Strategy/Wikimedia movement/2018-20/Recommendations/Sprint/Partnerships/3

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Recommendation 3: Shared ecosystem of services and tools for content partnerships[edit]

Q 1 What is your Recommendation?[edit]

We recommend that Wikimedia stewards an ecosystem of technological solutions such as software, tools and other services that support partnership work, in particular on large-scale content partnerships.

The approach should be based on the following principles: compatible technological ecosystems, sharing of resources, proper governance and abiding to best ethical practices on technology. It would ensure that key tools are developed to be usable and effective, properly address internal needs as well as needs of partners, and are properly and sustainably managed.

Wikimedia should also have the capacity, while developing this ecosystem, to explore how emergent technologies, such as machine learning and automation, can augment partnerships.

Q 2-1 What assumptions are you making about the future context that led you to make this Recommendation?[edit]

Development and management of key tools that are used in large-scale content partnerships cannot only depend on individual effort and engagement. In the past, reliance on individual contributions has led to tools that are not fully usable or not properly managed and updated. A structural approach to managing these tools is required in order to address the needs of partners and for tools to be usable, effective and sustainable.

Management of these tools should be distributed, with precise rules developed based on the general vision for governance, decentralisation and distribution of roles, developed in this strategy. A leading organisation should play the role of center for excellence and main steward of this ecosystem (see recommendations #2 and #3).

This organisation should take the responsibility for building a community of tool creators, based on the principles of free software development. It should also build partnerships with other movement entities able to contribute to the development and management of this ecosystem.

This ecosystem should function as an ecosystem of services and tools developed based on a single vision, a clear product development strategy and an approach that sustainably ensures availability of all the tools that are necessary from the perspective of large-scale content partnerships.

The ecosystem of services and tools should present the cutting edge of technological solutions. These include such technologies as machine learning, GIS, Language Computing, etc. This will constitute an additional incentive for content partners - so that by working with Wikimedia they may undergo a digital transformation of their own approaches to managing content. We are assuming that in the future visibility of content may decrease as the primary reason for working with Wikimedia and other incentives may also become more important.

The ecosystem should be based on agreed, common technical standards and a review process for their social and ethical impact.

Q 2-2 What is your thinking and logic behind this recommendation?[edit]

By ensuring proper ownership, management and development of these tools, we will provide better opportunities for individual, volunteer developers to support the development of these tools. Their work would also be better managed and coordinated. New model would also lesser dependence on individual maintenance of tools by their creators - by enabling shared responsibility for them.

Development of this ecosystem should be based on a thorough understanding of needs of partners, so that the tools and services are user-centric. In particular, they need to work well and be relevant in a broad range of local contexts - taking into account the varied needs and levels of competence of partners.

Development and use of this ecosystem will at the same time support mutual learning with partners, develop the essential knowledge ecosystem for the public good, and possibly provide advances around the use of technological developments (such as AI and machine learning) to derive full value from partnerships.

Potential and existing partners (for example GLAM institutions) are studying, observing, learning and are also adopting to modern technological developments such as machine learning, artificial intelligence (AI), etc in their routine business. Based on current trends, we can predict that use of machine learning and automation tools will be a major trend for managing, curating and sharing content (See report on “Augmentation”, Wikimedia 2030 Product Planning). In order to address the needs of partners, our technological solutions should be based on these cutting edge approaches. The institution responsible for managing this ecosystem also needs to play the role of the center of excellence for using emergent technologies in Wikimedia partnerships. These technologies require constant desk support, hence, for Wikimedia Movement with it volunteers to remain advanced, it is important for them to be aligned with the centre of excellence in technology space.

Q 3-1 What will change because of the Recommendation?[edit]

Today, lack of ownership of key tools is a major issue that affects their availability and usability. Wikimedia Volunteers and Staff working with the GLAM institutions would have a relatively better time advocating, negotiating and most importantly be enabled to more effectively use available tools.

Machine-trained automated task may increase productivity and complement volunteer’s effort on say working with large archival database where language processing tools and Artificial Intelligence (AI) help with text categorisation, content analysis etc. The end-result can then help in deriving larger value from partnerships, improve Wikimedia eco-systems and also provides insights to partner institutions. We would develop a strategy to provide AI ecosystem (Wikidata and Wikibase) for knowledge domains such as libraries, scientific research, culture, etc. Improvements and further developments to the open-knowledge mission would require support and assistance of the efficient modern technologies. An example would be application of Wikimedia’s Objective Revision Evaluation Service (ORES) to work in the domain of Artificial Intelligence (AI) to say identify gaps on Wikimedia Projects and where so ever the partners can support in bridging or improving them.

Q 3-2 Who specifically will be influenced by this recommendation?[edit]

All our partners, All our volunteers.

Q 5 How does this Recommendation relate to the current structural reality?[edit]

There is no structure in place today that ensures sustainable management of tools that are high quality, usable, locally relevant and based on latest technological solutions.

Emergent technologies have remained distant and exclusive somewhere and its inclusion can promote a helping and supplementary hand in nurturing, developing and growing the present day partnership efforts.