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WG: Survey on reusing vocabularies when modeling LOD

From: Schaible, Johann <Johann.Schaible@gesis.org>
Date: Thu, 5 Dec 2013 15:20:42 +0000
To: "semantic-web@w3.org" <semantic-web@w3.org>, "public-lod@w3.org" <public-lod@w3.org>
Message-ID: <E67DDC0829E98A4B84BCE984F1717EB85280DD4D@svboexc02.gesis.intra>
Hi all,

As I have written in my previous email below, I am conducting a survey on vocabulary reuse strategies in order to determine requirements for a tool that supports a Linked Data engineer by recommending him/her appropriate classes and properties from actively used vocabularies.

So far, I have had many promising responses, and I would like to thank all who have participated. However, it would be great, if we collected even more responses. If you haven't already participated, please participate in this survey and help me with my Ph.D. thesis. I would appreciate your effort very much.

The survey takes only 10 minutes and is available here: https://www.unipark.de/uc/GESIS-WTS/f0c5/

Thanks again for your effort :-)


Von: Schaible, Johann [mailto:Johann.Schaible@gesis.org]
Gesendet: Freitag, 15. November 2013 15:01
An: public-lod@w3.org
Betreff: Survey on reusing vocabularies

Hi all,

I am investigating the typical strategies for reusing vocabularies when modeling Linked Open Data. Given that many of you have expertise in the field of publishing and consuming LOD, I would like to ask you, if you could help me with my research by filling out an online survey (approximately 10 minutes).

Link to the survey: https://www.unipark.de/uc/GESIS-WTS/f0c5/

I am a research associate at the GESIS Leibniz-Institute for the Social Sciences in Cologne, Germany, and my Ph.D. thesis is about a recommender system that supports a Linked Data engineer in reusing vocabularies by recommending appropriate classes and properties from actively used vocabularies in the LOD cloud. The survey is a major part of identifying relevant requirements for such a support system.

Notice, we do not collect any sensitive personal data.  All survey participants will be treated anonymously, and the results will be published after thorough analysis.

Thank you and best regards,

Johann Wanja Schaible
Research Associate
GESIS - Leibniz-Institute for the Social Sciences
Department: Knowledge Technologies for the Social Sciences
Phone: +49-221-47694-517
e-mail: johann.schaible@gesis.org<mailto:johann.schaible@gesis.org>
Received on Thursday, 5 December 2013 15:21:21 UTC

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