Organizing the history of online governance
Ethnographic data has arrived on Govbase. In this post we share a new dataset that supports rich comparisons between events, experiments, and other lived experiences in the history of online governance: the Cases table.
By Campbell McNolty, Joshua Tan, and Ellie Rennie
The Cases table catalogs significant events in the history of online governance, from the DAO hack in 2016 to the original “rape in cyberspace” in 1993. It exists as an open dataset within Govbase, a crowd-sourced database for online governance.
We designed Cases for ethnographers and researchers who study online communities. Here are some of the things you can do with it:
- Filter the case studies in the database by the number of people involved in the event. Then read the case studies to search for qualitative differences in the way that small and large online communities govern themselves.
- Search for case studies related to a particular protocol or community, to learn more about the history of a community that you are interested in joining.
- Use qualitative data to make comparisons between community organising in the real world and community run campaigns that are governed online.
- Run the qualitative data through natural language processing software, to draw new insights into the commonalities and differences between governance events.
- Add your own data on governance events so that other researchers can use it to make new findings.
The Cases table was built to support ethnographic research into online communities, especially those in blockchain and decentralized finance (or DeFi). The first collection of records in the table were adapted from a dataset created by Professor Ellie Rennie and Campbell McNolty at RMIT University’s Blockchain Innovation Hub.
The data
Cases gathers qualitative and quantitative data on a wide range of events that have implications for community governance, including online votes, community disputes, hard forks, hacks, and piracy. It is currently organized into three distinct “source” data sets: the RMIT data set, the Metagov data set, and the Participedia data set.
The RMIT data set covers a range of incidents through the short history of DeFi. You can see more in the ‘DeFi Fails’ view.
The Metagov data set focuses on historical events in online governance, with a focus on failures that triggered some transition in governance. For example, the infamous “rape in cyberspace” was a harassment case in the virtual world LambdaMOO which triggered a range of responses from the community, from the initial banning of the offender to the adoption of a number of new moderation procedures.
The Participedia data set is sourced from Participedia, a crowd-sourced repository containing detailed qualitative information on a broad array of (mostly offline) participatory political processes. Indeed, Cases is designed to interoperate directly with Participedia, and you can see a big chunk of Participedia’s data set (and data model) copied over in the ‘Comparing online and offline cases’ view (though the integration is still a work-in-progress). If you are interested in comparing online and offline community governance using qualitative methods, take a look and let us know what you think!
In the rest of this section, we’ll introduce the main data columns of the Cases table. We also encourage you to mouse over the column descriptions directly in the table.
Starting from the “Title” and “Source” columns at the very left of the table, you’ll notice some tags for “incident type” have been added to make categorising and searching easier. Each record is also linked to other records from the Organizations table and the Projects table, taking full advantage of the data we already have in Govbase. Scrolling further to the right, you will find columns containing the size of the community, start dates and end dates for events (though not all cases have defined end dates), information about the people involved, categorisations of the types of community action, voting methods, and much more detail.
But perhaps the most important columns for a case are the ‘ArticleBody’ and ‘ArticleBodySummary’ columns. For example, if we select the article related to The DAO Hack record, here’s what we see:
The article opens in a text box so you can read what our contributors have written about the event. The articles are all formatted with the same headings (you’ll see in the example above that some of the headings are unused in any given article). These headings match up with the headings used in the Participedia database to make comparisons between their data and ours as easy as possible.
Let’s take a look at a few mores of the data points that are available in the Cases table. You can use some of these variables to filter or sort the cases that you are interested in examining.
We can see above that there is data on the types of community organising used, voting methods, links to further reading, and much more. Many of these are also formatted to operate cleanly with the Participedia database.
Future development
Qualitative data is time-consuming to generate but we are continually adding new data and seeking new contributors. Please reach out if you have your own case studies you would like to add, or if you want to help us develop new ones. In the future, we hope to make the Cases table even easier to read and access by presenting it in a wiki format.
We look forward to continuing our governance research collaborations within the Metagovernance Project, as well as making these cases freely available for other researchers. In the meantime, if you have questions, feedback, or would like to get in touch, please post a comment below or join our Telegram!
Govbase is a crowd-sourced database of tools and projects in online governance. To learn more, read the introductory article or start exploring the database.
Acknowledgements
We would like to thank Michael Zargham, Kelsie Nabben, and the team at Participedia for their feedback and support in developing the Cases table and this post.
Endnotes
[1] The initial data collection for the Cases table was undertaken as part of an Australian Research Council-funded Future Fellowship (FT190100372).
