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.

TreeBASE II RDF

One of the potentially powerful features of TreeBASE II is availability of a RDF version of a study. This means that, in principle, one could take the RDF for a TreeBASE study, combine it with RDF from other sources, and generate a richer view of a particular study. For example, if a TreeBASE study has a DOI, then we could link it to bibliographic details for the study, and through them to other information, such as GenBank sequences, specimens, etc. (see my little linked data browser for an example of some of this linking). If we added a phylogeny viewer, then we'd have a great tool for browsing the basic components of a phylogenetic study.

Unfortunately, we're not there yet. I've been trying to make sense of TreeBASE II RDF, and frankly, it's a mess. Here are some of the problems:

TreeBASE URIs aren't linked data compliant
The canonical URI for a study (e.g., http://purl.org/phylo/treebase/phylows/study/TB2:S10423) doesn't conform to the linked data approach. In fact, the URI crashes the linked data validator, so I tried another test.

curl --include 
   --header "Accept: application/rdf+xml" 
   http://purl.org/phylo/treebase/phylows/study/TB2:S10423

To be a valid linked data resource this request should return a 303 HTTP status code. Instead we get a 302 and some HTML. Linked data clients won't be able to extract information from this URI.

SKOS matching
There are some odd things going on in the RDF. It contains statements of the form:

<rdf:Description rdf:ID="otu1789319">
   <skos:closeMatch rdf:resource="http://purl.uniprot.org/taxonomy/76066.rdf">
</rdf:Description>

(I've tidied this up a little from the original, rather verbose RDF). This asserts that the TreeBASE OTU otu1789319 corresponds to the NCBI taxon with the taxonomy id 76066 (represented by the Uniprot URI). Except, it doesn't really. As far as I understand it, SKOS is about matching concepts, not documents. The URI http://purl.uniprot.org/taxonomy/76066.rdf is a document URI (specifically, a RDF document), the URI http://purl.uniprot.org/taxonomy/76066 is the taxon. The match should really be to http://purl.uniprot.org/taxonomy/76066. Then I've come across statements that match TreeBASE OTUs to http://purl.uniprot.org/taxonomy/0.rdf. This URI doesn't exist (we get a 404). This seems an odd way to say that we don't have a match -- if we don't have a match, don't include it in the RDF.

Local URIs for trees don't work
The RDF is full of local URIs such as http://purl.org/phylo/treebase/phylows/#tree1790755, which don't resolve. In fact they generate a rather spectacular Tomcat exception. I don't understand why we need local URIs. Everything in TreeBASE should have a global URI. Then we can avoid unnecessary statements such as:

http://purl.org/phylo/treebase/phylows/#tree1790755 owl:sameAs http://purl.org/phylo/treebase/phylows/tree/TB2:Tr7899

which links a local resource to a global one http://purl.org/phylo/treebase/phylows/tree/TB2:Tr7899. Incidentally, this URI doesn't resolve, despite claims that this bug has been fixed.

No links between tree and study
But the show stopper for me is that there is no link between a study and a tree! There is no triple in the RDF specifying any relationship between these two entities. To me this is just about the most important thing I need. I want to be able to query TreeBASE RDF using a study identifier (either from TreeBASE itself, or from an external identifier such as a DOI or a PubMed number). As it stands the TreeBASE II RDF is almost useless. I can't get it via a linked data client, it's full of URIs that don't resolve, and it lacks key triples that would glue things together.

RDF != XML

I can't help thinking that the RDF output hasn't been designed with end use in mind. I know from my own experience that it's not until you try to do something with the RDF that you realise how poor some design decisions may have been.

It's not enough to pump out RDF and hope for the best. RDF is not XML, which is just a verbose format for moving data around. RDF brings with it all sorts of expectations about how clients will resolve it, how they will interpret URIs, and the kinds of queries that will be performed. We are achingly close to being able to tie everything together, but not with RDF TreeBASE II is currently making available.

Linked data part 2

Continuing the Friday folly theme, below is a screencast of a linked data browser that uses the same ideas as last week's screencast, but uses a custom browser I've written to display the results in a more user-friendly way.

Linking the data together from Roderic Page on Vimeo.

The demo is live, you can view it at http://iphylo.org/~rpage/browser/www/uri/http://bioguid.info/doi:10.1371/journal.pone.0001787. Under the hood the browser uses bioGUID as the primary linked data provider (although it should consume any valid linked data source, for example Dbpedia). The data is stored in a local triple store (ARC), and the web interface is created by transforming SPARQL queries into HTML using XSLT. You can add data to it by editing the URL in the browser location bar and reloading the page, or entering a URL on the page. Linked data URLs be entered next to the Browse button as is, e.g. http://dbpedia.org/resource/Euphausia, or appended to http://iphylo.org/~rpage/browser/www, e.g. http://http://iphylo.org/~rpage/browser/www/http://dbpedia.org/resource/Euphausi. Other identifiers, such as DOIs, PubMed ids, and specimens need to be resolved via bioGUID, e.g. http://iphylo.org/~rpage/browser/www/uri/http://bioguid.info/gi:86161637.

All still very crude, but I hope you get the idea.

Linking biodiversity data

Time for a Friday folly. I've made a clunky screencast showing an example of linking biodiversity data together, using bioGUID as the universal wrapper around various data sources. I started with GenBank sequence EF013683, added another, EF013555, then explored some links (specimen, publication, taxon, journal), using the OpenLink RDF Browser:

Linking biodiversity data from Roderic Page on Vimeo.

You can try the URIs I used in the linked data browser of your choice:

• http://bioguid.info/genbank:EF013683
• http://bioguid.info/genbank:EF013555
• http://bioguid.info/occurrence:antweb:casent0106008
• http://bioguid.info/taxonomy:411739
• http://bioguid.info/doi:10.1073/pnas.0605858103
• http://bioguid.info/issn:0027-8424

The demo is a bit clunky, partly because the linked data browser is generic. What we really need is a browser that is tailored to displaying the kind of data we're interested, and hides the gory details under the hood. But the goal is to show that, once everything we care about has a resolvable URI that provides data in a consistent form, and we re-use identifiers, then we can glue stuff together with relative ease. In principle we can simply crawl this web of data (you can append other DOIs, ISSNs, and Genbank accession numbers to http://bioguid.info and get RDF to your heart's content).

None of this is particularly new, we've had RDF in biodiversity informatics for at least five years, there are various linked data-style projects, such as GeoSpecies and the first iteration of bioGUID, and some people (such as Roger Hyam) have been pushing HTTP URIs + RDF for a while, but we seem remarkably unable to get traction on this. Notably, no major biodiversity provider provides RDF (by major I mean GenBank or GBIF size). We make diagrams like the one I drew for GBIF last year, we make the case that linking is a Good Thing™, and yet nothing much happens. This suggests that the idea is still not be presented in a compelling enough fashion. Certainly, clunky demos like the one above probably won't help much. Linked Data clients are generally pretty awful things to use. I think we're going to need some compelling applications that really grab people's attention.

EOL, the BBC, and Wikipedia

Last month EOL took the brave step of including Wikipedia content in its pages. I say "brave" because early on EOL was pretty reluctant to embrace Wikipedia on this scale (see the report of the Informatics Advisory Group that I chaired back in 2008), and also because not all of EOL's curators have been thrilled with this development. Partly to assuage their fears, EOL displays Wikipedia-derived content on a yellow background to flag its "unreviewed" status, such as this image of the python genus Leiopython:

It's interesting to compare EOL's approach to Wikipedia with that taken by the BBC, as documented in Case Study: Use of Semantic Web Technologies on the BBC Web Sites. The BBC makes extensive use of content from community-driven external sites such as MusicBrainz and Wikipedia. They embed the content in their own pages, stating where the content came from, but not flagging it as any less meaningful or reliable than the BBC's own content (i.e., no garish yellow background).

Furthermore, the BBC does two clever things. Firstly:

To facilitate integration with the resources external to bbc.co.uk the music site reuses MusicBrainz URL slugs and Wildlife Finder Wikipedia URL slugs. This means that it is relatively straight forward to find equivalent concepts on Wikipedia/DBpedia and Wildlife Finder and, MusicBrainz and /music.

This means that if the identifier for the artist Bat for Lashes in Musicbrainz is http://musicbrainz.org/artist/10000730-525f-4ed5-aaa8-92888f060f5f.html, the BBC reuse the "slug" 10000730-525f-4ed5-aaa8-92888f060f5f and create a page at http://www.bbc.co.uk/music/artists/10000730-525f-4ed5-aaa8-92888f060f5f. Likewise, if the Wikipedia page for Varanus komodoensis is http://en.wikipedia.org/wiki/Komodo_dragon, then the BBC Wildlife Finder page becomes http://www.bbc.co.uk/nature/species/Komodo_dragon, reusing the slug Komodo_dragon.

Reusing identifiers like this can greatly facilitate linking between databases. I don't need to do a search, or approximate string matching, I just reuse the slug. Note that this is a two-way thing, it is trivial for Musicbrainz to create links to BBC information, and visa versa. Reusing identifiers isn't new, other examples include Amazon.com's ASIN (which for books are ISBNs), and BHL reuses uBio NameBankIDs -- want literature that mentions the Komodo dragon? Use the uBio NameBankID 2546401 in a BHL URL http://www.biodiversitylibrary.org/name/2546401.

The second clever thing the BBC does is treat the web as a content management system:

BBC Music is underpinned by the Musicbrainz music database and Wikipedia, thereby linking out into the Web as well as improving links within the BBC site. BBC Music takes the approach that the Web itself is its content management system. Our editors directly contribute to Musicbrainz and Wikipedia, and BBC Music will show an aggregated view of this information, put in a BBC context.

Instead of separating BBC and Wikipedia content (and putting the later in quarantine as does EOL), the BBC embraces Wikipedia, editing Wikipedia content if they feel a page need improving. One advantage of this approach is that it avoids the need for the BBC to replicate Wikipedia, either in terms of content (the BBC doesn't need to write its own descriptions of what an organism does) or services (the BBC doesn't need to develop tools for people to edit the BBC pages, people use Wikipedia's infrastructure for this). Wikipedia provides core text and identifiers, BBC provides its own unique content and branding.

EOL is trying something different, and perhaps more challenging (at least to do it properly). Given that both EOL and Wikipedia offer text about organisms, there is likely to be overlap (and possibly conflict) between what EOL and Wikipedia say about the same taxon. Furthermore, there will be duplication of information such as bibliographic references. For example, the Wikipedia content included in the EOL page for Leiopython contains a bibliography, which includes these references:

Hubrecht AAW. 1879. Notes III on a new genus and species of Pythonidae from Salawatti. Notes from the Leyden Museum 14-15.

Boulenger GA. 1898. An account of the reptiles and batrachians collected by Dr. L. Loria in British New Guinea. Annali del Museo Civico de Storia Naturale di Genova (2) 18:694-710

The genus name Leiopython was published by Hubrecht (1879), and Boulenger (1898) is cited in support of a claim that a distribution record is erroneous. Hence, these look like useful papers to read. Neither reference on the Wikipedia page is linked to an online version of the article, but both have been scanned by EOL's partner BHL (you can see the articles in BioStor here, and here, respectively)¹.

Problem is, you'd be hard pressed to discover this from the EOL page. The BHL results do list the journal Notes from the Leyden Museum, but you'd have to visit the links manually to discover whether they include Hubrecht (1879) (they do, as well as various occurences of Leiopython in the indices for the journal). In part this problem is a consequence of the crude way EOL handles bibliographies retrieved from BHL, but it's symptomatic of a broader problem. By simply mashing EOL and Wikipedia content together, EOL is missing an opportunity to make both itself and Wikipedia more useful. Surely it would be helpful to discover what publications cited on Wikipedia pages are in BHL (or in the list of references for hand-curated EOL pages)? This requires genuine integration (for example by reusing existing bibliographic identifiers such as DOIs, and tools such as OpenURL resolvers). If it fails to do this, EOL will resemble crude pre-Web 2.0 mashups where people created web pages that had content from external sites enclosed in <IFRAME> tags.

The contrast between the approaches adopted by EOL and the BBC is pretty stark. The BBC has devolved text content to external, community-driven sites that it thinks will do a better job than the BBC could alone. EOL is trying to integrate Wikipedia into it's own text content, but without addressing the potentially massive duplication (and, indeed, possible contradictions) that are likely to arise. Perhaps it's time for EOL to be as brave as the BBC, as ask itself whether it is sensible for EOL to try and occupy the same space as Wikipedia.

1. Note that the bibliographic details of both papers are wanting, Hubrecht 1879 is in volume 1 of Notes from the Leyden Museum, and Annali del Museo Civico de Storia Naturale di Genova series 2, volume 18 is also treated as volume 38.

GBIF and Linked Data

At the end of day two of the GBIF LSID-GUID Task Group I put together this crude diagram to summarise some of the possible links between biodiversity data and the larger linked data cloud, which I, among others, have argued is where biodiversity informatics should be heading. Here's my hastily put together diagram (created using the wonderful OmniGraffle):

I've put GBIF at the centre since we're at GBIF, and it's them we are trying to convince. Yellow circles are biodiversity data sources (which aren't linked data providers (but some can me made so using, for example, my LSID proxy resolver), white circles are linked data sources.

The "sales pitch"is that if we join the linked data cloud we open up the possibility of some very powerful queries, especially once that are outside the relatively narrow scope of what GBIF and TDWG concern themselves with. Imagine being able to query biodiversity data with respect to population and economic data across countries. These are the sort of things we could realistically aim for.

On a practical level, it also means biodiversity database could devolve a lot of their tasks to other databases (via reusing identifiers). Some taxonomists have DBPedia URIs, and more could be added to Wikipedia (and so will find there way into DBPedia). Geonames provides geographic URIs which we could reuse, and so on. Within our own community we could do a better job of reusing our own identifiers, and reusing external ones (such as taxa in Wikipedia).

It's late, this is a rushed diagram, and I don't know if it's going to end up in whatever report we manage to assemble tomorrow (our final day). But I hope it captures some of the scope of what we're looking at. I know there are some problems (as have been pointed out to me on Twitter), I'll try and deal with these tomorrow.

EOL, Wikipedia, TDWG, LinkedData, and the Vision Thing

Time for more half-baked ideas. There's been a lot of discussion on Twitter about EOL, Linked Data (sometimes abbreviated LOD), and Wikipedia. Pete DeVries (@pjd) is keen on LOD, and has been asking why TDWG isn't playing in this space. I've been muttering dark thoughts about EOL, and singing the praises of Wikipedia. On so it goes on. So, here's one vision of where we could (?should) be going with this.

Let's imagine that we do indeed want to play in the Linked Data space. The concern that tends to raised the most is that biodiversity informatics uses LSIDs as the standard GUID, and this doesn't play nice with Linked Data. This is true, but not life threatening. There are various hacks (like this and this that deal with this).

But, the real concern (I think) is that we need a way to link our stuff to the rest of the Linked Data cloud. That is, wherever possible we need to reuse existing identifiers. In the LOD diagram below (for the latest version see here) DBpedia.org is key to linking much of this together, and major players (such as the BBC) are now using DBpedia.org to make connections.



DBpedia.org is based on Wikipedia, so I think you can see where this is going. There are some 120,000+ taxon pages in Wikipedia, so that's some 120,000+ identifiers in DBpedia.org that others interested in organisms can (and will) use to refer to taxa. Given the centrality of Wikipedia and DBpedia to LOD, why don't we adopt DBpedia.org URIs as the default GUID for our taxa? At present we have numerous, competing identifiers (e.g., NCBI tax ids, ITIS tsn's, Catalogue of Life LSIDs, uBio NameBankID's, plus LSIDs from various nomenclators). For users this is a mess -- which one do I use? Deciding requires dealing with issues (such as the difference between nomenclatural codes, and between taxonomic names and concepts, etc., that frankly, nobody outside our community cares about.

So, if we want to play with LOD, we need to make our identifiers play nice (straightforward), and we should think seriously about adopting DBpedia.org URIs as the default GUID for taxa.

Now, where does this leave EOL? Well, frankly, it should get out of the business of making web pages for taxa, because Wikipedia owns that space already. Their pages are fewer, but often much more detailed than the corresponding EOL page, and Wikipedia reacts faster to new discoveries. Wikipedia supports community editing, versioning, and quite sophisticated tools for handling biblographic references.

There's plenty of scope for userful tools and services for EOL to develop, but I think the real game is elsewhere. Now, Wikipedia is far from perfect. It's basically semi-structured text with a God-awful template language, and it would benefit greatly from more structure (e.g., as could be provided by Semantic Mediawiki), but I think we should think about building upon it. We could build our own (and my experiments over at itaxon.org explore this), but the big challenge is getting a community around a project, and if David Shorthouse's pronouncement that The Community is Dead is correct, then maybe we should get on board with the community that already exists. Perhaps what EOL should be doing is talking to Wikipedia, improving the existing templates for taxon pages, and creating bots to automatically populate Wikipedia with more taxon pages.

Semantic Publishing: towards real integration by linking

PLoS Computational Biolgy has recently published "Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article" (doi:10.1371/journal.pcbi.1000361) by David Shotton and colleagues. As a proof of concept, they took Reis et al. (doi:10.1371/journal.pntd.0000228) and "semantically enhanced" it:

These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit “Citations in Context”, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps.

The enhanced article is here: doi:10.1371/journal.pntd.0000228.x001. For background on these enhancements, see also David's companion article "Semantic publishing: the coming revolution in scientific journal publishing" (doi:10.1087/2009202, PDF preprint available here). The process is summarised in the figure below (Fig. 10 from Shotton et al., doi:10.1371/journal.pcbi.1000361.g010).



While there is lots of cool stuff here (see also Elsevier's Article 2.0 Contest, and the Grand Chalenge, for which David is one of the judges), I have a couple of reservations.

The unique role of the journal article?

Shotton et al. argue for a clear distinction between journal article and database, in contrast to the view articulated by Philip Bourne (doi:10.1371/journal.pcbi.0​010034) that there's really no difference between a database and a journal article and that the two are converging. I tend to favour the later viewpoint. Indeed, as I argued in my Elsevier Challenge entry (doi:10.1038/npre.2008.2579.1), I think we should publish articles (and indeed data) as wikis, so that we can fix the inevitable error. We can always roll back to the original version if we want to see the author's original paper.

Real linking

But my real concern is that the example presented is essentially "integration by linking", that is, the semantically enhanced version gives us lots of links to other information, but these are regular hyperlinks to web pages. So, essentially we've gone from pre-web documents with no links, to documents where the bibliography is hyperlinked (most online journals), to documents where both the bibliography and some terms in the text are hyperlinked (a few journals, plus the Shotton et al. example). I'm a tad underwhelmed.
What bothers me about this is:

1. The links are to web pages, so it will be hard to do computation on these (unless the web page has easily retrievable metadata)
2. There is no reciprocal linking -- the resource being linked to doesn't know it is the target of the link

Web pages are for humans

The first concern is that the marked-up article is largely intended for human readers. Yes, there are associated metadata files in RDF N3, but the core "added value" is really only of use to humans. For it to be of use to a computer, the links would have to go to resource that the computer can understand. A human clicking on many of the links will get a web page and they can interpret that, but computers are thick and they need a little help. For example, one hyperlinked term is Leptospira spirochete, linked to the uBio namebank record (click on the link to see it). The link resolves to a web page, so it's not much use to a computer (unless if has a scrapper for uBio HTML). Ironically, uBio serves LSIDs, so we could retrieve RDF metadata for this name (urn:lsid:ubio.org:namebank:255659), but there's nothing in the uBio web page that tells the computer that.

Of course, Shotton et al. aren't responsible for the fact that most web pages aren't easily interpreted by computers, but simply embedding links to web pages isn't a big leap forward. What could they have done instead? One approach is to link to resources that are computer-readable. For example, instead of linking the term "Oswaldo Cruz Foundation" to that organisation's home page (http://www.fiocruz.br/cgi/cgilua.exe/sys/start.htm?tpl=home), why not use the DBpedia URI http://dbpedia.org/page/Instituto_Oswaldo_Cruz? Now we get both a human-readable page, and extensive RDF that a computer can use. In other words, if we crawl the semantically enhanced PLoS article with a program, I want to be able to have that crawler follow the links and still get useful information, not the dead end of a HTML web page. Quite a few of the institutions listed in the enhanced paper have DBPedia URIs:

• Brazilian National Commission for Ethics in Research
• Brazilian National Research Council
• Centers for Diseases Control and Prevention
• Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz, Ministério da Saúde
• Company for Urban Development of the State of Bahia (CONDER)
• Division of International Medicine and Infectious Diseases, Weill Medical College of Cornell University
• Environmental Systems Research Institute
• Escola Nacional da Saúde Pública, Fundação Oswaldo Cruz, Ministério da Saúde
• Image Bioinformatics Research Group, Department of Zoology, University of Oxford
• MRC Biostatistics Unit
• Oswaldo Cruz Foundation
• R Foundation for Statistical Computing
• Royal Tropical Institute, Holland
• Secretária Estadual de Saúde da Bahia
• Universidad de Buenos Aires
• Universidade Federal Rural do Rio de Janeiro
• Urban Health Council of Pau da Lima
• US National Institutes of Health
• Weill Medical College of Cornell University
• WHO Collaborative Laboratory for Leptospirosis

Why does this matter? Well, if you use DBPedia URIs you get RDF, plus you get connections with the Linked Data crowd, who are rapidly linking diverse data sets together:


I think this is where we need to be headed, and with a little extra effort we can get there, once we move on from thinking solely about human readers.

An alternative approach (and one that I played with in my Challenge entry, as well as my ongoing wiki efforts) is to create what Vandervalk et al. term a "semantic warehouse" (doi:10.1093/bib/bbn051). Information about each object of interest is stored locally, so that clicking on a link doesn't take you off-site into the world wide wilderness, but to information about that object. For example, the page for the paper Mitochondrial paraphyly in a polymorphic poison frog species (Dendrobatidae; D. pumilio) lists the papers cited, clicking on one takes you to the page about that paper. There are limitations to this approach as well, but the key thing is that one could imagine doing computations over this (e.g., computing citation counts for DNA sequences, or geospatial queries across papers) that simple HTML hyperlinking won't get you.

Reciprocal links

The other big issue I have with the Shotton et al. "integration by linking" is that it is one-way. The semantically enhanced paper "knows" that it links to, say, the uBio record for Leptospira, but uBio doesn't know this. It would enhance the uBio record if it knew that doi:10.1371/journal.pntd.0​000228.x001 linked to it.

Links are inherently reciprocal, in the sense that if paper 1 cites paper 2, then paper 2 is cited by paper 1.

Publishers understand this, and the web page of an article will often show lists of papers that cite the paper being displayed. How do we do this for data and other objects of interest? If we database everything, then it's straightforward. CrossRef is storing citation metadata and offers a "forward linking" service, some publishers (e.g., Elsevier and Highwire) offer their own versions of this. In the same way, this record for GenBank sequence AY322281 "knows" that it is cited by (at least) two papers because I've stored those links in a database. Knowing that you're being linked to dramatically enhances discoverability. If I'm browsing uBio I gain more from the experience if I know that the PLoS paper cites Leptospira.

Knowing when you're being linked to

If we database everything locally then reciprocal linking is easy. But, realistically, we can't database everything (OK, maybe that's not strictly true, can can think of Google as a database of everything). The enhanced PLoS paper "knows" that it cites the uBio record, how can the uBio record "know" that it has been cited by the PLoS paper? What if the act of linking was reciprocal? How can we achieve this in a distributed world? Some possibilities:

• we have an explicit API embedded in the link so that uBio can extract the source of the link (could be spoofed, need authentication?)
• we use OpenURL-style links that embed the PLoS DOI, so that uBio knows the source of the link (OpenURL is a mess, but potentially very powerful)
• uBio uses the HTTP referrer header to get the source of the link, then parses the PLoS HTML to extract metadata and the DOI (ugly screen scraping, but no work for PLoS)

Obviously this needs a little more thought, but I think that real integration by linking requires that the resources being linked are both computer and human readable, and that both resources know about the link. This would create much more powerful "semantically enhanced" publications.