Re: SWJ special issue on The Personal and Social Semantic Web, Deadline: July 29

I have read through this call for submissions on The Personal and Social
Semantic Web a couple of times.
I find it very interesting and also very surprising.

a major challenge is to allow various applications to exchange,
> reuse, and integrate user data from different sources.


various applications. Such as those that ask for permission in Facebook,
etc. But these work with existing APIs. Presumably what is available through
these APIs is a subset of what is available to Facebook etc. because of this
following?


> Such data comes in different flavors: user data such as user profiles,
> social networking/tagging/blogging data, etc.


We can see this I think.


> as well as usage data like clickthrough data or query logs.


But I don't think we can see this at all?

The amount of people's data
> available on the Web is tremendously growing so that sharing and mining
> ...  is a non-trivial problem ...
>

Yes.

means to facilitate integration of user and usage data
>

Is usage data available - what is meant by usage data here?

connecting user and usage data traces ...
>

Usage data traces? How is this going to be captured?

Linking distributed traces of user data provides new possibilities for
> inferring and modelling user preferences and personalizing Web systems to
> individual needs.
>

'to individual needs' perhaps. But isn't this the same data that Facebook et
al. capture and then package to resell to advertisers?
Two points.
1. If this is much the same data, even if derived by other means, it would
seem that the Social Semantic Web would be undercutting the business model
of Facebook et al? I would think it will be very difficult to access or
create otherwise the data on which their business models depend.
2. This data is indeed potentially very sensitive, and for this reason I
believe the public have an interest in it. Further, making it available to
users may be the only way of turning the corner away from a system that
effectively monitors everyone for the benefit of some third party or
parties. This is a subtle issue.
I was in a conversation recently with someone who was describing the
situation as it used to be in East Germany where the Stassi had convinced
say 70% of the population to spy on each other. So people would go around
with note books, stand at school gates or other innocent meeting places
jotting things down. Dangerous for the 30% who refused and a good method of
ensuring compliance.
With the advent of the web there are more effective methods of monitoring
people, by looking at trends in conversations, growth of conversations and
other things I haven't thought of, I expect. Not quite the same (and we do
not know what or if this is done) but not so very different either.
I do think that information that is made more firmly into the ownership of
the user/creator is better than an anonymous silo that may be mined for all
sorts of purposes by unknown entities.
A semantic approach may not prevent that sort of data mining, it may not be
desirable to prevent it, it may even facilitate it. But it also may give
greater ownership to the user creator of that data whereby they can
anticipate, if not control, how their data is mined?

Just some thoughts on these issues.

Best,

Adam

On 18 July 2011 07:41, Fabian Abel <abel@l3s.de> wrote:

> Call for Papers
>
> Semantic Web Journal (SWJ)
> Special Issue on
>
>         The Personal and Social Semantic Web
>
> Website: http://wis.ewi.tudelft.nl/swj2011/
> SWJ: http://www.semantic-web-journal.net/
> Twitter: http://twitter.com/persweb
>
> Submission deadline: July 29, 2011
>
> About
> ========
> Social Web sites, such as Facebook, YouTube, Delicious, Flickr and
> Wikipedia, and numerous other Web applications, such as Google and
> Amazon, rely on implicitly or explicitly collected data about their
> users and their activities to provide personalized content and services.
> As these applications become more and more connected on the Semantic
> Web, a major challenge is to allow various applications to exchange,
> reuse, and integrate user data from different sources. Such
> data comes in different flavors: user data such as user profiles,
> social networking/tagging/blogging data, etc. as well as usage data
> like clickthrough data or query logs. The amount of people's data
> available on the Web is tremendously growing so that sharing and mining
> these heterogeneous data corpora distributed on the Web is a
> non-trivial problem that poses several challenges to the Semantic Web
> community.
>
> Semantic interoperability between Social Web applications is becoming
> increasingly important as users leave a plethora of traces at diverse
> services on the Web. Semantic Web and Social Web technologies and
> paradigms provide means to facilitate integration of user and usage
> data, for example, with the principles of Linked Data and Microformats,
> vocabulary standards such as FOAF and SIOC, standardized APIs such as
> OpenSocial, or support for schema matching as provided by the Silk
> framework. Further, mechanisms like WebID, OpenId, OAuth and FOAF+SSL
> allow for identification and authorization on the Social Web. Hence,
> the time is right to exploit and improve such technologies for
> connecting user and usage data traces on the Social Semantic Web.
>
> Linking distributed traces of user data provides new possibilities for
> inferring and modeling user preferences and personalizing Web systems to
> individual needs. Novel models, techniques, frameworks and systems have to
> be developed to leverage Social Web semantics. While linkage of user and
> usage data promises advantages for recommendation and personalization, it
> also raises questions related to provenance, trust and privacy: how does
> one know that the data gathered from several sources can be trusted, and
> how can one avoid that sensitive personal data is disclosed to certain
> services or used to infer and expose sensitive information? Trust and
> privacy, and associated policies, may therefore impact mining and
> reasoning on the people's data.
>
>
> Topics
> =========
> This special issue presents latest research developments on user data in
> the Social Semantic Web from both angles: (1) techniques and applications
> for linking, reusing and mining user and usage data and exploiting such
> data to personalize Social Web experiences, as well as (2) trust and
> privacy techniques and their impact on society. In particular, we seek for
> contributions addressing the following topics.
>
> + People's Data on the Personal and Social Semantic Web:
>    - Analyses of user data and usage logs distributed on the Web
>    - Capturing the semantics of user interactions
>    - Inferring semantics from user data and usage logs
>    - Linkage, aggregation and integration of distributed user/usage data
>    - Linked Open Data in the Personal and Social Web
>    - Representing and enriching user and usage data
>    - Authorization and access control mechanisms for user/usage data
>    - Methods, techniques and formats for trust-enabled sharing user and
>      usage data (with provenance awareness)
>    - Data collections and services for Personal and Social Semantic Web
>
> + Applications that leverage People's Data on the Personal and Social
>   Semantic Web:
>    - Personalization and adaptation of Social Semantic Web applications
>    - Recommender systems and personalized search on the Social Semantic Web
>    - Personalization and adaptation approaches that benefit from analysis
>      of social data
>    - Mining user data streams and mining heterogeneous data sources
>    - Intelligent and adaptive user interfaces for user/usage data
>    - Interoperability of applications, data sources and services
>    - Semantic techniques for trust and privacy in social networks
>    - Supporting awareness for user/usage data distributed on the Web
>    - Scalability and robustness of Social Semantic Web systems
>
>
> Submissions
> ==============
> High-quality papers containing original research results on the above and
> related topics are solicited. Extended versions of papers previously
> published in conferences and workshops are also welcome, given that they
> are substantially expanded and improved. Authors should submit a manuscript
> (in IOS Press format) through the Semantic Web Journal on-line system,
> following the guidelines available at:
> http://www.semantic-web-journal.net/authors.
> Please mention the title of this special issue in the submission. All
> submissions will undergo an open review process, according to the
> standards of the Semantic Web Journal:
> http://www.semantic-web-journal.net/reviewers#review
>
>
> Important Dates
> =================
> Submission deadline:    29 July 2011
> Notifications:          September 2011
> Camera-ready version:   October 2011
> Publication:            November 2011
>
>
> Guest Editors
> ================
> Fabian Abel
> Delft University of Technology, The Netherlands
> http://www.st.ewi.tudelft.nl/~abel/
> f.abel@tudelft.nl
>
> Laura Hollink
> Delft University of Technology, The Netherlands
> http://www.st.ewi.tudelft.nl/~hollink/
> l.hollink@tudelft.nl
>
> Geert-Jan Houben
> Delft University of Technology, The Netherlands
> http://www.st.ewi.tudelft.nl/~houben/
> g.j.p.m.houben@tudelft.nl
>
>
> Guest Editorial Board
> ==========================================
> - Lora Aroyo (Vrije Universiteit, Amsterdam, the Netherlands)
> - Bettina Berendt (K.U. Leuven, Belgium)
> - Dan Brickley (Vrije Universiteit, Amsterdam, the Netherlands)
> - Francesca Carmagnola (University of Torino, Italy)
> - Federica Cena (University of Torino, Italy)
> - Vania Dimitrova (University of Leeds, UK)
> - Olaf Hartig (Humboldt-Universiaet zu Berlin, Germany)
> - Eelco Herder (L3S Research Center, Germany)
> - Andreas Hotho (University of Wuerzburg, Germany)
> - Vera Hollink (CWI Amsterdam, Netherlands)
> - Daniel Krause (Leibniz University Hannover, Germany)
> - Knud Moeller (DERI/NUIG, Ireland)
> - Claudia Mueller-Birn (FU Berlin, Germany)
> - Andreas Nauerz (IBM Research, Germany)
> - Alexandre Passant (DERI, Ireland)
> - Matthew Rowe (The Open University, UK)
> - Ansgar Scherp (University of Koblenz-Landau, Germany)
> - Sergej Sizov (University of Koblenz-Landau, Germany)
> - David Vallet (Universidad Autonoma de Madrid, Spain)
>
>
>