Increasing the Financial Transparency of European Commission Project Funding

Tracking #: 435-1593

Michael Martin
Claus Stadler
Philipp Frischmuth
Jens Lehmann

Responsible editor: 
Pascal Hitzler

Submission type: 
Dataset Description
The Financial Transparency System (FTS) of the European Commission contains information about grants for Euro- pean Union projects starting from 2007. It allows users to get an overview on EU funding, including information on beneficiaries as well as the amount and type of expenditure and information on the responsible EU department. The original dataset is freely available on the European Commission website, where users can query the data using an HTML form and download it in CSV and most recently XML format. In this article, we describe the transformation of this data to RDF and its interlinking with other datasets. We show that this allows interesting queries over the data, which were very difficult without this conversion. The main benefit of the dataset is an increased financial transparency of EU project funding. The RDF version of the FTS dataset will become part of the EU Open Data Portal and eventually be hosted and maintained by the European Union itself.
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Solicited Reviews:
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Review #1
By Aidan Hogan submitted on 15/Feb/2013
Review Comment:

The authors have done a good job of addressing my previous comments. There's still one or two typos present (e.g., search for " ," and "Jens"), and I would prefer to see commas used to separate thousands in Table 1, but very minor quibbles aside, I'm happy to accept.

Review #2
By Jérôme Euzenat submitted on 18/Feb/2013
Review Comment:

I think that the paper can be accepted now (this is in fact the decision I had in mind from last row). It has been improved in the explainations it provides.

I can argue once more for my request to change in the related work: this is supposed to be a data set paper, not a paper about extracting datasets (and we did not judged it this way). Hence the related work should not be about techniques for extracting datasets (which if they are innovative should be described elsewhere) but rather related data sets. For instance, if someone has published data about NSF grants or DFG grants and how it is different.

There are a few small typos:
- p2: flat rate_, there is an extra space before the comma
- p4: "Exemplary" not sure that this is the appropriate word
- p5: in case of -> in the case of
- p5: specifications which matches (there is one "s" too many)
- p5: cleansing of the data -> cleansing the data
- p7: "Jens" may not have to be here?