Katy McKinney-Bock,  | December 12, 2023

A full version of this report is available:

A Better Deal for Data is focusing on empowering people to participate in shared governance of their data, and is about making organizational commitments to data subjects, to data communities, and for the public good. Part of this is having an understanding about key challenges in the current data climate that are impacting people’s trust in data, and connecting this to the emergence of participatory data governance models. This research brief is an abstract of a full report on data governance, part 1 (link).

In the November research report for a Better Deal for Data, we ask: What is data governance? What is the problem space that emerging models of data governance seek to address? The report includes a discussion of some key issues from The Age of Surveillance Capitalism (Zuboff 2019) and of the theory of relational data governance (Viljoen 2020, 2021), as well as data governance challenges which have recently arisen with LLMs and generative AI (Aaronson 2023). All three of these resources point to the need for better governance of data.

I also include three responses to current data practices in the agricultural sector: Australia’s Farm Data Code, Solutions from the Land’s Data Policy Guidance on Farm Data, and OpenTEAM’s Agricultural Data Use Documents.

• • Farm Data Code: A code of conduct that was created in Australia by the National Farmers’ Federation, intended for service/product providers “who manage data on behalf of farmers.” Its goal is to improve data governance in the industry overall.
  • Data Policy Guidance on Farm Data:  Solutions from the Land, a nonprofit, published a document to guide data policy for farm data, which provides guidance from the perspective of producers and related to attaining the UN Sustainable Development Goals (SDGs).
  • Agricultural Data Use Documents: OpenTEAM, led by Wolfe’s Neck Center for Agriculture & the Environment, has published a series of documents about data management and governance, with a goal to “build towards an equitable, open source, and interoperable technology ecosystem,” including the Agriculturalists’ Bill of Data Rights.

Finally, I provide a working definition of data governance, and we explore resources that define the context around recent implementation of data governance models. A meta-analysis in Marcucci et al. (2023) of 58 governance documents finds three themes in common across governance policies: trust, protecting citizen and user rights, and use of data for public interest. An EU report on governance models puts context around the implementation of “good” data governance:

“Current trends in data governance involve the development of different tools such as data trusts, various forms of cooperatives and commons, and stewardship processes. We find that none of these are relevant as stand-alone approaches to data governance, but become relevant in relation to particular goals. As such, all are open to misuse if overarching normative goals are not clearly articulated and enforced.” (Lopez Solano et al., 2022, p. iv).

I briefly address practical adoption of governance models, pointing to research by (Verhulst, 2023) on redefining roles and responsibilities of data stewards, and ODI’s 9 practices to progress towards an  “open, trustworthy data ecosystem.”

In December, I will present a description of a set of governance models, including data trusts, data collaboratives, and data collectives. For each model, I will provide a description of the model, provide a case study to illustrate the model in action, and address any broader research on this model.

Feedback is always welcome on any and all of these reports¹, and please watch for a webpage announcing the Better Deal for Data.

This work is licensed under CC BY 4.0. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

This work is supported by a subaward from OpenTEAM as an initiative of Wolfe’s Neck Center for Agriculture and the Environment, specifically funded by the U.S. Department of Agriculture under agreement number NR233A750004G032. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author and do not necessarily reflect the views of any funder. In addition, any reference to specific brands or types of products or services does not constitute or imply an endorsement.

¹Please send feedback via email to [email protected].

References

Aaronson, S. A. (2023). Data Dysphoria: The Governance Challenge Posed by Large Learning Models (SSRN Scholarly Paper 4554580). https://doi.org/10.2139/ssrn.4554580

Ada Lovelace Institute. (2020). Rethinking data and rebalancing digital power. https://www.adalovelaceinstitute.org/wp-content/uploads/2022/11/Ada-Lovelace-Institute-Rethinking-data-and-rebalancing-digital-power-FINAL.pdf

GovLab. (n.d.). Data Collaboratives. Retrieved December 8, 2023, from https://datacollaboratives.org/

Lopez Solano, J., de Souza, S., Martin, A., & Taylor, Linnet. (2022). Governing data and artificial intelligence for all: Models for sustainable and just data governance. European Parliament. https://doi.org/10.2861/915401

Marcucci, S., Alarcón, N. G., Verhulst, S. G., & Wüllhorst, E. (2023). Informing the Global Data Future: Benchmarking Data Governance Frameworks. Data & Policy, 5, e30. https://doi.org/10.1017/dap.2023.24

National Farmers Federation. (2023). Farm Data Code. https://nff.org.au/programs/australian-farm-data-code/

Open Data Institute. (2023). Guide to data practices. Open Data Insistute. Can be found at: theodi.org/tools

Open Data Policy Lab & GovLab. (n.d.). Data Stewards Academy. Retrieved December 8, 2023, from https://course.opendatapolicylab.org/

OpenTEAM. (2023). Agriculturalists’ Bill of Data Rights, v1.0. https://openteam-agreements.community/billofrights/

Solutions from the Land, : LW Morton, F Yoder, E Shea, J Anderson, K Bridgeforth, B Doyle, R Gaesser, AG Kawamura, A Kent, M Kimble, B LaCross, A Moller, H Shapiro, V Ulibarri., & M Kimble, B LaCross, A Moller,. (2023). Solutions from the Land Data Policy Guidance on Farm Data: Strengthening Collection, Analysis and Use of Agriculture and Food System Data for Sustainable Development Attainment (SDGs). Solutions from the Land. https://www.solutionsfromtheland.org/wp-content/uploads/2023/10/2023.10.10-SfL-Data_Policy_Guide_2023-Final1.pdf

Soni, S. (2021, September 28). Building the Stewardship Navigator: Our Approach and Methodology. The Data Economy Lab. https://thedataeconomylab.com/2021/09/28/building-the-stewardship-navigator-our-approach-methodology/

Verhulst, S. G. (2023, March 13). Wanted: Data Stewards — Drafting the Job Specs for A Re-imagined Data Stewardship Role. Data Stewards Network. https://medium.com/data-stewards-network/wanted-data-stewards-drafting-the-job-specs-for-a-re-imagined-data-stewardship-role-f7cd28a83379

Viljoen, S. (2020). A Relational Theory of Data Governance. The Yale Law Journal, 131(2). https://www.yalelawjournal.org/feature/a-relational-theory-of-data-governance

Viljoen, S. (2021, March 22). Data Governance for a Society of Equals. LPE Project. https://lpeproject.org/blog/data-governance-for-a-society-of-equals/

Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs. https://www.hachettebookgroup.com/titles/shoshana-zuboff/the-age-of-surveillance-capitalism/9781610395694/