Linked data that isn't: the failings of RDF

OK, a bit of hyperbole in the morning. One of the goals of RDF is to create the Semantic Web, an interwoven network of data seamlessly linked by shared identifiers and shared vocabularies. Everyone uses the same identifiers for the same things, and when they describe these things they use the same terms. Simples.

Of course, the reality is somewhat different. Typically people don't reuse identifiers, and there are usually several competing vocabularies we can chose from. To give a concrete example, consider two RDF documents describing the same article, one provided by CiNii, the other by CrossRef. The article is:

Astuti, D., Azuma, N., Suzuki, H., & Higashi, S. (2006). Phylogenetic Relationships Within Parrots (Psittacidae) Inferred from Mitochondrial Cytochrome-b Gene Sequences(Phylogeny). Zoological science, 23(2), 191-198. doi:10.2108/zsj.23.191

You can get RDF for a CiNii record by appending ".rdf" to the URL for the article, in this case http://ci.nii.ac.jp/naid/130000017049. For CrossRef you need a Linked Data compliant client, or you can do something like this:

curl -D - -L -H "Accept: application/rdf+xml" "http://dx.doi.org/10.2108/zsj.23.191"

You can view the RDF from these two sources here and here.

No shared identifiers
The two RDF documents have no shared identifiers, or at least, any identifiers they do share aren't described in a way that is easily discovered. The CrossRef record knows nothing about the CiNii record, but the CiNii document includes this statement:

<rdfs:seeAlso rdf:resource="http://ci.nii.ac.jp/lognavi?name=crossref
&amp;id=info:doi/10.2108/zsj.23.191" dc:title="CrossRef" />

So, CiNii knows about the DOI, but this doesn't help much as the CrossRef document has the URI "http://dx.doi.org/10.2108/zsj.23.191", so we don't have an explicit statement that the two documents refer to the same article.

The other shared identifier the documents could share is the ISSN for the journal (0289-0003), but CiNii writes this without the "-", and uses the PRISM term "prism:issn", so we have:

<prism:issn>02890003</prism:issn>

whereas CrossRef writes the ISSN like this:

<ns0:issn xmlns:ns0="http://prismstandard.org/namespaces/basic/2.1/">
0289-0003</ns0:issn>

Unless we have a linked data client that normalises ISSNs before it does a SPARQL query we will miss the fact that these two articles are in the same journal.

Inconsistent vocabularies
Both CiNii use the PRISM vocabulary to describe the article, but they use different versions. CrossRef uses "http://prismstandard.org/namespaces/basic/2.1/" whereas CiNii uses "http://prismstandard.org/namespaces/basic/2.0/". Version 2.1 versus version 2.0 is a minor difference, but the URIs are different and hence they are different vocabularies (having version numbers in vocabulary URIs is asking for trouble). Hence, even if CiNii and CrossRef wrote ISSNs in the same way, we'd still not be able to assert that the articles come from the same journal.
Inconsistent use of vocabularies
Both CiNii use FOAF for author names, but they write the names differently:

<foaf:name xml:lang="en">Suzuki Hitoshi</foaf:name>

<ns0:name xmlns:ns0="http://xmlns.com/foaf/0.1/">Hitoshi Suzuki</ns0:name>

So, another missed opportunity to link the documents. One could argue this would be solved if we had consistent identifiers for authors, but we don't. In this case CiNii have their own local identifiers (e.g. http://ci.nii.ac.jp/nrid/1000040179239), and CrossRef has a rather hideous looking Skolemisation: http://id.crossref.org/contributor/hitoshi-suzuki-2gypi8bnqk7yy.

In summary, it's a mess. Both CiNii and CrossRef organisations are whose core business is bibliographic metadata. It's great that both are serving RDF, but if we think this is anything more than providing metadata in a useful format I think we may be deceiving ourselves.

Referring to a one-degree square in RDF using c-squares

I'm in the midst of rebuilding iSpecies (my mash-up of Wikipedia, NCBI, GBIF, Yahoo, and Google search results) with the aim of outputting the results in RDF. The goal is to convert iSpecies from a pretty crude "on-the-fly" mash-up to a triple store where results are cached and can be queried in interesting ways. Why? Partly because I think such a triple store is an obvious way to underpin a "biodiversity hub" of the kind envisaged by PLoS (see my earlier post).

As ever, once one embarks down the RDF route (and I've been here before), one hits all the classic stumbling blocks, such as "what URI do I use for a thing?", and "what vocabulary do I use to express relationships between things?". For example, I'd like to represent the geographic distribution of a taxon as depicted on a GBIF map. How do I describe this in a RDF document?

To make this concrete, take one of my favourite animals, the New Zealand mud crab Helice crassa. Here's the GBIF map for this taxon:


This map has the URL (I kid you not):

http://ogc.gbif.org/wms?request=GetMap
&bgcolor=0x666698
&styles=,,,
&layers=gbif:country_fill,gbif:tabDensityLayer,gbif:country_borders,gbif:country_names
&srs=EPSG:4326
&filter=()(
%3CFilter%3E
%3CPropertyIsEqualTo%3E
%3CPropertyName%3Eurl
%3C/PropertyName%3E
%3CLiteral%3E
%3C![CDATA[http%3A%2F%2Fdata.gbif.org%2Fmaplayer%2Ftaxon%2F17462693%2FtenDeg%2F-45%2F160%2F]]%3E
%3C/Literal%3E
%3C/PropertyIsEqualTo%3E
%3C/Filter%3E)()()
&width=721
&height=362
&Format=image/png
&bbox=160,-45,180,-35

(or http://bit.ly/cuTFW9, if you prefer). Now, there's no way I'm using this URL! Plus, the URL identifies an image, not the distribution.

But, if we look at the map we see that it is made of 1° × 1° squares. If each of those had a URI then I could simply list those squares as the distribution of the crab. This seems straightforward as GBIF has a service that provides these squares. For example, the URL http://data.gbif.org/species/17462693 (where 17462693 corresponds to Helice crassa) returns:

MINX	MINY	MAXX	MAXY	DENSITY
167.0	-45.0	168.0	-44.0	5
174.0	-42.0	175.0	-41.0	20
174.0	-38.0	175.0	-37.0	17
174.0	-37.0	175.0	-36.0	4

These are the 1° × 1° squares for which there are records of Helice crassa. Now, what I'd like to do is have a URI for each square, and I'd like to do this without reinventing the wheel. I've come across a URI space for points of the globe (the WGS 84 Geographic Point URI Space"), but not one for polygons. Then it dawned on me that perhaps c-squares, developed by Tony Rees at the CSIRO in Australia, would do the trick¹. To quote Tony:

C-squares is a system for storage, querying, display, and exchange of "spatial data" locations and extents in a simple, text-based, human- and machine- readable format. It uses numbered (coded) squares on the earth's surface measured in degrees (or fractions of degrees) of latitude and longitude as fundamental units of spatial information, which can then be quoted as single squares (similar to a "global postcode") in which one or more data points are located, or be built up into strings of codes to represent a wide variety of shapes and sizes of spatial data "footprints".

C-squares appeal partly (and this says nothing good about me) because they have a slightly Byzantine syntax. However, they are short, and quite easy to calculate. I'll let the reader find out the gory details. To give an example, my home town, Auckland, has latitude -36.84, longitude 174.74, which corresponds to the 1° × 1° c-square with the code 3317:364.

Now, all I need to do is convert c-squares into URIs. If you append the c-square to http://bioguid.info/csquare:, like this, http://bioguid.info/csquare:3317:364, you get a linked data-friendly URI for the c-square. In a web browser you get a simple web page like this:


A linked data client will get RDF, like this:

<?xml version="1.0" encoding="utf-8"?>
<rdf:RDF 
   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" 
   xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" 
   xmlns:dcterms="http://purl.org/dc/terms/" 
   xmlns:dwc="http://rs.tdwg.org/dwc/terms/" 
   xmlns:geom="http://fabl.net/vocabularies/geometry/1.1/">
   <dcterms:Location rdf:about="http://bioguid.info/csquare:3307:364">
      <rdfs:label>3307:364</rdfs:label>
      <geom:xmin>74</geom:xmin>
      <geom:ymin>-37</geom:ymin>
      <geom:xmax>75</geom:xmax>
      <geom:ymax>-36</geom:ymax>
      <dwc:footprintWKT>POLYGON((-37 75,-37 74,-36 74,-36 75,-37 75))</dwc:footprintWKT>
   </dcterms:Location>
</rdf:RDF>

Now, I can refer to each square by it's own URI. This will also enable me to query a triple store by c-square (e.g., what other taxa occur within this 1° × 1° square?).

1. Tony Rees had emailed me about this in response to a tweet about URIs for co-ordinates, but it took me a while to realise how useful c-square notation could be.