Publishing my papers as Linked Research

I intend to make the extra effort of republishing my own research papers as Linked Research, i.e. in a form readable by humans (HTML5), but also embedding meta-data (as RDF) for machine processing.

I’ve started with Authoritative Linked Data descriptions of Debian source packages using ADMS.SW (a good candidate, as it deals with Linked Data ;).

You’ll notice the menu which helps select different style sheets for preparing clean printable versions, not far from the LaTeX output usually converted to PDF.

I hope this will pave the way to more Linked Research, and less opaque publications.

The only hassle at the moment is the conversion from LaTeX to HTML5 which I’m doing manually, in Emacs + nxml-mode.

Update: Check the preprint links in my publications page, for more papers.

New paper on observation of contributions in forges through standard feeds

Just a quick word to mention the paper published at SITIS 2009 by our collegue Vu.

Biblio entry : DANG Quang Vu, BAC Christian, BERGER Olivier, VLASCEANU Valentin, Supporting situation awareness in FLOSS projects by semantical aggregation of tools feeds. The 5th International Conference on Signal Image Technology and Internet Based Systems (SITIS’09), 29 november – 04 december 2009, Marrakech, Morocco, 2009

At all good libraries soon 😉

Here’s the abstract :

It is rather difficult to monitor or visualize what can be the contribution of a member in a collaboration project, especially when the project uses multiple tools to produce its results. This is the case for collaborative development of FLOSS software, that uses Wiki, bug tracker, mailing lists and source code management tools. This paper presents an approach to data collection by using aggregation of feeds published by the different tools of a software forge. To allow this aggregation, collected data is semantically reformatted into Semantic Web standards: RDF, DC, DOAP, FOAF and EvoOnt. Resulting data can then be processed, re-published or displayed to project members. We implemented this approach in a supervision module that has been integrated into the PicoForge platform. This module is able to draw a live graph of the social community out of the different sources of data, and in turn exports semantic feeds for other uses.