburg University, Tilburg, the Netherlands, May 17-19, 2017.

Kontokosta, C. E. (2018). Urban informatics in the science and practice of planning. Journal of Planning Education and Research, 0739456X18793716.

Kontokosta, C. E., & Malik, A. (2018). The Resilience to Emergencies and Disasters Index: Applying big data to benchmark and validate neighborhood resilience capacity. Sustainable cities and society, 36, 272-285.

Lapucci, M., & Cattuto, C. (2021). Data Science for Social Good: Philanthropy and Social Impact in a Complex World. Springer International Publishing AG.

Lane, J., Stodden, V., Bender, S., & Nissenbaum, H. (Eds.). (2014). Privacy, big data, and the public good: Frameworks for engagement. Cambridge University Press.

Leng, Y., Rudolph, L., Pentland, A. S., Zhao, J., & Koutsopolous, H. N. (2016). Managing travel demand: Location recommendation for system efficiency based on mobile phone data. arXiv preprint arXiv:1610.06825.

Lowman, M. (Ed.). (2017). A Practical Guide to Analytics for Governments: Using Big Data for Good. New York:  John Wiley & Sons.

Marivate, V., & Moorosi, N. (2018, May). Exploring data science for public good in South Africa: evaluating factors that lead to success. In Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age (p. 6). ACM.

McCosker, A., Yao, X., Albury, K., Maddox, A., Farmer, J., & Stoyanovich, J. (2022). Developing data capability with non-profit organisations using participatory methods. Big Data & Society, 9(1), 20539517221099882.

McKeever, B., Greene, S., MacDonald, G., Tatian, P. & Jones. D.  (2018). Data Philanthropy: Unlocking the Power of Private Data for Public Good. Washington, DC: Urban Institute.

McNutt, J.G.  (2018) (ed)  Technology, Activism and Social Justice in a Digital Age. London & New York:  Oxford University Press. 

McNutt, J. G., & Goldkind, L. (2020). Civic Technology and Data for Good: Evolutionary Developments or Disruptive Change in E-Participation?. In Digital Government and Achieving E-Public Participation: Emerging Research and Opportunities (pp. 124-142). IGI Global.

Meijer, A., & Potjer, S. (2018). Citizen-generated open data: An explorative analysis of 25 cases. Government Information Quarterly, 35(4), 613-621.

Meng, A., DiSalvo, C., & Zegura, E. (2019). Collaborative Data Work Towards a Caring Democracy. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 42.

Meng, A. (2014). Investigating the roots of open data’s social impact. JeDEM-eJournal of eDemocracy and Open Government, 6(1), 1-13.

Milan, S., & Almazor, M. G. (2015). Citizens’ media meets big data: The emergence of data activism. Mediaciones, 11(14), 120-133.

Mohammed, O., Manohar, K., Gillette, K., Murphy, B., & Hosein, P. (2022, December). Data4Good: An Established Framework for supporting Civil Society Organizations. In 2022 IEEE International Humanitarian Technology Conference (IHTC) (pp. 73-78). IEEE.

Mayer, D. J., & Fischer, R. L. (2022). Exploring data use in nonprofit organizations. Evaluation and Program Planning, 102197.

Niño, M., Zicari, R. V., Ivanov, T., Hee, K., Mushtaq, N., Rosselli, M., ... & Besier, J. (2017). Data projects for “social good”: challenges and opportunities.
Int. J. Hum. Soc. Sci, 11, 1094-1104.

Noveck, B. S. (2015). Smart citizens, smarter state: The technologies of expertise and the future of governing. Cambridge:  Harvard University Press. 

Ottinger, G. (2010). Buckets of resistance: Standards and the effectiveness of citizen science. Science, Technology, & Human Values, 35(2), 244-270

Pfaff, T. (2015). The Definitive Guide to doing Data Science for Social Good.  https://www.kdnuggets.com/2015/07/guide-data-science-good.html

Poel, M., Meyer, E. T., & Schroeder, R. (2018). Big data for policymaking: Great expectations, but with limited progress?. Policy & Internet, 10(3), 347-367.

Porway, J. (2021July 14) Charting the ‘Data for Good’ Landscape. Data.org https://data.org/news/charting-the-data-for-good-landscape/

Shi, Z. R., Wang, C., & Fang, F. (2020). Artificial intelligence for social good: A survey. arXiv preprint arXiv:2001.01818.

Smith, A. (2016). Shared, Collaborative and On Demand: The New Digital Economy. Washington, DC: Pew Internet & American Life Project. Retrieved May, 21, 2016.\

Schrock, A. R. (2016). Civic hacking as data activism and advocacy: A history from publicity to open government data. New Media & Society, 18(4), 581-599.

Schrock, A. (2018). Civic Tech: Making Technology Work for People. Rouge Academic Press.  Available at https://www.civictechs.com/

Schrock, A., & Shaffer, G. (2017). Data ideologies of an interested public: A study of grassroots open government data intermediaries. Big Data & Society, 4(1), 2053951717690750.

Susha, I., Janssen, M., & Verhulst, S. (2017). Data collaboratives as “bazaars”? A review of coordination problems and mechanisms to match demand for data with supply. Transforming Government: People, Process and Policy, 11(1), 157-172.

Susha, I., Janssen, M., Verhulst, S., & Pardo, T. (2017, June). Data collaboratives: How to create value from data for public problem solving?: Panel. In Proceedings of the 18th Annual International Conference on Digital Government Research (pp. 604-606). New York: ACM.

Susha, I., Janssen, M., & Verhulst, S. (2017). Data collaboratives as a new frontier of cross-sector partnerships in the age of open data: taxonomy development.

Susha, I., & Gil-Garcia, J. R. (2019, January). A Collaborative Governance Approach to Partnerships Addressing Public Problems with Private Data. In Proceedings of the 52nd Hawaii International Conference on System Sciences.

Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751-752.

Tripp, W., Gage, D., & Williams, H. (2020). Addressing the data analytics gap: A community-university partnership to enhance analytics capabilities in the non-profit sector. Collaborations: A Journal of Community-Based Research and Practice, 3(1).
Varshney, K. R., & Mojsilovic, A. (2019). Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact. arXiv preprint arXiv:1905.11519.

Verhulst, S., & Sangokoya, D. (2015). Data collaboratives: Exchanging data to improve people’s lives. https://medium. com/@ sverhulst/data-collaboratives-exchanging-data-to-improvepeople-s-lives-d0fcfc1bdd9a.

Verhulst SG & Young, A.  (2017) The Potential of Social Media Intelligence to Improve People’s Lives. The Governance Lab.
Available at http://www.thegovlab.org/static/files/publications/social-media-data.pdf.

Verhulst, S. G., & Young, A. (2019). The potential and practice of data collaboratives for migration. In Guide to Mobile Data Analytics in Refugee Scenarios (pp. 465-476). Springer, Cham.

Williams, U., Brown, R., Davis, M., Pavri, T., & Shafiei, F. (2021). Teaching Data Science in Political Science: Integrating Methods with Substantive Curriculum. PS: Political Science & Politics, 1-4.

Wong, W. H. & Brown, P. A. (2013). E-bandits in global activism: Wikileaks, Anonymous, and the politics of no one. Perspectives on Politics, 11(4), 1015–1033.

Wong, Y. C., Law, C. K., Fung, J. Y. C., & Lam, J. C. Y. (2009). Perpetuating old exclusions and producing new ones: digital exclusion in an information society
. Journal of Technology in Human Services, 27(1), 57–78.

Zegura, E., DiSalvo, C., & Meng, A. (2018, June). Care and the Practice of Data Science for Social Good. In Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (p. 34). ACM.

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