Rifaccio.
C ---------- Forwarded message ---------- From: ENWP Pine deyntestiss@hotmail.com Date: 2012/12/30 Subject: [Wikimedia-l] "Big data" benefits and limitations (relevance: WMF editor engagement, fundraising, and HR practices) To: "wikimedia-l@lists.wikimedia.org" wikimedia-l@lists.wikimedia.org, "wiki-research-l@lists.wikimedia.org" wiki-research-l@lists.wikimedia.org, "wikitech-l@lists.wikimedia.org" wikitech-l@lists.wikimedia.org
I'm sending this to Wikimedia-l, Wikitech-l, and Research-l in case other people in the Wikimedia movement or staff are interested in "big data" as it relates to Wikimedia. I hope that those who are interested in discussions about WMF editor engagement efforts, WMF fundraising, or WMF HR practices will also find that this email interests them. Feel free to skip straight to the links in the latter portion of this email if you're already familiar with "big data" and its analysis and if you just want to see what other people are writing about the subject.
* Introductory comments / my personal opinion
"Big data" refers to large quantities of information that are so large that they are difficult to analyze and may not be related internally in an obvious way. See https://en.wikipedia.org/wiki/Big_data
I think that most of us would agree that moving much of an organization's information into "the Cloud", and/or directing people to analyze massive quantities of information, will not automatically result in better, or even good, decisions based on that information. Also, I think that most of us would agree that bigger and/or more accessible quantities of data does not necessarily imply that the data are more accurate or more relevant for a particular purpose. Another concern is the possibility of unwelcome intrusions into sensitive information, including the possibility of data breaches; imagine the possible consequences if a hacker broke into supposedly secure databases held by Facebook or the Securities and Exchange Commission.
We have an enormous quantity of data on Wikimedia projects, and many ways that we can examine those data. As this Dilbert strip points out, context is important, and looking at statistics devoid of their larger contexts can be problematic. http://dilbert.com/strips/comic/1993-02-07/
Since data analysis is also something that Wikipedia does in the areas I mentioned previously, I'm passing along a few links for those who may be interested about the benefits and limitations of big data.
* Links:
From the Harvard Business Review
http://hbr.org/2012/04/good-data-wont-guarantee-good-decisions/ar/1
From the New York Times
https://www.nytimes.com/2012/12/30/technology/big-data-is-great-but-dont-for... and https://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-wor...
From the Wall Street Journal. This may be especially interesting to
those who are participating in the discussions on Wikimedia-l regarding how Wikimedia selects, pays, and manages its staff. http://online.wsj.com/article/SB10000872396390443890304578006252019616768.ht...
And from English Wikipedia (: https://en.wikipedia.org/wiki/Big_data and https://en.wikipedia.org/wiki/Data_mining and https://en.wikipedia.org/wiki/Business_intelligence
Cheers,
Pine
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