Hello Leigh,
thanks for the pointers, I apologize for missing relevant ones. And I
agree we should say how exactly we got the data, good point.
Pascal.
On 5/18/2013 4:58 AM, Leigh Dodds wrote:
Hi Pascal,
Its good to draw attention to these issues. At ISWC 2009 Tom Heath,
Kaitlin Thaney, Jordan Hatcher and myself ran a workshop a legal and
social issues for data sharing [1, 2]. Key themes from the workshop
were around the importance of clear licensing, norms for attribution,
and including machine-readable license data.
At the time I did a survey of the current state of licensing of the
Linked Data cloud, there's a write-up [3] and diagram [4].
Looking over your analysis, I don't think the picture has changed
considerably since then. We need to work harder to ensure that data is
clearly licensed. But this is a general problem for Open Data, not
just Linked Open Data.
You don't say in your paper how you did the analysis. Did you use the
metadata from the LOD group in datahub? [5]. At the time I had to do
mine manually, but it wouldn't be hard to automate some of this now,
perhaps to create an regularly updated set of indicators.
One criteria that agents might apply when conducting "Follow Your
Nose" consumption of Linked Data is the licensing of the target data,
e.g. ignore links to datasets that are not licensed for your
particular usage.
Cheers,
L.
[1]. http://opendatacommons.org/events/iswc-2009-legal-social-sharing-data-web/
[2]. http://blog.okfn.org/2009/11/05/slides-from-open-data-session-at-iswc-2009/
[3]. http://blog.ldodds.com/2010/01/01/rights-statements-on-the-web-of-data/
[4]. http://www.flickr.com/photos/ldodds/4043803502/
[5]. http://datahub.io/group/lodcloud
On Sat, May 18, 2013 at 3:15 AM, Pascal Hitzler
<[email protected]> wrote:
We just finished a piece indicating serious legal issues regarding the
commercialization of Linked Data - this may be of general interest, hence
the post. We hope to stimulate discussions on this issue (hence the
provokative title).
Available from
http://knoesis.wright.edu/faculty/pascal/pub/nomoneylod.pdf
Abstract.
Linked Data (LD) has been an active research area for more than 6 years and
many aspects about publishing, retrieving, linking, and cleaning Linked Data
have been investigated. There seems to be a broad and general agreement that
in principle LD datasets can be very useful for solving a wide variety of
problems ranging from practical industrial analytics to highly specific
research problems. Having these notions in mind, we started exploring the
use of notable LD datasets such as DBpedia, Freebase, Geonames and others
for a commercial application. However, it turns out that using these
datasets in realistic settings is not always easy. Surprisingly, in many
cases the underlying issues are not technical but legal barriers erected by
the LD data publishers. In this paper we argue that these barriers are often
not justified, detrimental to both data publishers and users, and are often
built without much consideration of their consequences.
Authors:
Prateek Jain, Pascal Hitzler, Krzysztof Janowicz, Chitra Venkatramani
--
Prof. Dr. Pascal Hitzler
Kno.e.sis Center, Wright State University, Dayton, OH
[email protected] http://www.knoesis.org/pascal/
Semantic Web Textbook: http://www.semantic-web-book.org
Semantic Web Journal: http://www.semantic-web-journal.net
--
Prof. Dr. Pascal Hitzler
Kno.e.sis Center, Wright State University, Dayton, OH
[email protected] http://www.knoesis.org/pascal/
Semantic Web Textbook: http://www.semantic-web-book.org
Semantic Web Journal: http://www.semantic-web-journal.net
