What's in Data.gov?

Guest Author
Jul. 20 2009, 12:32AM EDT


A recent article by Tim Berners-Lee, “Putting Government Data online“, has  attracted significant interest to the  datasets published at the US data.gov website.  As Berners-Lee discusses the Semantic Web techniques that can be used to get those data into RDF space (something we are now working on), we would like to share our initial investigation of the contents of these government datasets.

I. Translate dataset into RDF

The catalog of the datasets in data.gov,http://www.data.gov/details/92,  is published in CSV format as part of data.gov. We  converted it into RDF using simple CSV parsing. We kept the translation minimal: (i) the properties are directly created from thecolumn names; (ii) each table row is mapped to an instance of pmlp:Dataset; (iii) all non-header cells are mapped to a literal - we don’t create new URIs at this point. The output of our work is published on Tetherless World website at:


(We are now starting to do more  integration work, extracting multiple objects from single tables, linking into the linked open data  cloud, etc.  and will publish new version when that is done - the purpose of this first work was simply to make the catalog more available to the RDF community)

II. Browse and query the RDF graph

As an example, we can browse the dataset in tabulator, and then use a SPARQL webservice to query the dataset. For example, we use a sparql queryto list datasets published in CSV format:


III. Observations on the RDF graph

Using this service we can answer some basic questions about the data.gov datatsets:

1. How many datasets are published, and how many among them can be easily converted into RDF?

There are 332 datasets which can be partitioned by  type:  raw data catalog(301);  tool catalog (31).

Not all of the datasets have a link to downloadable data because some offer only browseable data via their own websites,  Others  publish datasets in multiple formats. As of today, the online static files associated with the datasets are distributed as  follows:  204 datasets offer a CSV format dump, 10 datasets offer an XML format dump, and 21 datasets offer an XLS format dump.

2. How are the datasets categorized?


3. What are some of the key items in the dataset?

4. What are the  sources of the datasets?

The majority of the datasets are published by the EPA, and they contain environmental data partitioned by the states of the US in three individual years.  Others come from other govt agencies - the distribution is as follows:

IV. Getting Datasets linked

Although the datasets are not explicily linked, we see a number of opportunities for connecting these datasets to others (and into the Linked Open Data datasets):

  • A large percentage of files have some sort of geo-tagging, thus they can be linked to DBpedia or Geo-names (and then presented via Map services).
  • Some datasets are subsets of other datasets, e.g. EPA data “2005 Toxics Release Inventory data for the state of Georgia” is a subset of  “2005 Toxics Release Inventory National data file of all US States and Territories” making for easier “internal” linking of the datasets.
  • A number of the datasets contain temporal information, e.g. IRS’s “Tax Year 1992 Private Foundations Study”,…”Tax Year 2005 Private Foundations Study” which provides an opportunity for mashups using timelines and such.

V. Conclusions

We are committed to getting more of the data.gov data online soon (in RDF), and then investigating data integration and knowledge discovery. In order to get our datasets linked to the linked data cloud, we will use SPARQL for extracting entities and our Semantic Mediawiki as a platform to capture the owl:sameAs mappings.  Scalable dataset publishing is also challenging as some of these are very large datasets, e.g. “2005-2007 American Community Survey Three-Year PUMS Population File” has a 1.1 g zipped csv file.  Moreover, some datasets are not directly available in one file but via a web service.  Our current plan is to produce RDF documents available for download soon, and to work on bringing more of these datasets into live, SPARQLable forms as we can.

Guest Author



I've been fasctinated by the RDFization of so much data.

I've been hesitant to do too much with RDF just yet on my site, as it looks like excessive code to Google (and I'm still worried about rankings and things) -- but I'm getting everything ready for a big "push" for when they get the kinks worked out of their systems and fully embraced linked data.(it's just a matter of uncommenting a few lines of code here and there).

:: fingers crossed ::

excellent job converting the gov data - I love it and hope I can make some good use of it.