Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
<goog_433392935> https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Awesome reading, I liked it a lot. Thanks!
On Wed, Jan 27, 2016 at 9:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Hi Asaf --
Thanks for sharing this. It's a good article and there's a lot to agree with. Certainly there's a clear need for both qualitative and quantitive research and figuring out how to combine them is a worthwhile challenge. A lot of modern productive development practices stress empathy, meeting users where they are along with big data and we're certainly aspiring to this level of work in the Reading team.
Where I think the Foundation and the Movement struggle is on the evaluation side and I don't think the article addresses this issue particularly well. Measuring the impact of non-profit work has always been challenging and will continue to be so. It's certainly true that the emphasis on big data has been less helpful here.
Finally, since I can't resist, Nokia failed because they didn't do ethnographic research on their existing users in Europe and North America, not potential users across the planet and missed the fact that people would be thrilled to trade in their candy-bar phones for fancy iphones and androids!
-Toby
On Wed, Jan 27, 2016 at 5:34 AM, Marcel Ruiz Forns mforns@wikimedia.org wrote:
Awesome reading, I liked it a lot. Thanks!
On Wed, Jan 27, 2016 at 9:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- *Marcel Ruiz Forns* Analytics Developer Wikimedia Foundation
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Thanks for sharing this, Asaf and Raul. The design research team is (obviously) onboard with this approach.
Related: here's a post on doing ethnographic work in a Wikipedia context, written for Medium by veteran Wikiresearcher Heather Ford: https://medium.com/ethnography-matters/what-does-it-mean-to-be-a-participant...
Jonathan "I dearly miss my Nokia 925" Morgan
On Wed, Jan 27, 2016 at 6:04 AM, Toby Negrin tnegrin@wikimedia.org wrote:
Hi Asaf --
Thanks for sharing this. It's a good article and there's a lot to agree with. Certainly there's a clear need for both qualitative and quantitive research and figuring out how to combine them is a worthwhile challenge. A lot of modern productive development practices stress empathy, meeting users where they are along with big data and we're certainly aspiring to this level of work in the Reading team.
Where I think the Foundation and the Movement struggle is on the evaluation side and I don't think the article addresses this issue particularly well. Measuring the impact of non-profit work has always been challenging and will continue to be so. It's certainly true that the emphasis on big data has been less helpful here.
Finally, since I can't resist, Nokia failed because they didn't do ethnographic research on their existing users in Europe and North America, not potential users across the planet and missed the fact that people would be thrilled to trade in their candy-bar phones for fancy iphones and androids!
-Toby
On Wed, Jan 27, 2016 at 5:34 AM, Marcel Ruiz Forns mforns@wikimedia.org wrote:
Awesome reading, I liked it a lot. Thanks!
On Wed, Jan 27, 2016 at 9:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- *Marcel Ruiz Forns* Analytics Developer Wikimedia Foundation
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
I should add that the research-and-data team is also on board with this approach. Honestly, I think it's a little silly that we make the distinction between methodological expertise when we split the team up.
But "thick data", come on. We can get a better term than that? How about "meaningful measurements"? Or we could just call it "competent application of methods".
-Aaron
On Wed, Jan 27, 2016 at 11:43 AM, Jonathan Morgan jmorgan@wikimedia.org wrote:
Thanks for sharing this, Asaf and Raul. The design research team is (obviously) onboard with this approach.
Related: here's a post on doing ethnographic work in a Wikipedia context, written for Medium by veteran Wikiresearcher Heather Ford: https://medium.com/ethnography-matters/what-does-it-mean-to-be-a-participant...
Jonathan "I dearly miss my Nokia 925" Morgan
On Wed, Jan 27, 2016 at 6:04 AM, Toby Negrin tnegrin@wikimedia.org wrote:
Hi Asaf --
Thanks for sharing this. It's a good article and there's a lot to agree with. Certainly there's a clear need for both qualitative and quantitive research and figuring out how to combine them is a worthwhile challenge. A lot of modern productive development practices stress empathy, meeting users where they are along with big data and we're certainly aspiring to this level of work in the Reading team.
Where I think the Foundation and the Movement struggle is on the evaluation side and I don't think the article addresses this issue particularly well. Measuring the impact of non-profit work has always been challenging and will continue to be so. It's certainly true that the emphasis on big data has been less helpful here.
Finally, since I can't resist, Nokia failed because they didn't do ethnographic research on their existing users in Europe and North America, not potential users across the planet and missed the fact that people would be thrilled to trade in their candy-bar phones for fancy iphones and androids!
-Toby
On Wed, Jan 27, 2016 at 5:34 AM, Marcel Ruiz Forns mforns@wikimedia.org wrote:
Awesome reading, I liked it a lot. Thanks!
On Wed, Jan 27, 2016 at 9:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- *Marcel Ruiz Forns* Analytics Developer Wikimedia Foundation
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- Jonathan T. Morgan Senior Design Researcher Wikimedia Foundation User:Jmorgan (WMF) https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
On Wed, Jan 27, 2016 at 9:54 AM, Aaron Halfaker ahalfaker@wikimedia.org wrote:
I should add that the research-and-data team is also on board with this approach. Honestly, I think it's a little silly that we make the distinction between methodological expertise when we split the team up.
+1. I should have said "the research team", since we're really one big data-loving family.
But "thick data", come on. We can get a better term than that? How about "meaningful measurements"? Or we could just call it "competent application of methods".
Or just... "science" ;) I suspect "thick data" is an unfortunate consequence of an industry jargon arms race: researchers get listened to (not to mention hired) in our field if they characterize what they do as "big data", because that term is hot right now--even though it's really no more accurate or useful, as a term, than "Web 2.0" was when that was A Big Thing.
So some qual researchers feel having a catchy term of their own will make folks more likely to listen to them. I feel fortunate that at our organization, at least, I never feel like I need to use buzzwords in order to get PMs to take me seriously. \o/
J
-Aaron
On Wed, Jan 27, 2016 at 11:43 AM, Jonathan Morgan jmorgan@wikimedia.org wrote:
Thanks for sharing this, Asaf and Raul. The design research team is (obviously) onboard with this approach.
Related: here's a post on doing ethnographic work in a Wikipedia context, written for Medium by veteran Wikiresearcher Heather Ford: https://medium.com/ethnography-matters/what-does-it-mean-to-be-a-participant...
Jonathan "I dearly miss my Nokia 925" Morgan
On Wed, Jan 27, 2016 at 6:04 AM, Toby Negrin tnegrin@wikimedia.org wrote:
Hi Asaf --
Thanks for sharing this. It's a good article and there's a lot to agree with. Certainly there's a clear need for both qualitative and quantitive research and figuring out how to combine them is a worthwhile challenge. A lot of modern productive development practices stress empathy, meeting users where they are along with big data and we're certainly aspiring to this level of work in the Reading team.
Where I think the Foundation and the Movement struggle is on the evaluation side and I don't think the article addresses this issue particularly well. Measuring the impact of non-profit work has always been challenging and will continue to be so. It's certainly true that the emphasis on big data has been less helpful here.
Finally, since I can't resist, Nokia failed because they didn't do ethnographic research on their existing users in Europe and North America, not potential users across the planet and missed the fact that people would be thrilled to trade in their candy-bar phones for fancy iphones and androids!
-Toby
On Wed, Jan 27, 2016 at 5:34 AM, Marcel Ruiz Forns <mforns@wikimedia.org
wrote:
Awesome reading, I liked it a lot. Thanks!
On Wed, Jan 27, 2016 at 9:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- *Marcel Ruiz Forns* Analytics Developer Wikimedia Foundation
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- Jonathan T. Morgan Senior Design Researcher Wikimedia Foundation User:Jmorgan (WMF) https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Hi Asaf and Raul,
The shorter version: My background tells me that ethnographers bring a new perspective and depth to many quantitative research endeavours. I am fully on board that for some projects you cannot rely on quantitative analysis alone.
The longer version: As a researcher in the Foundation, I can share with you some of my thoughts on the subject of what is called "thick data" in the article.
* In the context of the article, thick data refers to ethnographic studies, not necessarily other qualitative approaches for understanding deeper. It's important to distinguish the two since although the Research team does qualitative and quantitative research, none of that research that I'm aware of at the moment involves ethnographic research.
* Most of the people in the Research team that I have talked to value ethnographic research.
* Combining ethnographic and big data approaches is not a solved problem, many acknowledge that it's an important one, but it's not solved. Quite a few top tier academic institutions have acknowledged and are working on it. The so called Social Computing programs are the children of this acknowledgement. :-) I got my PhD in a department called management science and engineering. The department was created by combining three programs: Operations Research (think applied math and more recently big data work), Organizational Behavior (ethnographic studies and more), System Economics (or Economics of Systems I believe). I experienced first-hand the challenges and opportunities of increasing research interactions among these traditionally separate programs/departments. We are making progress on this front, we are not there yet, neither in academia nor in research institutions and industry.
* As Aaron and Jonathan have mentioned, the Research team values qualitative and quantitative research. The most recent example of it may be the research https://meta.wikimedia.org/wiki/Research:Characterizing_Wikipedia_Reader_Behaviour we have started to understand Wikipedia readers in fall 2015. That research has not involved ethnographic research, however, it definitely has involved and will continue to involve a mix of qualitative and quantitative approaches.
I hope this helps.
And thanks again for starting this conversation. :-)
Best, Leila
Leila Zia Research Scientist Wikimedia Foundation
On Wed, Jan 27, 2016 at 12:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Leila,
I consider much of the research I do to be ethnographic* in nature. But like you, Leila, my background is in one of these new-fangled hybrid disciplines**, and quote-un-quote real social scientists might bristle when I claim that term.
Abbey, Daisy, and Sherah are going to embark on a trip to Mexico next week for a Bona Fide *field study*. Don't get more ethnographic than that ;)
Also, at least one of Wang's examples of "thick data" research looks an awful lot like a standard user study: *"One employee, Jenna Lyons was given the opportunity to implement iterative, experimental, and real-time testing of products with consumers. Her approach resonated with consumers, transforming Jcrew into a cult brand and tripling its revenues." *So the author of this article seems to be adopting a big tent definition of ethnography, that includes a lot of different qualitative research methods. Apparently you don't need to be stranded for months on the Trobriand Islands https://en.wikipedia.org/wiki/Bronis%C5%82aw_Malinowski#Career in order to be considered an ethnographer. Whew!
Anyway, I'm sure I'm boring most of the people on this list by now, so I'll stop. If anyone's curious about how to do ethnographic research in an industry setting, I recommend *Practical Ethnography http://www.practicalethnography.com/*. If anyone wants to read a really, really interesting book by one of America's best ethnographers, I recommend *You Owe Yourself a Drunk: An Ethnography of Urban Nomads https://www.waveland.com/browse.php?t=74. *
- J
*disclosure: I'm not really interested in disputing/defining the boundaries of ethnography. I'll gladly leave that up to people who haven't (yet) escaped from academia **I got my degree in a department called "Human Centered Design & Engineering"... I'll leave it to the reader to decide whether that is an actual academic discipline, or simply word salad.
On Wed, Jan 27, 2016 at 11:37 AM, Leila Zia leila@wikimedia.org wrote:
Hi Asaf and Raul,
The shorter version: My background tells me that ethnographers bring a new perspective and depth to many quantitative research endeavours. I am fully on board that for some projects you cannot rely on quantitative analysis alone.
The longer version: As a researcher in the Foundation, I can share with you some of my thoughts on the subject of what is called "thick data" in the article.
- In the context of the article, thick data refers to ethnographic
studies, not necessarily other qualitative approaches for understanding deeper. It's important to distinguish the two since although the Research team does qualitative and quantitative research, none of that research that I'm aware of at the moment involves ethnographic research.
- Most of the people in the Research team that I have talked to value
ethnographic research.
- Combining ethnographic and big data approaches is not a solved problem,
many acknowledge that it's an important one, but it's not solved. Quite a few top tier academic institutions have acknowledged and are working on it. The so called Social Computing programs are the children of this acknowledgement. :-) I got my PhD in a department called management science and engineering. The department was created by combining three programs: Operations Research (think applied math and more recently big data work), Organizational Behavior (ethnographic studies and more), System Economics (or Economics of Systems I believe). I experienced first-hand the challenges and opportunities of increasing research interactions among these traditionally separate programs/departments. We are making progress on this front, we are not there yet, neither in academia nor in research institutions and industry.
- As Aaron and Jonathan have mentioned, the Research team values
qualitative and quantitative research. The most recent example of it may be the research https://meta.wikimedia.org/wiki/Research:Characterizing_Wikipedia_Reader_Behaviour we have started to understand Wikipedia readers in fall 2015. That research has not involved ethnographic research, however, it definitely has involved and will continue to involve a mix of qualitative and quantitative approaches.
I hope this helps.
And thanks again for starting this conversation. :-)
Best, Leila
Leila Zia Research Scientist Wikimedia Foundation
On Wed, Jan 27, 2016 at 12:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
While a fan of Jenna Lyons, thick data seems to have its limits http://www.nytimes.com/2015/06/11/business/j-crew-flounders-in-fashions-shifting-tides.html. *(I haven't read the article in question.)
On Wed, Jan 27, 2016 at 12:41 PM, Jonathan Morgan jmorgan@wikimedia.org wrote:
Leila,
I consider much of the research I do to be ethnographic* in nature. But like you, Leila, my background is in one of these new-fangled hybrid disciplines**, and quote-un-quote real social scientists might bristle when I claim that term.
Abbey, Daisy, and Sherah are going to embark on a trip to Mexico next week for a Bona Fide *field study*. Don't get more ethnographic than that ;)
Also, at least one of Wang's examples of "thick data" research looks an awful lot like a standard user study: *"One employee, Jenna Lyons was given the opportunity to implement iterative, experimental, and real-time testing of products with consumers. Her approach resonated with consumers, transforming Jcrew into a cult brand and tripling its revenues." *So the author of this article seems to be adopting a big tent definition of ethnography, that includes a lot of different qualitative research methods. Apparently you don't need to be stranded for months on the Trobriand Islands https://en.wikipedia.org/wiki/Bronis%C5%82aw_Malinowski#Career in order to be considered an ethnographer. Whew!
Anyway, I'm sure I'm boring most of the people on this list by now, so I'll stop. If anyone's curious about how to do ethnographic research in an industry setting, I recommend *Practical Ethnography http://www.practicalethnography.com/*. If anyone wants to read a really, really interesting book by one of America's best ethnographers, I recommend *You Owe Yourself a Drunk: An Ethnography of Urban Nomads https://www.waveland.com/browse.php?t=74. *
- J
*disclosure: I'm not really interested in disputing/defining the boundaries of ethnography. I'll gladly leave that up to people who haven't (yet) escaped from academia **I got my degree in a department called "Human Centered Design & Engineering"... I'll leave it to the reader to decide whether that is an actual academic discipline, or simply word salad.
On Wed, Jan 27, 2016 at 11:37 AM, Leila Zia leila@wikimedia.org wrote:
Hi Asaf and Raul,
The shorter version: My background tells me that ethnographers bring a new perspective and depth to many quantitative research endeavours. I am fully on board that for some projects you cannot rely on quantitative analysis alone.
The longer version: As a researcher in the Foundation, I can share with you some of my thoughts on the subject of what is called "thick data" in the article.
- In the context of the article, thick data refers to ethnographic
studies, not necessarily other qualitative approaches for understanding deeper. It's important to distinguish the two since although the Research team does qualitative and quantitative research, none of that research that I'm aware of at the moment involves ethnographic research.
- Most of the people in the Research team that I have talked to value
ethnographic research.
- Combining ethnographic and big data approaches is not a solved problem,
many acknowledge that it's an important one, but it's not solved. Quite a few top tier academic institutions have acknowledged and are working on it. The so called Social Computing programs are the children of this acknowledgement. :-) I got my PhD in a department called management science and engineering. The department was created by combining three programs: Operations Research (think applied math and more recently big data work), Organizational Behavior (ethnographic studies and more), System Economics (or Economics of Systems I believe). I experienced first-hand the challenges and opportunities of increasing research interactions among these traditionally separate programs/departments. We are making progress on this front, we are not there yet, neither in academia nor in research institutions and industry.
- As Aaron and Jonathan have mentioned, the Research team values
qualitative and quantitative research. The most recent example of it may be the research https://meta.wikimedia.org/wiki/Research:Characterizing_Wikipedia_Reader_Behaviour we have started to understand Wikipedia readers in fall 2015. That research has not involved ethnographic research, however, it definitely has involved and will continue to involve a mix of qualitative and quantitative approaches.
I hope this helps.
And thanks again for starting this conversation. :-)
Best, Leila
Leila Zia Research Scientist Wikimedia Foundation
On Wed, Jan 27, 2016 at 12:34 AM, Asaf Bartov abartov@wikimedia.org wrote:
Estonian Wikipedian Raul Veede, User:Oop, asked to relay this link to "the metrics people", so I am sending it here and to the Community Engagement team at the Wikimedia Foundation.
https://medium.com/ethnography-matters/why-big-data-needs-thick-data-b4b3e75...
Cheers,
A.
Asaf Bartov Wikimedia Foundation <http://www.wikimediafoundation.org>Imagine a world in which every single human being can freely share in the sum of all knowledge. Help us make it a reality! https://donate.wikimedia.org
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
-- Jonathan T. Morgan Senior Design Researcher Wikimedia Foundation User:Jmorgan (WMF) https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics