[Wikimedia-l] Let's map capacities! (Announcing the CCM)

[Asaf Bartov]

Dear Wikimedians,

*How many Wikimedia communities have embraced advanced Wikidata use? How
many have active social media accounts, and are there geographic or
cultural patterns to which groups have and have not? Which groups have a
written, current strategy? What are the most common gaps in capacity in
Latin America? or in Eastern Europe? What kind of investment in capacity
building would be likely to bring the most value?*

To answer these questions and more, we invite all of you to participate in
the new *Community Capacity Map (CCM)*: a *self-assessment exercise* for
communities, groups (whether formally recognized user groups or not),
thematic organizations, and chapters, to *map capacities* across the
movement, with a view to identifying *existing gaps* as well as *opportunities
for capacity-building*.

The CCM is here on Meta:
https://meta.wikimedia.org/wiki/Community_Capacity_Map

The context for this work, as well as "likely-asked questions, with
answers" ("LAQ"?), are explained here, including an answer to "*why should
I take the time to read all this?*" --
https://meta.wikimedia.org/wiki/Community_Capacity_Map/About
(and also pasted at the bottom of this e-mail, for your convenience.)

The self-assessment is to be done based on the detailed *Guidelines* provided
here:
https://meta.wikimedia.org/wiki/Community_Capacity_Map/Guidelines

I am looking forward to learning more about your groups' and orgs'
capacities and gaps, and to do my best to play matchmaker between those
needs and our available resources and opportunities.  While I encourage you
to begin contributing straightaway, *there is no deadline *-- this is
envisioned to be a long-term, ongoing, and tracked-over-time tool -- so
contribute if and when your group is able to make the time.

(don't forget to scroll down to the LAQ!)

Warmly,

Asaf Bartov
Senior Program Officer, Emerging Wikimedia Communities

==
Likely-asked questions, with answers
this exists with working links and [modest] formatting here:
https://meta.wikimedia.org/wiki/Community_Capacity_Map/About#Likely-asked_questions,_with_answers

Why do this at all?  The Community Resources team is doing this to attempt
a more *comprehensive* view of capacities and gaps across the movement, to
enhance our existing, anecdotal and ad-hoc, impressions of only some of the
communities and affiliates. See the goal statement above. Why now?  The CCM
experiment is an implementation of one of the recommendations made at the
conclusion of the Community Capacity Development pilot year

. Why should I spend the time to read through it or go through the
self-assessment?  There are a couple of reasons you may want to put in the
time: First, by self-assessing your group/organization's capacities and
gaps, you are giving WMF and other potential investors in community
capacity a chance to provide your group/org with resources and
opportunities to *build up* those capacities. Secondly, self-assessing
according to the Guidelines page
 may be
in itself a worthwhile exercise and discussion-starter for your group/org,
pointing at potential areas for proactive work by *your org/group itself*,
for example in your next annual plan. Finally, self-assessing (at least
some) capacities today would enable you to review and re-assess in six
months, or two years, and see how your group/org has developed (or not) in
each of these aspects. So does WMF expect all groups and organizations to
do this?  No. This is an opportunity and a tool. Like all other tools, you
are free to use it or not, and we certainly understand that it would take
time and that you may have more pressing priorities in your group/org. We
*hope* as many groups, organizations, and communities eventually take the
time to self-assess, at least on some capacities, but it is not mandatory,
and there would be no penalty for not participating. Would we have to
provide self-assessments for *all* of the capacities?  No. Feel free to
self-assess on as many or as few capacities as you are able to, interested
in, or find relevant. You can also add assessments gradually, as your
group/org finds time to discuss and agree on assessments. Should I assess
capacities in the context of my wiki community, my user-group/chapter, or
what?  It depends. It may make sense to do separate assessments, or just
one. For example, while the English community has plenty of bot builders
and technical experts, you may belong to a small community contributing in
English in a country with little or no bot-building expertise, such as
Wikimedians in Uganda. In this case, it would make sense to describe the
capacities of the Ugandan group you're part of, and not of the whole
English Wikipedia community. On the other hand, it is possible that t

Re: [Wikimedia-l] What's making you happy this week? (Week of 14 January 2018)

[geni]

On 14 January 2018 at 19:05, Pine W  wrote:
> What's making you happy this week?


We appear to have buried the hatchet with Jason Scott

https://livestream.com/internetsociety/wikidaynyc/videos/168540333

-- 
geni

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Re: [Wikimedia-l] Siamese networks and image classification

[John Erling Blad]

This is the same as the entry on the wishlist for 2016, but describes the
actual method.
https://meta.wikimedia.org/wiki/2016_Community_Wishlist_Survey/Categories/Commons#Use_computer_vision_to_propose_categories

Both contrastive and triplet loss can be used while learning, but neither
are described at Wikipedia.

On Sun, Jan 14, 2018 at 8:16 PM, Pine W  wrote:

> Hi John,
>
> I have not heard of an initiative to use Siamese neural networks for image
> classifications on on Commons. You might make a suggestion on the AI,
> Research, and/or Commons mailing lists regarding this idea. You might also
> make a suggestion in IdeaLab
> .
>
> Pine 
> 
>
> On Sun, Jan 14, 2018 at 3:46 AM, John Erling Blad 
> wrote:
>
> > Has anyone tried to use a Siamese neural network for image classification
> > at Commons? I don't know if it will be good enough to run in autonomous
> > mode, but it will probably be a huge help for those that do manual
> > classification.
> >
> > Imagine a network providing a list of possible categories, and the user
> > just ticks off usable categories.
> >
> > A Siamese network can be learned by using a triplet loss function, where
> > the anchor and the positive candidate comes from the same category, and
> the
> > negative candidate comes from an other category but are otherwise close
> to
> > the anchor.
> >
> > Output from the network is like a fingerprint, and those fingerprints can
> > be compared to other images with known fingerprints, or against a
> > generalized fingerprint for a category.
> >
> > John Erling Blad
> > ___
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