Open Access Reader

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Introduction[edit]

Open Access Reader Logo v1.png

Open Access Reader (OAR) is a project to systematically ensure that all significant open access research is cited in Wikipedia.

There's lots of great research being published in good quality open access journals that isn't cited in Wikipedia. It's peer reviewed, so it should count as a reliable source. It's available for anyone to read and probably comes with pretty decent metadata too. Can we set up a process to make it easy to find and cite these papers?

We propose the creation of a desktop and mobile crowdsourcing tool that guides users through setting up a Wikipedia account, finding and summarising a significant, uncited open access article in their area of interest, and inserting this summary into an existing Wikipedia article with a correctly formatted citation link.

If you like this idea, please endorse it!

Exploration Period, August - October 2014[edit]

An initial grant from The Wikimedia Foundation IEG programme produced:

  • Strong recommendations for CORE as the source for OA metadata.
  • A small but promising proof of concept (source), generated from a static metadata dump from CORE.
  • Discovery of research outlining a method of matching OA articles from CORE to Wikipedia categories.
  • A set of wireframes for a desktop UI, with mockups coming soon.
  • A proposal from the CORE team to produce and support:
    • the backend required to supply open access metadata in the form we require for OAR.
    • a considered and justified ranking methodology.
  • Discovery of Citoid, a tool to automatically generate correct citation links.
  • A press list for a campaign to develop a crowdsourcing community.

See also: Project Diary

Project Overview[edit]

We break down this endeavour into four parts:

I: Sourcing Papers[edit]

There exist projects to provide API access to the aggregation of all open access repositories, such as CORE. It makes sense to use one of these instead of re-inventing the wheel, but which should we use?

II: Prioritising Significance[edit]

There are millions of papers published every year. What's the best way to decide which papers editors should tackle first?

III: Identifying, Recruiting and Alerting Contributors[edit]

It's likely that OA papers come with metadata. How can we use this to find contributors that are likely to take an interest?

IV: Streamlining Contributor Workflow[edit]

How can we make this convenient for contributors to use?

Project Management[edit]

Roadmap[edit]

Milestones to MVP:

  1. Identify best Open Access Aggregator - Done! (CORE)
  2. Identify and assess available open metrics to create specification for significance filter.
  3. Produce a system that generates an up-to-date list of most significant papers.
  4. Assess quality of topic metadata to create specification for paper-to-keyword filter.
  5. Build and demonstrate paper-to-keyword filter.
  6. Configure automated report of most significant papers for a particular keyword
  7. Create feedback process
  8. Introduce the report to sample communities via Wikiprojects, lists.

The Team[edit]

Perhaps you'd like to volunteer?

Success Metrics[edit]

  • Build MVP
  • New citations generated
  • New contributors

Possible Extensions[edit]

This general principle (take large open repository, remove things already cited, rank by significance) could be extended to other areas, e.g.

Endorsements[edit]

If you think this is a cool idea, please put your name below!