Scholarly HTML would be nice, but...

I'm quite interested in the idea of Scholarly HTML, as espoused in Pete Sefton's blog, and I've commented on some of Peter Murray Rust's hamburger PDF comments previously (although I do think a lot of people confuse wild PDF with well-made, should one say Scholarly PDF). I've always been slightly worried by one thing though.

A well-known advantage of PDF is that it pretty much assures I can save a document, share it, move it around etc and it will still be intact and readable. That's one of the reasons it's so popular.

Mostly we don't do that with HTML. Mostly we just point to it. But if I see an article these days, I want it on my computer if I'm allowed; this let's me study it at leisure, drop it in my Mendeley system, etc. As pointed out, that works a treat with PDF, and pretty well with Word or OpenOffice documents as well. This applies even where the document is quite heavily compound, with many embedded images, tables etc.

But if I try saving a HTML document to my hard disk, nothing very standard happens. OK, if I use Safari on my Mac, I get a .webarchive file, which is quite nice as I can do all the things with it that I could do with a PDF and Word etc, and when I open it later it will be as it was before, with all the images in place. But neither IE nor Firefox seem capable of opening a .webarchive file.

If I try saving the same article from Firefox, I get a .html file with the main article in it, and a directory with associated files in it (eg images). Safari does seem capable of opening this combination, but it's pretty ugly, and hard to move around. I haven't tried IE as I don't have easy access to it.

Is there in existence or development a standard approach to packaging the HTML and associated files that would be as convenient as the .webarchive, but usable across all browsers? If so, Scholarly HTML would be that little bit closer!

Semantically richer PDF?

PDF is very important for the academic world, being the document format of choice for most journal publishers. Not everyone is happy about that, partly because reading page-oriented PDF documents on screen (especially that expletive-deleted double-column layout) can be a nightmare, but also because PDF documents can be a bit of a semantic desert. Yes, you can include links in modern PDFs, and yes, you can include some document or section metadata. But tagging the human-readable text with machine-readable elements remains difficult.

In XHTML there are various ways to do this, including microformats (see Wikipedia). For example, you can use the hcard microformat to encode identifying contact information about a person (confusingly hcard is based on the vcard standard). However, there are relatively few microformats agreed. For example, last time I checked, development of the hcite microformat for encoding citations appeared to be progressing rather slowly, and still some way from agreement.

The alternative, more general approach seems to be to use RDF; this is potentially much more useful for the wide range of vocabularies needed in scholarly documents. RDFa is a mechanism for including RDF in XHTML documents (W3C, 2008).

RDF has advantages in that it is semantically rich, precise, susceptible to reasoning, but syntax-free (or perhaps, realisable with a range of notations, cf N3 vs RDFa vs RDF/XML). With RDF you can distinguish “He” (the chemical element) from “he” (the pronoun), and associate the former with its standard identifier, chemical properties etc. For the citation example, the CLADDIER project made suggestions and gave examples, for example of encoding a citation in RDF (Matthews, Portwin, Jones, & Lawrence, 2007).

PDF can include XMP metadata, which is XML-encoded and based on RDF (Adobe, 2005). Job done? Unfortunately not yet, as far as I can see. XMP applies to metadata at the document or major component level. I don’t think it can easily apply to fine-grained elements of the text in the way I’ve been suggesting (in fact the specification says “In general, XMP is not designed to be used with very fine-grained subcomponents, such as words or characters”). Nevertheless, it does show that Adobe is sympathetic towards RDF.

Can we add RDF tagging associated with arbitrary strings in a PDF document in any other ways? It looks like the right place would be in PDF annotations; this is where links are encoded, along with other options like text callouts. I wonder if it is possible simply to insert some arbitrary RDF in a text annotation? This could look pretty ugly, but I think annotations can be set as hidden, and there may be an alternate text representation possible. It might be possible to devise an appropriate convention for a RDF annotation, or use the extensions/plugin mechanism that PDF allows. A disadvantage of this is that PDF/A (ISO, 2005) disallows extensions to PDF as defined in PDF Reference (Adobe, 2007), but PDF/A is important for long-term archiving (ie that such extensions are not compatible with long-term archiving). I don’t know whether we could persuade Adobe to add this to a later version of the standard. If something like this became useful and successful, time would be on our side!

What RDF syntax or notation should be used? To be honest, I have no idea; I would assume that something compatible with what’s used in XMP would be appropriate; at least the tools that create the PDF should be capable of handling it. However, this is less help in deciding than one might expect, as the XMP specification says “Any valid RDF shorthand may be used”. Nevertheless, in XMP RDF is embedded in XML, which would make both RDF/XML and RDFa possibilities.

So, we have a potential place to encode RDF, now we need a way to get it into the PDF, and then ways to process it when the PDF is read by tools rather than humans (ie text mining tools). In Chemistry, there are beginning to be options for the encoding. We assume that people do NOT author in PDF; they write using Word or OpenOffice (or perhaps LaTeX, but that’s another story).

Of relevance here is the ICE-TheOREM work between Peter Murray-Rust’s group at Cambridge, and Pete Sefton’s group at USQ; this approach is based on either MS Word or OpenOffice for the authors (of theses, in that particular project), and produces XHTML or PDF, so it looks like a good place to start. Peter MR is also beginning to talk about the Chem4Word project they have had with Microsoft, “an Add-In for Word2007 which provides semantic and ontological authoring for chemistry”. And the ChemSpider folk have ChemMantis, a “document markup system for Chemistry-related documents”. In each of these cases, the authors must have some method of indicating their semantic intentions, but in each case, that is the point of the tools. So there’s at least one field where some base semantic generation tools exist that could be extended.

PDFBox seems to be a common tool for processing PDFs once created; I know too little about it to know if it could easily be extended to handle RDF embedded in this way.

So I have two questions. First, is this bonkers? I’ve had some wrong ideas in this area before (eg I thought for a while that Tagged PDF might be a way to achieve this). My second question is: anyone interested in a rapid innovation project under the current JISC call, to prototype RDF in PDF files via annotations?

References:

Adobe. (2005). XMP Specification. San Jose.
Adobe. (2007). PDF Reference and related Documentation.
ISO. (2005). ISO 19005-1:2005 Document management — Electronic document file format for long-term preservation — Part 1: Use of PDF 1.4 (PDF/A-1).
Matthews, B., Portwin, K., Jones, C., & Lawrence, B. (2007). CLADDIER Project Report III: Recommendations for Data/Publication Linkage: STFC, Rutherford Appleton Laboratory.
W3C. (2008). RDFa Primer: Bridging the Human and Data Webs. Retrieved 6 April, 2009, from http://www.w3.org/TR/xhtml-rdfa-primer/

Survey on malformed PDFs?

A DCC-Associates member asks

"Does anyone know there has been a study to estimate how many PDF documents
do not comply with the PDF standards?"

I've not heard of anything, nor can I find one with my best Google searches, but it's a particularly hard question to ask Google! So, if you know of anything that has happened or is in progress, please leave a comment here. Thanks,

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...