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Wikimedia Deutschland/Knowledge Equity in Linked Open Data Research

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If you are interested in participating in this project, please fill out this survey!

Strategic background

At the highest level, Wikimedia defined its 2030 movement strategy as the following:

“By 2030, Wikimedia will become the essential infrastructure of the ecosystem of free knowledge, and anyone who shares our vision will be able to join us.”

Two goals guide this strategic direction:

  • Knowledge as a Service – Become a platform that serves knowledge in many formats and builds tools for allies.
  • Knowledge Equity – Focus on the knowledge and communities that structures of power and privilege have left out.

These are reflected in Wikimedia Deutschland’s 2030 strategy as well:

  • “Wikimedia Deutschland commits to embracing the diversity of humanity striving towards comprehensive knowledge equity, and creating an inclusive culture in everything we do”.
  • Additionally, we made this more concrete by choosing ‘greater diversity and equitable participation’ as one of the strategic priorities for the next seven years. And in the strategic priority ‘more usage, easier access’, we are also committing to “to pave the way toward easier and more equitable access to [the] content [of Wikimedia projects]”.

Linked Open Data (LOD) also has a vision that is led by knowledge equity as a guiding principle: within its suite of products:

  • “Wikidata and the Wikibase Ecosystem intend to level the open data playing field. Linked Data should be a common good and available to everyone who needs it. Everyone should find themselves represented in the Linked Open Data web. We will continually increase our understanding and act to ensure that our communities and our data represent the world in an equitable way.”

In this project we seek to learn from the experience of people contributing their own historically and structurally marginalized knowledge using Wikidata, Wikibase Suite and Wikibase Cloud.

  • How do Wikidata, Wikibase Suite, and Wikibase Cloud enable the contribution of structurally marginalized or non dominant knowledge and perspectives?
  • How do WMDE LOD products contribute to difficulties or barriers people face when contributing their ways of knowing?
  • What can be changed, or improved, from a product perspective, to mitigate or address inequities and marginalization

Findings will inform product strategy and decision making as a result of:

  • a better understanding of barriers, who experiences it, in what ways, and to what extent, in their particular cultural and technical contexts.
  • identifying and sharing actionable recommendations for work that WMDE product teams can conduct to address and reduce barriers and further knowledge equity, supporting teams in their journey to understanding and furthering knowledge equity.

Project details

This research builds off of an emergent, internal (to WMDE) understanding that knowledge equity is a continuous and active practice. In a 2023 workshop, knowledge equity was defined as “the practice of critically engaging power distributions in the production, ownership, valuation, and access to knowledge.” In this vision of knowledge equity, communities and data (that are part of the LOD ecosystem) represent the world in an equitable way.

Historically marginalized knowledge can be defined as the knowledge of communities that have historically been marginalized or even erased. Marginalized knowledge, for example, can be of: Indigenous nations, people whose ancestors experienced slavery, folks who were impacted by JimCrow and racism, women in general, LGBTQ+ peoples.

Timeline

  • Active December 2023 - May 2024
  • Interviews conducted between Feb. 15 - Mar. 29, 2024
    • Ideally 12-15 participants
  • Looking to learn from folks whose knowledge is underrepresented and has been historically marginalized, focusing on people who identify differently from this demographic and these geographic locations will help.
  • The findings of the research will be shared on the usual Wikidata/Wikibase communication spaces and updated on this page as well.

How we are defining this work, the goals, expected outputs and how we will go about the work

Below are the key questions we seek to answer with this research (also in the KELOD research framework).

Theme 1

What are people’s experiences when attempting to contribute marginalized knowledge using Wikidata, Wikibase Suite and Wikibase Cloud? What knowledge are they sharing or contributing?

  1. What are the activities people are doing to share or contribute knowledge?
  2. What are their goals?
  3. What are their motivations?
  4. What contexts are they working in and what tools are they using?
  5. What kind of challenges or barriers do they face?
  6. Are they compensated for this work? How do they feel about the exchange?
  7. What works well in their context for sharing knowledge?

Theme 2

What role do Wikidata, Wikibase Suite, and Wikibase Cloud play in the current state of knowledge equity and people’s ability to contribute marginalized knowledge?

  1. In their experience, how does the design of the software impact their ability to contribute?
    1. What kind of challenges do they face when using the software?
    2. What works well for them when using the software?
    3. In what ways does the software as a whole support, or not support, their ability to contribute?
    4. Are they able to contribute in the way they would like to?
  2. What, if any, suggestions or recommendations do they have for the WMDE product teams for reducing barriers to contributing knowledge when using Wikidata, Wikibase Suite and/or Wikibase Cloud?
    1. From a systems perspective?
    2. From a product perspective?
    3. From a collaboration -people perspective - (for example, do they find people to work with, learn from and find technical support from?)
    4. Other perspectives?

Your participation

We would like to talk with people for an hour or an hour and a half, or the time they have available, about your experience contributing knowledge using Wikidata, Wikibase Suite, and Wikibase Cloud. These interviews will be:

  • fairly compensated
  • recorded and documented (only with permission of participants)
  • take place between February 9 and March 29, 2024
  • recorded using Google Meet, then uploaded and stored in Great Question (the GDPR compliant software we are using for surveys, scheduling, video review, transcription and sharing compensation)
  • deleted at any time upon the participant’s request.
  • summarized for findings (participants will remain anonymous unless otherwise requested)

If you are interested in participating in this project, please fill out this survey!

Update 16th of October 2024

The research has been successfully conducted. Full report can be found here.

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