**Participants**, please read/think about/research these, ahead of time:
* Session description:
** The role of research, analytics, and machine learning in the future of Wikimedia.
*** Research: the systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions.
*** Analytics: the systematic computational analysis of data or statistics.
*** Machine learning: the construction of computer algorithms through implicit learning from data.
* Session Outline:
** ==Part 1==
*** Welcomes, outline, goals [15 mins]
**** Introductions
**** Set the Goal: The output of this session will feed into phase 2 of the 2030 Strategic Direction
**** Here is how we plan to do it:
***** Introduce our teams, the work and mandate of each team, capabilities we teams have, capabilities we're planning, and the things "we" see missing
***** Brainstorm what "you" think we should be doing
***** Break out and talk about risks, needs, opportunities, and what to avoid, stop, or re-resource
*** How do Research, Analytics, and Machine Learning relate to knowledge equity and knowledge as a service? What are some examples of features, services, processes, commitments, products, etc that further the strategic direction? Which are planned? Interactive: what other capabilities should be considered? [45 mins]
**** Aaron: Machine Learning
**** Dan: Analytics
**** Leila: Research
*** Introduce the breakout questions, ask people to go to breakout mode. [5-mins]
** ==Part 2==
*** Breakout sessions: [30 mins]
**** What major risks do you see to our ability to provide these capabilities from the technical side, and how can they be mitigated? For existing capabilities, this includes risks to sustaining and scaling it.
**** What technological needs do you see (beyond addressing the risks) for providing the respective capabilities?
**** Which technological opportunities do you see for providing the respective capabilities? Which methods or technologies should we explore?
**** What should we avoid doing with respect to the relevant capabilities?
**** What should we stop doing with respect to the relevant capabilities?
**** What amount of resources should be committed to providing each of the capabilities? Consider horizons of 1 year, 3 years, and 5 years.
*** Reconvene and discuss, each breakout group presenting the result of their discussion as a response to the above questions [15 mins]
*** Wrap up [5 mins]
* Pre-event questions for discussion
** What do you hope to get from this session?
** What do you hope the session does not cover?
* Related position statements:
** https://wikifarm.wmflabs.org/devsummit/index.php/Session:6
* Related background reading:
** https://www.youtube.com/watch?v=LYF-3t14CSc -- 1 hour talk by @halfak about newcomer dynamics in Wikipedia and the large potential for innovation around Machine Learning
** @leila presenting about the Knowledge Gap (video link will be added soon)
** https://wikitech.wikimedia.org/wiki/User:Ottomata/Stream_Data_Platform Event-driven service design will simplify and improve infrastructure in general, not just Analytics
**Session notes**:
* https://etherpad.wikimedia.org/p/devsummit18-researchanalyticsmachinelearning
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==Discussions before and after the summit, whether or not you're attending==
* IRC: Dan is milimetric, Leila is leila, Aaron is halfak, we are all in #wikimedia-research
* Google Hangout: we started a group chat with all the folks that had their statements categorized in Session 6. If you want to be invited to the Hangout, please ping any of these people
* Alternatives: we are very open to something else, but keep in mind that a lot of us are travelling so whatever it is should have an app or some easy way to check from a phone, such as email
This is one of the 8 [[https://www.mediawiki.org/wiki/Wikimedia_Developer_Summit/2018 |Wikimedia Developer Summit 2018]] topics.
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Post-event Summary:
* ...
Action items:
* ...
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# Participation from non-attendees
//to do//https://phabricator.wikimedia.org/T183320