More on contact pages and linked data

I wrote about RDF-encoding contact information a little earlier and had some very helpful comments. On reflection, and after exploring the “View Source” options for a couple of institutional contact pages, I’ve had some further thoughts.

- Contacts pages are rarely authored, they are nearly always created on the fly from an underlying database. This makes them natural for expressing in RDF (or microformats). It’s just a question of tweaking the way the HTML wrapper is assembled. Bath University’s Person Finder pages do encode their data in microformats.

- I wondered why more universities don’t encode their data in microformats or (even better) in RDF for Linked Data. One possible answer is that the contact pages were probably one of the earliest examples of constructing web pages from databases. It works, it ain’t broke, so they haven’t needed to fix it! If so, a reasonable case would need to be made for any change, but once made it would be comparatively cheap to carry out.

- A second problem is that it is not at all clear to me what the best encoding and vocabulary for institutional (or organisational unit) contact pages might be. So maybe it’s even less surprising that things have not changed. To say I'm confused is putting it mildly! So what follows list some of the options after further (but perhaps not complete) investigation...

One approach is the hCard microformat, based on the widely used vCard specification, RFC2426 (this is what Bath uses). That’s fine as far as it goes, but microformats don’t seem to fit directly in the Linked Data world. I’m no expect (clearly!), but in particular, microformats don’t use URIs for the names of things, and don’t use RDF. They appear useful for extracting information from a web page, but not much beyond that (I guess I stand to be corrected here!).

Looking at RDF-based encodings, there are options based on vCard, there are FOAF and SIOC (both really coming from a social networking view point), and there’s the Portable Contacts specification.

Given that vCard is a standard for contact information, it would seem sensible to look for a vCard encoding in RDF. It turns out that there are two RDF encodings of vCard, one supposedly deprecated, and the other apparently unchanged since 2006. I now discover an activity to formalise a W3C approach in this area, with a draft submission to W3C edited by Renato Ianella and dating only from last December (2009), but I would need a W3C username and password to see the latest version, so I can't tell how it's going,

Someone asked me a while ago who sets the standards for Linked Data vocabularies. My response at the time was that the users did, by choosing which specification to adopt. At the time, FOAF seemed to have most mentions in this general area, and I rather assumed (see the previous post) that it would have the appropriate elements. However, the “Friend of a Friend” angle really does seem to dominate; this vocabulary does seem to be more about relationships, and to be lacking in some of the elements needed for a contacts page. I suspect this might have stemmed from a desire to stop people compromising their privacy in a spam-laden world. However, those of us in public service posts often need to expose our contact details. However, FOAF does have email as foaf:mbox, which apparently includes phone and fax as well, as you can see from the sample FOAF extract in my earlier post.

In a tweet Dan Brickley suggested: “We'll probably round out FOAF’s address book coverage to align with Portable Contacts spec”, so I had a look at the latter. The main web site didn’t answer, but Google’s cache provided me with a draft spec, which does appear to have the elements I need.

What elements do I need for a contact page? Roughly I would want some or all of:

• Name
• Job title/role in DCC (my virtual organisation)
• (Optional job title/role in home organisation)
• Organisational unit/Organisation
• Address/location
• Phone/fax numbers
• Email address

So what could I do if this information were expressed in RDF in the contact pages for a partner institution (say UKOLN at Bath)? Well, presumably the DCC contact pages would be based on a database showing the staff who work on the DCC, with the contact information directly extracted from the remote pages (either linked in real time or perhaps cached in some way). And if Bath changed their telephone numbers again, our contact details would remain up to date. But more. Given that there are some staff members who have roles in several projects, it would be easy to see who the linkages were between the DCC and the other project (eg RSP in the past, or I2S2 now). Part of the point of Linked Data (rather than microformats) is that one can reason with it; follow the edges of the great global graph…

And perhaps I would be able to find a simple app that extracts a vCard from the contact page to import into my Mac’s Address Book, which is where I started this search from! You wouldn’t think it would be hard, would you? I mean, this isn’t rocket science, surely?

Linked data and staff contact pages

You may remember that I am interested in the extent to which we should use Semantic Web (or Linked Data) on the DCC web site. After some discussions, I reached the conclusion that we should do so, but the tools were not ready yet (this isn’t quite an Augustinian “Oh Lord, make me good but not yet”; specifically, we are moving our web site to Drupal 6, the Linked Data stuff will not be native until Drupal 7, and our consultants are not yet up to speed with Linked Data). I have to say that not all our staff are convinced of the benefits of using RDF etc on the web site, and I have had a mental note to write more about this, real soon now.

I was reminded of this recently. I wanted to phone a colleague who worked at UKOLN, one of our partners, and I didn’t have his details in my address book. So I looked on their web site and navigated to his contacts page. Once there I copied his details into the address book, before lifting the phone to give him a ring. After the call (he wasn’t there; the snow had closed the office), I thought about that process. I had to copy all those details! Wouldn’t it be great if I could just import them somehow? How could that be? UKOLN have expertise in such matters, so I tweeted Paul Walk (now Deputy Director, previously technical manager) asking whether they had considered making the details accessible as Linked Data using something like FOAF. You can guess I’m not fully up to speed with this stuff, but I’m certainly trying to learn!

Paul replied that they had considered putting microformats into the page (I guess this is the hCard microformat), and then asked me whether my address book understood RDF, or if I was going to script something? I was pretty sure the answer to the second part was “no” as I suspect such scripting currently is beyond me, and told Paul that I was using MacOSX 10.6 Address Book; it says nothing about RDF, but will import a vcard. I was thinking that if there was appropriate stuff (either hCard microformat or RDFa with FOAF) on the page, I might find an app somewhere that would scrape it off and make a vcard I could import.

Paul’s final tweet was: “@cardcc see the use-case, not sure it's a 'linked data' problem though. What are the links that matter if you're scraping a single contact?”

Well, I couldn’t think of a 140-character answer to that question, which seemed to raise issues I had not thought about properly. What are the links that matter? Was it linked data, or just coded data that I wanted? Is this really a semantic web question rather than linked data? Or is it a RDF question? Or a vocabulary question? Gulp!

After some thought, perhaps Paul was as constrained by his 140 characters as I was. Surely a contacts page contains both facts and links within itself. See the Wikipedia page on FOAF for examples of a FOAF file in turtle for Jimmy Wales; the coverage is pretty much like a contacts page.

So Paul’s contact page says he works for UKOLN at the University of Bath, and gives the latter’s address (I guess formally speaking he works in UKOLN, an administrative unit, and is employed by the University); that his position in UKOLN is Deputy Director, that his phone, fax and email addresses are x, y and z. All of these are relationships between facts, expressible in the FOAF vocabulary. With RDFa, that information could be explicitly encoded in the HTML of the page and understood by machines, rather than inferred from the co-location of some characters on the page (the human eye is much better at such inferences). So there’s RDF, right there. Is that Linked Data? Is it Semantic Web? I’m not really sure.

More to the point, would it have been any greater use to me if it had been so encoded? A FOAF-hunting spider could traverse the web and build up a network of people, and I might be able to query that network, and even get the results downloaded in the form of a vcard that I could import into my Mac Address Book. That sounds quite possible, and the tools may already exist. Or, there may exist an app (what we used to call a Small Matter Of Programming, or a SMOP) that I could point at a web page with FOAF RDFa on it. Perhaps that’s what Paul was after in relation to scripting. Maybe the upcoming Dev8D might find this an interesting task to look at?

What other things could be done with such a page? Well, Paul or others might use it to disambiguate the many Paul Walk alter egos out there. You’ll see I have a simple link to Paul’s contact page above, but if this blog were RDF-enabled, perhaps we could have a more formal link to the assertions on the page, eg to that Paul Walk’s phone number, that Paul Walk’s email address, etc.

Well I’m not sure if this makes sense, and it does feel like one of those “first fax machine” situations. However FOAF has been around for a long while now. Does that mean that folk don’t perceive an advantage in such formal encodings to balance their costs, or is this an absence of value because of a lack of exploitable tools? If so, anyone going to Dev8D want to make an app for me?

(It’s also possible of course that Paul doesn’t want his details to be spidered up in this way, but I guess none of us should put contact details on the web if that’s our position.)

By the way, I found a web page called FOAF-a-matic that will create FOAF RDF for you. Here's an extract from what it created for me, in RDF:

<foaf:Person rdf:ID="me"> <foaf:name>Chris Rusbridge</foaf:name> <foaf:title>Mr</foaf:title> <foaf:givenname>Chris</foaf:givenname>

<foaf:family_name>Rusbridge</foaf:family_name>

<foaf:mbox rdf:resource="mailto:c.rusbridge@xxxxx"/> <foaf:workplaceHomepage rdf:resource="http://www.dcc.ac.uk/"/>

</foaf:Person>

What could I do with that now?

More activity on semantic publishing

If you saw tweets from @cardcc today, you might realise I’ve been very interested in a couple of recent developments in semantic publishing. I wrote earlier about linking data to journal articles, including David Shotton’s adventures in semantic publishing. David’s work was one of those included in the review article in the Biochemical Journal by Attwod, Kell, McDermott et al (2009). The article ranged over the place of ontologies and databases, science blogs, and various experiments. These included

• RSC and Project Prospect,
• The ChemSpider Journal of Chemistry,
• The FEBS Letters experiment,
• PubMed Central and BioLit,
• Shotton’s PLoS experiment,
• Elsevier Grand Challenge,
• Liquid Publications,
• The semantic Biochemical Journal experiment.

The latter was the real focus of the article, available in PDF, but which if read through a special reader called Utopia Document displayed some active capabilities. These included the ability to visualise and rotate 3-d images of proteins, to see tables represented as graphs (or vice versa) and to link to entries in nucleic acid databases. The capabilities were perhaps a bit awkward to spot and to manipulate, but still interesting. This article is (gold) open access. Other articles in the issue have also been instrumented in this way.

It’s clearly early days for Utopia, and I wasn’t wholly impressed with it as a PDF reader, but I was certainly very excited at some of what I read and saw.

I also read today a very different article (I think not available on open access), by Ruthensteiner and Hess (2008). They describe the processes in making 3-d models of biological specimens, and presenting them in PDF, readable by a standard Acrobat Reader. The 3-d capability was at least as good as if not better than the Utopia results.

Because it’s getting late, I’ll end with my last tweet:

“My head is spinning with semantic article possibilities. I hope some get picked up in new #jiscmrd proposals, see http://www.jisc.ac.uk/fundingopportunities/funding_calls/2009/12/1409researchdata.aspx"

Attwood, T. K., Kell, D. B., McDermott, P., Marsh, J., Pettifer, S. R., Thorne, D., et al. (2009). Calling International Rescue: knowledge lost in literature and data landslide! The Biochemical journal, 424(3), 317-33. doi: 10.1042/BJ20091474.

Ruthensteiner, B., & Hess, M. (2008). Embedding 3D models of biological specimens in PDF publications. Microscopy research and technique, 71(11), 778-86. doi: 10.1002/jemt.20618. Pubmed abstract.

DCC web site and Linked Data

We at the DCC are in the early stages of refreshing our web site (www.dcc.ac.uk). Nothing you can see yet, but we're talking to a few consultants about what and how we can do better. The ones we have spoken to so far seem pretty clued up on content management systems, and even on web 2.0 approaches. But questions about the role of the Semantic Web or Linked Data get blank looks.

Now our web site is not and will probably never be a major source of data as facts; rather it should contain resources: often documents, sometimes tools, sometimes sharing opportunities. There definitely are facts of various kinds there (which may not sufficiently explicit yet), such as staff contact details, document metadata, event locations and times, etc. But these are a comparatively small part of the content.

Does this (or anything else) justify investment in building a web site that is based on Linked Data/Semantic Web? What advantages could we get in doing so? What advantages could our users get if we did so?

I would really like to get some views on this!

Semantic Web of Linked Data for Research?

In the beginning was the World Wide Web. Then we were going to have the Semantic Web. (Then we had Web 2.0, but that’s another story.) But maybe the Semantic Web wasn’t semantic enough for some, so they changed the name to Linked Data, and it began to take off a little more. Now there’s an argument on whether all linked data are Linked Data!

The debate started with Andy Powell asking on Twitter what name we should use when all the conditions for Linked Data are met except for one, which was the requirement that data be expressed in standards, specifically RDF (see Andy's summary). Tim Berners Lee had suggested there were 4 principles for Linked Data:

1. Use URIs as names for things.
2. Use HTTP URIs so that people can look up those names.
3. When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL).
4. Include links to other URIs. so that they can discover more things.

There were quite strong divisions; one group says roughly: “Linked Data is a brand and a definition; live with it”, while the other group says something like “Linked Data can afford to be inclusive, and will benefit from that” (both of these are extreme simplifications). I’ve read all the remarks and they’re pretty convincing; I mostly agree with them (not much help to you, gentle reader!). Paul Walk's summary is quite balanced. However, I particularly liked a comment made on someone else’s blog post by Dan Brickley, who should know about RDF (quoted by Andy in the post mentioned above):

“I have no problem whatsoever with non-RDF forms of data in “the data Web”. This is natural, normal and healthy. Statistical information, geographic information, data-annotated SVG images, audio samples, JSON feeds, Atom, whatever.

We don’t need all this to be in RDF. Often it’ll be nice to have extracts and summaries in RDF, and we can get that via GRDDL or other methods. And we’ll also have metadata about that data, again in RDF; using SKOS for indicating subject areas, FOAF++ for provenance, etc.

The non-RDF bits of the data Web are – roughly – going to be the leaves on the tree. The bit that links it all together will be, as you say, the typed links, loose structuring and so on that come with RDF. This is also roughly analogous to the HTML Web: you find JPEGs, WAVs, flash files and so on linked in from the HTML Web, but the thing that hangs it all together isn’t flash or audio files, it’s the linky extensible format: HTML. For data, we’ll see more RDF than HTML (or RDFa bridging the two). But we needn’t panic if people put non-RDF data up online…. it’s still better than nothing. And as the LOD scene has shown, it can often easily be processed and republished by others. People worry too much! :)”

I think this makes lots of sense for research data. I’ve been wondering for some time how RDF fits into the world of research data. I asked the NERC Data Managers at their meeting earlier this year, and the general consensus appeared to be that RDF was good for the metadata, but not the actual research data. This seems reasonable and is consistent with Dan’s view above.

But it does rather raise the question about exactly what kinds of data RDF IS suitable for. It begins to look as if it is good for isolated facts, simple relationships and descriptive data. While RDF probably can encode most things you would put in databases or scientific datasets, generally it would be very difficult to express what those databases and datasets can express, and there would be a massive explosion of triples if one tried.

To answer Andy’s original question (what name…), although I was taken with the idea of linked data, it’s clearly too easy to confuse with Linked Data. So I think I’d go with Paul Walk’s suggestion of Web of Data, or interchangeably Dan Brickley's data Web. If we can weave research data into a Web of Data, we’ll be doing well!

Strand B1 research papers at IDCC4

In the morning parallel session B at the International Digital Curation Conference, the ever-interesting Jane Hunter from the University of Queensland began the session speaking about her Aus-e-Lit project (linked to Austlit) The project is based on FRBR, and offers federated search interfaces to related distributed databases. They include tagging and annotation services, and compound object authoring tools… based on an OAI-ORE based tool called Literature Online Research Environment (LORE). These compound objects, published to the semantic web as RDF named graphs, can express complex relationships between authors and works that represent parts of literary history, tracking lineage of derivative works and ideas, scholarly editions, research trails, and also used for teaching and learning objects. There were of course problems: the need for unique identifiers for non-information resources; use of local identifiers, use of non-persistent identifiers; community concern about ontology complexity… but also a desire for more complexity (wasn’t it ever thus)!

Hunter was followed by Kai Naumann, from the State Archive of Baden-Wurttemberg. They have many issues, starting with the very wide range of objects from paper, microfilm etc and beginning digital objects, of which a large number are now being ingested. Need to find resources with finding aids regardless of media and object type. Need to maintain and assure authenticity and integrity. They chose to use the PREMIS approach to representations (which reminded me again how annoying the clash of PREMIS terminology with that of OAIS is!). It seemed to be a very sophisticated approach. Naumann suggested that preservation metadata models should balance 3 aims: instant availability, easy ingest and long-term understandability. For low use (as in real archives), with heterogeneous objects, you need to design relatively simple metadata sets. It’s important to maintain relational integrity between the content and metadata (I’m not sure that has a strict, relational database meaning!). Structural relations between content units can be a critical for authenticity.

Jim Downing of Cambridge came next, speaking for Pete Sefton, USQ (although he admitted he was a pale, short, damp substitute for the real thing!). The topic was embedding metadata & semantics in documents; they work together on the JISC-funded ICE-Theorem project. We need semantically rich documents for science, but most documents start in a (business-oriented) word processor. Semantically rich documents enable automation, reduce information loss, have better discovery and presentation. Unfortunately, users (and I think, authors) don’t really distinguish between metadata, semantics and data. Document and metadata creation are not really separable. Documents often have multiple, widely separated authors, particularly in the sciences. Their approach is to make it work with MS Word & OpenOffice Writer, & use Sefton’s ICE system. They need encodable semantics that are round-trip survivable: if created by a rich tool, then processed with a vanilla tool then checked again with the rich tool, the semantics should still be present, for real interoperability. Things they thought of but didn’t do: MS Word Smart Tags, MS Word foreign namespace XML, ODF embedded semantics, anything that breaks WYSIWYG such as wiki markup in document), new encoding standards. What does work? An approach based on microformats (I thought simply labelling it as microformats was a bit of an over-statement, given the apparent glacial pace of “official” microformat standardisation!). They will overload semantics into existing capabilities, eg tables, styles, links, frames, bookmarks, fields (some still fragile).

Paul McKeown from EMC Corp gave a paper written by Stephen Todd on XAM, a standard newly published by SNIA. It originated from the SNIA 100 year archive survey report. Separating logical and physical data formats, and the need over time to migrate content to new archives. Location-independent object naming (XUID), with rich metadata, and pluggable architecture for storage system support. Application tool talks to XAM layer which abstracts away the vendor implementations. 3 primary objects: XAM library (object factory?), XSet, XStreams, etc. Has a retention model. (Sorry Paul, Stephen, I guess I was getting tired at this point!)

Wilbanks on the Control Fallacy: How Radical Sharing out-competes

Closing the first day of the International Digital Curation Conference, and as a prelude to a substantial audience discussion, John Wilbanks from Science Commons outlined his vision and his group’s plans and achievements. His slides are available on Slideshare and from the IDCC web site.

John suggests that the only real alternative to radical sharing is inefficient sharing! Science (research and scholarship, to be more general) is in a way not unlike a giant Wikipedia, an ever-changing consensus machine, based on publishing (disclosing, making things public); advances by individual action, and by discrete edits (ie small changes to the body of research represented by individual research contributions). Unlike Wikipedia the Science consensus machine is slow and expensive, but it does have strong authentication and trust. It represents an “inefficient and expensive ecosystem of processes to peer-produce and review scholarly content”.

However, disruptive processes can’t be planned for, and when they occur, attract opposition from entrenched interests (open access is one such disruptive system). So a scholarly paper may be thought of as “an advertisement for years of scholarship” (I think he gave a reference but I can’t find it). International research forms a highly stable system, good at resisting change on multiple levels, and in many cases this is a Good Thing. This system includes Copyright (Wilbanks suggested IPR was an unpopular term, new to me but perhaps a US perspective); traditionally, in the analogue world, copyright locks up the container, not the facts. New publishing business models lock up even more rights on “rented” information. If we can deposit our own articles (estimated cost 40 minutes per researcher per year), then we can add further services over our own material (individually or collectively), including tracking use and re-use; then we can out-compete the non-sharers.

Science Commons has been working for the past 2 years focusing their efforts in both the particular (one research domain, building the Neurocommons) and the general; their approach requires sharing. They discovered two things quite early on: first that international rules on intellectual property in data vary so widely that building a general data licence to parallel the Creative Commons licences for text was near impossible, and second that viral licences (like the Creative Commons Share-Alike licences, and the GPL) act against sharing, since content under different viral licences cannot be mixed. So their plan is to try putting their data into the public domain as the most free approach. They use a protocol (not licence) for implementing open data. reward comes through trademark, badging as part of the same “tribe”. Enforcement doesn’t apply; community norms rule, as they do in other areas of scholarly publishing. For example attribution is a legal term of art (!!), but in scholarly publishing we prefer the use of citations to acknowledge sources, with the alternative for an author being possible accusations of plagiarism, rather than legal action (in most cases).

There was some more, on the specifics of their projects, on trying to get support in ‘omics areas for a semantic web of linked concepts, built around simple, freely alterable ontologies; how doing this will help Google Scholar rank papers better. Well worth a look at the slides (worth while anyway, since I may well have got some of this wrong!). But Wilbanks ended with a resounding rallying cry: Turn those locks into gears! Don’t wait, start now.

IPR and science data integration

Preparing for the JISC Innovation Forum, I have been reading John Wilbanks’ comment piece (Wilbanks, 2008) tracing the reasoning behind the Science Commons approach of abandoning Creative Commons-style licensing for integratable data, in favour of a dedication to the public domain plus codified community norms. To be honest, I was gob-smacked when this came about; it seemed that a desirable outcome (CC-like licensing for data) had been abandoned. However, Wilbanks makes a powerful argument, and as a non-lawyer (albeit someone who has been arguing about the existence and/or nature of any implied licence for web pages since 1995 or so), it seems to me a very convincing one.

It is a critical point that this is the approach of choice where the data are to be offered for integration with other data on the open web. So this approach would be sensible for most of the kinds of data we think of as forming part of the semantic web, for instance.

The arguments clearly do not apply, and are specifically not intended to apply, to all classes of science data or databases. For instance, many science data are collected under grants from funders who require conditions to be placed on subsequent use. Wilbanks analysis might suggest that some of these mandates are misguided, and this may be so, but some have very strong ethical and legal bases, particularly (but not only) research producing or using social science or medical data relating to individuals.

The UK Data Archive, for example, requires registration and agreement to an end user licence before access to any datasets. The standard licence, for example, requires me (my emphasis):

“2. To give access to the Data Collections, in whole or in part, or any material derived from the Data Collections, only to registered users who have received permission from the UK Data Archive to use the Data Collections, with the exception of Data Collections supplied for the stated purpose of teaching.”

And…

“5. To preserve at all times the confidentiality of information pertaining to identifiable individuals and/or households that are recorded in the Data Collections where the information contained in the Data Collections was created less than 100 years previously, or where such information is not in the public domain. In addition, where so requested, to preserve the confidentiality of information about, or supplied by, organisations recorded in the Data Collections. In particular I undertake not to use or attempt to use the Data Collections to deliberately compromise or otherwise infringe the confidentiality of individuals, households or organisations. Users are asked to note that, where Data Collections contain personal data, they are required to abide by the current Data Protection Act in their use of such data. “

UKDA are right to take a strong protectionist approach to most of these data (maybe the 1881 census data could get a more wide-ranging exclusion than that implied in the previous paragraph). Problems of cascading and non-inter-operable licence conditions may arise, but probably only on a small scale, and likely to be resolvable on the basis of negotiations, or through emerging facilities specifically aimed at providing access to potentially disclosive data.

Wilbanks recognises these problems:

“There will be significant amounts of data that is not or cannot be made available under this protocol. In such cases, it is desirable that the owner provides metadata (as data) under this protocol so that the existence of the non-open access data is discoverable.”

The UKDA metadata catalogue is both open and interoperates, so it does effectively apply this rule (although perhaps not yet to the letter).

Likewise, BADC distributes some data that it has acquired through NERC (funder) mandates (effectively their data policy, apparently under review), but also some data that it has acquired from sources such as the Met Office Hadley Centre, for whom it might have high commercial value. It's not surprising that some of these funders impose restrictions, although it would be good if they would look long and hard at the value question before doing so.

At the Forum legal session on data, there was a debate on the motion: “Curating and sharing research data is best done where the researcher’s institution asserts IPR claims over the data”. Prior to the speakers, a straw poll suggested that 5 were in favour, 10 against with 7 abstentions. After the debate, the motion was lost with 6 in favour, 14 against and 2 abstentions. What the debate most illuminated, perhaps, was the widespread distrust held for the whole apparatus: institutions, publishers, researchers, even curators… and in addition, we all probably shared a lack of clarity about the nature of data, the requirements of collaboration, the impacts of disciplinary norms, effective business models, etc, etc.

In practice, of course, curation is going to require a partnership of all the stakeholders identified above, and probably more!

WILBANKS, J. (2008) Public domain, copyright licenses and the freedom to integrate science. Journal of Science Communication, 7. http://jcom.sissa.it/

Semantic web on the Today programme

Turning on the radio this morning, I was surprised to hear someone discussing data on the Today programme on BBC Radio 4. It turned out to be Sir Tim Berners Lee talking about the semantic web; he even managed to mention RDF and HTML without confusing the interviewers too much. The interesting 8 and a half minute discussion is available via the BBC iPlayer.

I'm quite keen on understanding better how the semantic web might relate to science data. When people talk about data in relation to the semantic web, they often seem to be thinking the sort of relatively unitary facts or simple relationships that RDF triples are quite good at expressing, such as the population of China is 1,330,044,605. It's certainly not clear to me how this generalises to express the changing population, let alone how it could express the data from a spectrometer or
a crystal structure determination or remote-sensing data. If anyone can point me to a good resource discussing this, I would be grateful!

Research Repository System web orientation

This is one of a series of posts aiming to expand on the idea of the negative click, positive value repository, which I'm now calling a Research Repository System. I've suggested it should contain these elements:

• web orientation
• researcher identity management
• authoring support
• object disclosure control
• data management support
• persistent storage
• full preservation archive, and
• spinoffs
  

By web orientation, I mean that the RRS should be Web 2.0-like, being user-centred in that it knows who you are, and exploits that knowledge, and is very easy to use. It should be oriented towards sharing, but (as you’ll see) in a very controlled way; that is items should be sharable with varying groups of people from close colleagues, through unkown reviewers, to the general public. I think simple tagging rather than complex metadata should be supported. Maybe some kind of syndication/publishing support like RSS or Atom. The RSS should have elements with first class Semantic Web capabilities, supporting RDF. And because research and education environments are so very varied, and so highly tailored to individual circumstances (even if this is only based on the personal preferences of the PhD student who left a few years ago!), the RRS should be highly configurable, based on substitutable components, and able to integrate with any workflow.

Although the idea is linked in my mind to institutional or laboratory repositories, there are aspects that seem to me to require a service at above the institutional level (where researchers from different institutions work together, for example). It could be that some genuine Web 2.0 entrepreneurship might provide this!

Science publishing, workflow, PDF and Text Mining

… or, A Semantic Web for science?

It’s clear that the million or so scientific articles published each year contain lots of science. Most of that science is accessible to scientists in the relevant discipline. Some may be accessible to interested amateurs. Some may also be accessible (perhaps in a different sense) to robots that can extract science facts and data from articles, and record them in databases.

This latter activity is comparatively new, and (not surprisingly) hits some problems. Articles, like web pages, are designed for human consumption, and not for machine processing. We humans have read many like them; we know which parts are abstracts, which parts are text, which headings, which references. We can read the tables, find the intersections and think about what the data points mean. We can look at the graphs, the spectra etc, and relate them to the author’s arguments. Most of these tasks are hard for robots. But with a little bit of help and persistence, plus some added “understanding” of genre and even journal conventions, etc, robots can sometimes do a pretty good job.

However, most science articles are published in PDF. And PDF does not make the robot’s task easy; in fact, PDF often makes it very hard (not necessarily to be deliberately obscure, but perhaps as side-effects of the process leading to the PDF).

Peter Murray-Rust has been leading a number of one-man campaigns (actually they all involve many more than one man, but he is often the vocal point-person). One such campaign, based on attempts to robotically mine chemical literature can be summed up as “PDF is a hamburger, and we’re trying to turn it back into a cow” (the campaign is really about finding better semantic alternatives to PDF). I've referred to his arguments in the past, and we've been having a discussion about it over the past few days (see here, its comments, and here).

I have a lot of sympathy with this viewpoint, and it’s certainly true that PDF can be a hamburger. But since scientists and publishers (OK, mostly publishers) are not yet interested in abandoning PDF, which has several advantages to counter its problems, I’m also interested in whether and if so, how PDF could be improved to be more fit for the scientific purpose.

One way might be that PDF could be extended to allow for the incorporation of semantic information, in the same way that HTML web pages can be extended, eg through the use of microformats or RFDa, etc. If references to a gene could be tagged accordning to the Gene Ontology, references to chemicals tagged according to the agreed chemical names, InChis etc, then the data mining robots would have a much easier job. Maybe PDF already allows for this possibility?

PMR argues quite strongly that PDF is by design unfit for our purpose (in this case, holding scientific information such that it can reliably be extracted by text mining robots); that PDF's determined page-orientation and lack of structural and semantic significance doom such attempts to failure. He also argues strongly that the right current solution is to use XML… or perhaps XHTML for science writing.

I don’t know. He might be right. But being right is not necessarily going to persuade thousands of journal editors and hundreds of thousands of scientists to mend their ways and write/publish in XML.

I think we should tackle this in several ways:

• try to persuade publishers to publish their XML (often NLM XML) versions of articles as well as the PDFs
• try to persuade publishers who don’t have a XML format to release HTML versions as well as (or instead of PDFs)
• tackle more domain ontologies to get agreements on semantics
• work on microformats and related approaches to allow semantics to be silently encoded in documents
• try to persuade authors to use semantic authoring tools (where they exist), and publishers to accept these
• try to persuade Adobe to extend PDF to include semantic micro-metadata, and to help provide tools to incorporate it, and to extract it.

Might that work? Well, it’s a broad front and a lot of work, but it might work better than pursuing only one of them… But if we got even part way, we might really be on the way towards a semantic web for science...

Wouldn't it be nice...

... if we had some papers for the 4th International Digital Curation Conference in Edinburgh (dinner in the Castle, anyone?) next December, created in a completely open fashion by a group of people who have perhaps never met, using data that's publicly available, and where the data and data structures in the paper are tagged (semantic web???), attached as supplementary materials, or deposited so as to be publicly available.

No guarantees, folks, since the resulting paper has to get through the Programme Committee rather than just me. But it would have a wonderful feeling of symmetry...