skip to main content
10.1145/3536169.3537788acmotherconferencesArticle/Chapter ViewAbstractPublication PagespdcConference Proceedingsconference-collections
research-article

A Participatory Approach to Eliciting Local Values of Civic Data Justice

Published:19 August 2022Publication History

ABSTRACT

This article is a response to scholars calling for conceptualizing local values of data justice. Such values are grounded in the ways local communities utilize and understand data that has been created for their use. To elicit these values, I organized 11 data literacy workshops with community leaders in Atlanta’s Historic Westside neighborhoods. Analyzing the qualitative data I gathered from these workshops using Grounded Theory (GT) allowed me to identify three values of data justice that were prioritized by community leaders. These include (i) Support the community’s data infrastructure literacy, (ii) Empower the community through data, and (iii) Foster accountability through data. These local values and the methods I used to engage with the Westside can guide other researchers interested in creating civic data infrastructures with their communities.

References

  1. Chris Anderson. 2008. The End of Theory: The Data Deluge Makes the Scientific Method Obsolete. Wired (2008). https://www.wired.com/2008/06/pb-theory/Google ScholarGoogle Scholar
  2. Stefan Baack. 2015. Datafication and empowerment: How the open data movement re-articulates notions of democracy, participation, and journalism. Big Data & Society 2, 2 (2015), 2053951715594634.Google ScholarGoogle ScholarCross RefCross Ref
  3. Liam Bannon and Pelle Ehn. 2013. Design Design Matters in Participatory Design. In Routledge international handbook of participatory design, Jesper Simonsenand Toni Robertson (Eds.). Routledge, 37–63.Google ScholarGoogle Scholar
  4. Jo Bates, Yu-Wei Lin, and Paula Goodale. 2016. Data journeys: Capturing the socio-material constitution of data objects and flows. Big Data & Society 3, 2 (2016), 2053951716654502.Google ScholarGoogle ScholarCross RefCross Ref
  5. Rahul Bhargava. [n.d.]. Remix a Visualization. https://databasic.io/en/culture/remixGoogle ScholarGoogle Scholar
  6. Rahul Bhargava. 2017. You Don’t Need a Data Scientist, You Need a Data Culture. https://datatherapy.org/2017/12/06/building-a-data-culture/Google ScholarGoogle Scholar
  7. Alan Borning and Michael Muller. 2012. Next steps for value sensitive design. In Proceedings of the SIGCHI conference on human factors in computing systems. 1125–1134.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Pam Briggs and Lisa Thomas. 2015. An inclusive, value sensitive design perspective on future identity technologies. ACM Transactions on Computer-Human Interaction (TOCHI) 22, 5(2015), 1–28.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. John M Carroll, Jordan Beck, Shipi Dhanorkar, Jomara Binda, Srishti Gupta, and Haining Zhu. 2018. Strengthening community data: towards pervasive participation. In Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age. 1–9.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. John M Carroll and Mary Beth Rosson. 2013. Wild at home: The neighborhood as a living laboratory for HCI. ACM Transactions on Computer-Human Interaction (TOCHI) 20, 3(2013), 1–28.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Alan Chamberlain, Andy Crabtree, Tom Rodden, Matt Jones, and Yvonne Rogers. 2012. Research in the wild: understanding’in the wild’approaches to design and development. In Proceedings of the Designing Interactive Systems Conference. 795–796.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Sasha Costanza-Chock. 2018. Design justice: Towards an intersectional feminist framework for design theory and practice. Proceedings of the Design Research Society(2018).Google ScholarGoogle ScholarCross RefCross Ref
  13. Christopher A Le Dantec and Carl DiSalvo. 2013. Infrastructuring and the formation of publics in participatory design. Social Studies of Science 43, 2 (2013), 241–264.Google ScholarGoogle ScholarCross RefCross Ref
  14. Tim Davies. 2010. Open data, democracy and public sector reform. A look at open government data use from data. gov. uk (2010), 1–47.Google ScholarGoogle Scholar
  15. Lina Dencik, Arne Hintz, and Jonathan Cable. 2016. Towards data justice? The ambiguity of anti-surveillance resistance in political activism. Big Data & Society 3, 2 (2016), 2053951716679678.Google ScholarGoogle ScholarCross RefCross Ref
  16. Michael Ann DeVito, Ashley Marie Walker, and Julia R Fernandez. 2021. Values (Mis) alignment: Exploring Tensions Between Platform and LGBTQ+ Community Design Values. Proceedings of the ACM on Human-Computer Interaction 5, CSCW1(2021), 1–27.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Catherine D’Ignazio and Rahul Bhargava. [n.d.]. Data Culture. https://databasic.io/en/culture/Google ScholarGoogle Scholar
  18. Catherine D’Ignazio and Rahul Bhargava. 2016. DataBasic: Design principles, tools and activities for data literacy learners. The Journal of Community Informatics 12, 3 (2016).Google ScholarGoogle ScholarCross RefCross Ref
  19. Catherine D’ignazio and Lauren F Klein. 2020. Data feminism. MIT press.Google ScholarGoogle Scholar
  20. Lynn Dombrowski, Ellie Harmon, and Sarah Fox. 2016. Social justice-oriented interaction design: Outlining key design strategies and commitments. In Proceedings of the 2016 ACM Conference on Designing Interactive Systems. 656–671.Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Marian Dörk, Patrick Feng, Christopher Collins, and Sheelagh Carpendale. 2013. Critical InfoVis: exploring the politics of visualization. In CHI’13 Extended Abstracts on Human Factors in Computing Systems. 2189–2198.Google ScholarGoogle Scholar
  22. Catherine d’Ignazio and Lauren F Klein. 2016. Feminist data visualization. Workshop on Visualization for the Digital Humanities (VIS4DH), Baltimore. IEEE.Google ScholarGoogle Scholar
  23. Paul N Edwards, Steven J Jackson, Geoffrey C Bowker, and Cory P Knobel. 2007. Understanding infrastructure: Dynamics, tensions, and design. (2007).Google ScholarGoogle Scholar
  24. Sheena Erete, Emily Ryou, Geoff Smith, Khristina Marie Fassett, and Sarah Duda. 2016. 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. 1273–1283.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Stephen Few. 2006. Information dashboard design: The effective visual communication of data. Vol. 2. O’reilly Sebastopol, CA.Google ScholarGoogle Scholar
  26. Mark Frank, Johanna Walker, Judie Attard, and Alan Tygel. 2016. Data Literacy-What is it and how can we make it happen?The Journal of Community Informatics 12, 3 (2016).Google ScholarGoogle Scholar
  27. Batya Friedman and David G Hendry. 2019. Value sensitive design: Shaping technology with moral imagination. Mit Press.Google ScholarGoogle Scholar
  28. Batya Friedman, Peter H. Kahn Jr., and Alan Borning. 2008. Value Sensitive Design and Information Systems. John Wiley & Sons, Ltd, Chapter 4, 69–101. https://doi.org/10.1002/9780470281819.ch4 arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/9780470281819.ch4Google ScholarGoogle Scholar
  29. Jonathan Gray, Carolin Gerlitz, and Liliana Bounegru. 2018. Data infrastructure literacy. Big Data & Society 5, 2 (2018), 2053951718786316.Google ScholarGoogle ScholarCross RefCross Ref
  30. Erik Grönvall, Lone Malmborg, and Jörn Messeter. 2016. Negotiation of values as driver in community-based PD. In Proceedings of the 14th Participatory Design Conference: Full papers-Volume 1. 41–50.Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Michael Gurstein. 2003. Effective use: A community informatics strategy beyond the digital divide. First Monday (2003).Google ScholarGoogle Scholar
  32. Michael B Gurstein. 2011. Open data: Empowering the empowered or effective data use for everyone?First Monday (2011).Google ScholarGoogle Scholar
  33. Donna Haraway. 2020. Situated knowledges: The science question in feminism and the privilege of partial perspective. In Feminist theory reader. Routledge, 303–310.Google ScholarGoogle Scholar
  34. Richard Heeks and Jaco Renken. 2018. Data justice for development: What would it mean?Information Development 34, 1 (2018), 90–102.Google ScholarGoogle ScholarCross RefCross Ref
  35. Richard Heeks and Satyarupa Shekhar. 2019. Datafication, development and marginalised urban communities: An applied data justice framework. Information, Communication & Society 22, 7 (2019), 992–1011.Google ScholarGoogle ScholarCross RefCross Ref
  36. Lilly C Irani and M Six Silberman. 2013. Turkopticon: Interrupting worker invisibility in amazon mechanical turk. In Proceedings of the SIGCHI conference on human factors in computing systems. 611–620.Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Nassim JafariNaimi, Lisa Nathan, and Ian Hargraves. 2015. Values as hypotheses: design, inquiry, and the service of values. Design issues 31, 4 (2015), 91–104.Google ScholarGoogle Scholar
  38. Jeffrey Alan Johnson. 2014. From open data to information justice. Ethics and Information Technology 16, 4 (2014), 263–274.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Jeffrey Alan Johnson. 2016. The value—and limits—of distributive justice in information privacy. In Western Political Science Association 2016 Annual Meeting, San Diego, CA. 23–26.Google ScholarGoogle Scholar
  40. Helena Karasti and Jeanette Blomberg. 2018. Studying infrastructuring ethnographically. Computer Supported Cooperative Work (CSCW) 27, 2 (2018), 233–265.Google ScholarGoogle ScholarCross RefCross Ref
  41. Finn Kensing and Joan Greenbaum. 2013. Heritage: having a say. In Routledge international handbook of participatory design, Jesper Simonsenand Toni Robertson (Eds.). Routledge, 21–36.Google ScholarGoogle Scholar
  42. Rob Kitchin and Tracey Lauriault. 2014. Towards critical data studies: Charting and unpacking data assemblages and their work. (2014).Google ScholarGoogle Scholar
  43. Rob Kitchin, Tracey P Lauriault, and Gavin McArdle. 2015. Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards. Regional Studies, Regional Science 2, 1 (2015), 6–28.Google ScholarGoogle ScholarCross RefCross Ref
  44. Jes A Koepfler, Katie Shilton, and Kenneth R Fleischmann. 2013. A stake in the issue of homelessness: Identifying values of interest for design in online communities. In Proceedings of the 6th International Conference on Communities and Technologies. 36–45.Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Christopher A Le Dantec, Erika Shehan Poole, and Susan P Wyche. 2009. Values as lived experience: evolving value sensitive design in support of value discovery. In Proceedings of the SIGCHI conference on human factors in computing systems. 1141–1150.Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Yanni Alexander Loukissas. 2017. Taking Big Data apart: local readings of composite media collections. Information Communication and Society 20, 5 (2017), 651–664. https://doi.org/10.1080/1369118X.2016.1211722Google ScholarGoogle ScholarCross RefCross Ref
  47. Shannon Mattern. 2016. Interfacing urban intelligence. Code and the City 4960(2016).Google ScholarGoogle Scholar
  48. Michael Muller. 2014. Curiosity, creativity, and surprise as analytic tools: Grounded theory method. In Ways of Knowing in HCI. Springer, 25–48.Google ScholarGoogle Scholar
  49. Michael Muller, Ingrid Lange, Dakuo Wang, David Piorkowski, Jason Tsay, Q Vera Liao, Casey Dugan, and Thomas Erickson. 2019. How data science workers work with data: Discovery, capture, curation, design, creation. In Proceedings of the 2019 CHI conference on human factors in computing systems. 1–15.Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Michael J Muller and Sandra Kogan. 2010. Grounded theory method in HCI and CSCW. Cambridge: IBM Center for Social Software 28, 2 (2010), 1–46.Google ScholarGoogle Scholar
  51. Tim O’Reilly. 2011. Government as a Platform. Innovations: Technology, Governance, Globalization 6, 1(2011), 13–40.Google ScholarGoogle Scholar
  52. Nassim Parvin. 2018. Doing justice to stories: On ethics and politics of digital storytelling. Engaging Science, Technology, and Society 4 (2018), 515–534.Google ScholarGoogle ScholarCross RefCross Ref
  53. Firaz Peer and Carl DiSalvo. 2019. Workshops as Boundary Objects for Data Infrastructure Literacy and Design. In Proceedings of the 2019 on Designing Interactive Systems Conference. 1363–1375.Google ScholarGoogle Scholar
  54. Aare Puussaar, Ian G Johnson, Kyle Montague, Philip James, and Peter Wright. 2018. Making open data work for civic advocacy. Proceedings of the ACM on Human-Computer Interaction 2, CSCW(2018), 1–20.Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Ingrid Robeyns. 2003. The capability approach: an interdisciplinary introduction. In Training course preceding the Third International Conference on the Capability Approach, Pavia, Italy. 29.Google ScholarGoogle Scholar
  56. Yvonne Rogers. 2011. Interaction design gone wild: striving for wild theory. interactions 18, 4 (2011), 58–62.Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Yvonne Rogers and Paul Marshall. 2017. Research in the Wild. Synthesis Lectures on Human-Centered Informatics 10, 3(2017), i–97.Google ScholarGoogle Scholar
  58. Susan Leigh Star and Anselm Strauss. 1999. Layers of silence, arenas of voice: The ecology of visible and invisible work. Computer supported cooperative work (CSCW) 8, 1 (1999), 9–30.Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. Lucy Suchman. 2002. Located accountabilities in technology production. Scandinavian journal of information systems 14, 2 (2002), 7.Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Alex S Taylor, Siân Lindley, Tim Regan, David Sweeney, Vasillis Vlachokyriakos, Lillie Grainger, and Jessica Lingel. 2015. Data-in-place: Thinking through the relations between data and community. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. 2863–2872.Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. Linnet Taylor. 2017. What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society 4, 2 (2017), 2053951717736335.Google ScholarGoogle ScholarCross RefCross Ref
  62. Linnet Taylor, Gargi Sharma, Aaron Martin, and Shazade Jameson. 2020. Data justice and covid-19. London, Meatspace Press.Google ScholarGoogle Scholar
  63. Nick Taylor, Keith Cheverst, Peter Wright, and Patrick Olivier. 2013. Leaving the wild: lessons from community technology handovers. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1549–1558.Google ScholarGoogle ScholarDigital LibraryDigital Library
  64. Annuska Zolyomi, Anne Spencer Ross, Arpita Bhattacharya, Lauren Milne, and Sean A Munson. 2018. Values, identity, and social translucence: Neurodiverse student teams in higher education. In Proceedings of the 2018 chi conference on human factors in computing systems. 1–13.Google ScholarGoogle ScholarDigital LibraryDigital Library

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    PDC '22: Proceedings of the Participatory Design Conference 2022 - Volume 1
    August 2022
    240 pages

    Copyright © 2022 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 19 August 2022

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate49of289submissions,17%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format