Finding a Path to Sustainability for the Dataverse Community - A 2024 report by the Dataverse sustainability working group.
Creators
Contributors
Description
The Dataverse Project is an open-source software project that has cultivated a growing and lively community of collaborators, contributors and implementers. In 2023, the Dataverse community formally recognized the need to address the challenges the Dataverse community has been facing due to its continuous popularity and growth. From this, the Dataverse Sustainability Working Group was established and decided an in-depth analysis of the current state of affairs was necessary to identify and find a path to sustainability for the Dataverse community. The mission of the working group, as endorsed by the Global Dataverse Community Consortium (GDCC), was to provide evidence-based, community-reviewed, and consensus-based recommendations on how to sustain and grow the Dataverse community. The group started its work in August 2023 and ran until October 2024, ending with the publication of this report.
The working group divided its work across two work packages. One to analyze the current state of affairs of Dataverse’s sustainability and the second to gauge the possibilities to generate monetary support for Dataverse sustainability by providing more added values in exchange for e.g. membership fees.
Work package one was completed by performing a phase analysis and organizing several workshops as described in the It Takes a Village (ITAV) framework. During the phase analysis, the categories of governance, technology, resources and engagement were examined, resulting in maturity levels of 1, 2.5, 1, 2 out of three, respectively. What consistently stood out during these analysis sections, was the current invaluable investment by the Dataverse Project Team at IQSS at Harvard University in Dataverse, which resulted in the working points being mainly in the area of formalizing and documentation of processes and policies.
After this analysis, workshops were organized to identify critical catastrophes and to afterwards explore the necessary steps to prevent these from happening. The phase analysis in combination with the workshops results in the definition of the 10 recommendations for the Dataverse community to improve its sustainability, which can be found in the report.
For work package two (added values), a survey was carried out early 2024, where the things found to be most valuable by the respondents were: the support for software installation/migration and upgrading, the integration of long-term preservation in Dataverse, members’ ability to prioritize getting a bug fix or feature request into a release, and sustaining the Dataverse software and associated services and tools. The latter shows the overall attribution of value from the community members to sustainability for Dataverse. These results can help provide options to establish recurrent income for the Dataverse community, though further feasibility studies are necessary per item before implementation or offering of these options can be considered.
In conclusion, there is a need for formalization that is currently lacking, for which this working group has proposed 10 recommendations. In order to move forward with these recommendations, dedicated human resources that can focus on drafting an action plan will be necessary. The working group urges individual Dataverse installations to explore how they can invest in the provision of these dedicated human resources and in the sustainability work that is necessary. Especially since the continued sustaining of the Dataverse software and associated services and tools was voted as being one of the most valuable value exchanges available for the respondents of the survey performed in work package two. And as the community grows, formalization of the mechanisms and incentives to contribute to sustainability will be critical to address the above-mentioned 10 recommendations.
Files
Finding a Path to Sustainability for the Dataverse Community 2024.pdf
Files
(625.1 kB)
Name | Size | Download all |
---|---|---|
md5:6268571c63bdfad77cb4f6cb9c505278
|
625.1 kB | Preview Download |