A week late on posting this, catching up with Brian’s notes on the ILI 2013: Future Technologies and Their Applications Workshop workshop we ran last week, and his follow up – What Have You Noticed Recently? – inspired by not properly paying attention to what I had to say, here are few of my own reflections on what I heard myself saying at the event, along with additional (minor) comments around the set of ‘resource’ slides I’d prepped for the event, though I didn’t refer to many of them…
- slides 2-6 – some thoughts on getting your eye into some tech trends: OU Innovating Pedagogy reports (2012, 2013), possible data-sources and reports;
- slides 6-11 – what can we learn from Google Trends and related tools? A big thing: the importance of segmenting your stats; means are often meaningless. The Mothers’ Day example demonstrates two signal causes (in different territories – i.e. different segments) for the compound flowers trend. The Google Correlate example show how one signal may lead – or lag – another. So the question: do you segment your library data? Do you look for leading or lagging indicators?
- slides 12-18 – what role should/does/could the library play in developing the reputation of the organisation’s knowledge producers/knowledge outputs, not least as a way of making them more discoverable; this builds on the question of whose role it is to facilitate access to knowledge (along with the question: facilitate access for whom?)? – my take is this fits in the role librarians often take of organising an institution’s knowledge.
- slides 19-27 – what is a library for? Supporting discovery (of what, by whom)? (Helping others) organise knowledge, and gain access to information? Do research?
- slides 28-30 – the main focus of my own presentation during the main ILI2013 conference (I’ll post the slides/brief commentary in another post): if the information we want to discover is buried in data, who’s there to help us extract or discover the information from within the data?
- slides 31-32 – sometimes reframing your perception of an organisation’s offerings can help you rethink the proposition, and sometimes using an analogy helps you switch into that frame of mind. So if energy utilities provide “warm house” and “clean, dry clothes” service, rather than gas or electricity, what shift might libraries adopt?
- slides 33-39 – a few idle idea prompts around the question of just what is it that libraries do, what services do they provide?
- slide 40 – one of the items from this slide caused a nightmare tangent! The riff started with a trivial observation – a telling off I received for trying to use the phone on my camera to take a photo of a sign saying “no cameras in the library”, with a photocopier as a backdrop (original story). The purpose of this story was two-fold: 1) to get folk into the idea of spotting anachronisms or situations where one technology is acceptable where an equivalent or alternative is not (and then wonder why/what fun can be had around that thought;-); 2) to get folk into wondering how users might appropriate technology they have to hand to make their lives easier, even if it “goes against the rules”.
- slide 41 – a thought experiment that I still have high hopes for in the right workshop setting…! if you overheard someone answer a question you didn’t hear with the phrase “did you try the library?”, what might the question be? You can then also pivot the question to identify possible competitors; for example, if a sensible answer to the same question is “did you try Amazon?”, Amazon might be a competitor for the delivery of that service.
- slide 42 – this can lead on from the previous slide, either directly (replace “library” with “Amazon” or “Google”), or as way of generating ideas about how else a service might be delivered.
Slide not there – a riff on the question of: what did you notice for the first time today? This can be important for trend spotting – it may signify that something is becoming mainstream that you hadn’t appreciated before. To illustrate, I’ve started trying to capture the first time I spot tech in the wild with a photo, such as this one of an Amazon locker in a Co-Op in Cambridge, or a noticing from the first time I saw video screens on the Underground.
As with many idea generating techniques, things can be combined. For example, having introduced the notion of Amazon lockers, we might then ask: so what use might libraries make of such a system, or thing? Or if such things become commonplace, how might this affect or influence the expectations of our users??
I though this was handy on the OER-DISCUSS mailing list:
Our copyright officer writes:
… US Copyright ‘Fair Use’ or S29 copying for non-commercial research and private study which allows copying but the key word here is ‘private’. i.e. the provisos are that you don’t make the work or copies available to anyone else.
Although there are UK Exceptions for education, they are very limited or obsolete.
S.32 (1) and (2A) do have the proviso “is not done by reprographic process” which basically means that any copying by any mechanical means is excluded, i.e. you may only copy by hand.
S36 educational provision in law for reprographic copying is
a) only applicable to passages in published works i.e. books journals etc and
b) negated becauses licences are now available S.36 (3)
S.32 (2) permits only students studying courses in making Films or Film soundtracks to copy Film, broacasts or sound recordings.
The only educational exception students can rely on is s.32(3) for Examination athough this also is potentially restrictive. For the exception to apply, the work must count towards their final grade/award and any further dealing with the work after the examination process, becomes infringement.
I’m not sure how they are using Voicethread, but if the presentations are part of their assessed coursework and only available to students, staff and examiners on the course, they may use any Copyright protected content, provided it’s all removed from availability after the assessment (not sure how this works with cloud applications though)
There is also exception s.30 for Criticism or Review, which is a general exception for all, and the copying is necessary for a genuine critique or review of it.
If the students can’t rely on the last 3 exceptions, using Copyright free or licenced material (e.g. Creative Commons), would be highly recommended.
Kate Vasili – Copyright Officer, Middlesex University, Sheppard Library
One of the possible barriers to widespread adoption of open notebook science is knowing where to start. Video reports of lab experiments hosted on Youtube can be easily embedded in a hosted WordPress blog; a MediaWiki wiki can be used to provide one page per experiment, with change tracking/history on each page and a shadow page for commentary and discussion; Github can be used to provide a version control environment for software code, results data, project pages and documentation. For tabulated data, Google Spreadsheets provides a hosting environment and an API that lets you treat the data as a database and also explore it dashboard style via a range of interactive visual filtering and charting components. Alternatively, a CKAN instance (such as is used to run thedatahub.org) offers data management and preview tools.
Keeping track of data analysis in an open way is also getting easier. In An R-chitecture for Reproducible Research/Reporting/Data Journalism, I briefly mentioned RPubs.com, a site that can be used to 1-click publish HTML reports of statistical analyses executed within the RStudio environment (I really need to do a proper post about this). But now there’s an example of another hosted solution from Fridolin Wild of the OU’s KMi: Crunch.
Crunch offers a hosted RStudio environment (so you can access RStudio via a browser) with public and private areas. The public areas allow you to post datasets, run scripts as a service, or publish results (Sweave generated PDFs, or knitr generated HTML reports, for example).
Crunch also incorporates a MySQL database for each user. (Scheduling and pipelining are also on the cards…)
Whilst developed as an application to support learning analytics (I think?), Crunch also provides a great demonstration of a more general open research data workbench. You can store – and publish – data sets, along with analysis scripts and reports generated by executing those scripts over your data set. Version control isn’t available at the moment (I think?) but RSTudio does have git/github support, so that may be coming. The provision of a MySql database means that data collections can be managed within a database environment. (From a data journalism, rather than an open/reproducible research, perspective, I did wonder whether it would be possible to situate something like Scraperwiki on the same platform and replace its SQLite support with MySQL support, so a Scraperwiki scraper could be used to scrape data into a MySQL database that was then accessed from RStudio? Being able to wire MySQL read/write access into Google Refine on the same platform could also be interesting..;-)
I’m not sure about the extent to which the OU LIbrary is taking an interest in the development of Crunch, but providing best practice support and advice in the orchestration of information and data handling tools seems to me to be in-scope for the academic research librarian, in much the same way as advising on the use of bibliography data management tools used to be…? (For a recent take on this, see Dorothea Salo’s recent Ariadne article Retooling Libraries for the Data Challenge.)
I had the honour of being invited to talk at the JIBS User Group 20 Anniversary AGM yesterday, and as well as having a bit of a rant in the closing plenary about opening up and making internal reuse of data and making FOI requests about SCONUL data*, I also gave this sideways take on Ranganathan’s Five Laws of Library Science for the current age (The Frictionless Library).
Amongst other things, the presentation sketches a possible project (that I think could make for a good workshop day) revisiting each of the laws in network context using the various techniques of constitutional interpretation and (briefly) revisits at least one of the notions of the Invisible Library (see also The Invisible Library (ILI, 2009), another meaningless set of slides…;-)
* Note to self: read up about the current HESA HE Information Landscape Project (Redesigning the higher education data and information landscape). Also check out the “KB+” JISC project (programme?) that will “develo[p] a shared community service that will improve the quality, accuracy, coverage and availability of data for the management, selection, licensing, negotiation, review and access of electronic resources for UK HE” (via @benshowers) and the Talis Aspire Community Edition (aggregated reading lists across several HEIs).
PS I’m working out how to make the slides a little bit more useful as a post hoc/legacy resource by posting them with a bit a context and commentary… But it may take a bit of time…
PPS on the way home, I listened to this Long Now Foundation seminar by Brewster Kahle on Universal Access to All Knowledge, which got me wondering about the extent to which University libraries are depositing resources into the Internet Archive..? There’s a nice piece at the end that makes the point that IPR is such that in terms of the digital record, there’s likely to be a gap in the timeline of archived content right around the 20th century…
PPPS as far as library futures go, here’s a loosely related Roadmapping TEL activity on “Ideas that influence the future of technology enhanced learning” that is currently running on Ideascale.
There were also several discussions during the day relating to information skills needs for 21st century librarians. Some of the ANCIL reports from the Arcadia project on a new information literacy curriculum may be of interest to JIBS members in this regard, I think? Arcadia Project Report
I think there’s a real need for librarians to help folk make sense of the wealth of data out there, and this in part requires a good understanding of network structures and organisations, not just a concentration on hierarchical models.
Hear (sic) also, for example, OU Vice Chancellor Martin Bean on ‘sensemaking’ and the role of the library from his 2010 ALT-C Keynote:
I think it’s also time to start seeing people as information and knowledge resources, as well as just texts…
If you live by pop tech feed or Twitter, you’ve probably heard that Google is rolling out a new style of socially powered search results. If not, or if you’re still not clear about what it entails, read Phil Bradley’s post on the matter: Why Google Search Plus is a disaster for search.
Done that? If not, why not? This post isn’t likely to make much sense at all if you don’t know the context. Here’s the link again: Why Google Search Plus is a disaster for search
So the starting point for this post is this: Google is in the process of rolling out a new web search service that (optionally) offers very personal search results that contains content from folk that Google thinks you’re associated with, and that Google is willing to show you based on license agreements and corporate politics.
Think about this for a minute…. in e the totally personalised view, folk will only see content that their friends have published or otherwise shared…
In Could Librarians Be Influential Friends?, I wondered aloud whether it made sense for librarians and other folk involved with providing support relating to resource discovery and recommendation to start a) creating social network profiles and encouraging their patrons to friend them, and b) start recommending resources using those profiles in order to start influencing the ordering/ranking of results in patrons’ search results based on those personal recommendations. The idea here was that you could start to make
invisible frictionless recommendations by influencing the search engine results returned to your patrons (the results aren’t invisible because your profile picture may appear by the result showing that you recommend it. They’re frictionless in the sense that having made the original recommendation, you no longer have to do any work in trying to bring it to the attention of your patron – the search engines take care of that for you (okay, I know that’s a simplistic view;-). [Hmm.. how about referring to it as recommendation mode support?]
(Note that there is an complementary form of support to the approach which I’ve previously referred to as Invisible Library Tech Support (responsive mode support?; which I guess is also frictionless, at least from the perspective of the patron) in which librarians friend their patrons or monitor generic search terms/tags on Q&A sites and then proactively respond to requests that users post into their social networks more generally.)
With the aggressive stance Google now seems to be taking towards pushing social circle powered results, I think we need to face up to the fact – as Phil Bradley pointed out – that if librarians want to make sure they’re heard by their patrons, they’re going to need to start setting up social profiles, getting their patrons to friend them, and start making content and resource recommendations just anyway in order to make them available as resources that are indexed by patrons’ personal search engines. The same goes for publishers of OERs, academic teaching staff, and “courses”.
If we think of Google social search as searching over custom search engines bound by resources created and recommended by members of a users social circle, if you want to make (invisible) recommendations to a user via their (personalised) web search results, you’re going to need to make sure that the resources/content you want to recommend is indexed by their personal search engines. Which means: a) you need to friend them; and b) you need to share that content/those resources in that social context.
(Hmmm…this makes me think there may be something in the course custom search engine approach after all… Specifically, if the course has a social profile, and recommends the links contained within the course via that profile, they become part of the personalised search index of student’s following that course profile?)
Just by the by, as another example of Google completely messing things up at the moment, I notice that when I share links to posts on this blog via Google+, they don’t appear as trackbacks to the post in question. Which means that if someone refers to a post on this blog on Google+, I don’t know about it… whereas if they blog the link, I do…
See also my chronologically ordered posts on the eroding notion of “Google Ground Truth”.
[Invisible vs frictionless (and various notions of that word) is all getting a bit garbled; see eg @briankelly’s Should Higher Education Welcome Frictionless Sharing and my comments to it for a little more on this…]
PS I’ve been getting increasingly infuriated by the clutter around, and lack of variation within, Google search results lately, so I changed my default search engine to Bing. The results are a bit all over the place compared to the Google results I tend to get, but this may be down in part to personalisation/training. I am still making occasional forays to Google, but for now, Bing is it… (because Bing is not Google…)
PPS Hah – just noticed: Google Search Plus doesn’t mean plus in the sense of search more, it means search Google+, which is less, or minus the wider world view…;-)
PPPS I keep meaning to blog this, and keep forgetting: Turn[ing] off [Google] search history personalization, in particular: “If you’ve disabled signed-out search history personalization, you’ll need to disable it again after clearing your browser cookies. Clearing your Google cookie clears your search settings, thereby turning history-based customizations back on.” WHich is to say, when you disable personalisation, you don’t disable personalisation against your Google account, you disable it only insofar as it relates to your current cookie ID?
Picking up on a query I raised in Citation Positioning, here’s a quick summary of an online discussion featuring variously @edsu, @epoz, @ostephens and myself (I’m the one who knows absolutely nothing…!)
The context is: can I use the OAI-PMH interface on Citeseer to grab record level machine readable results from Citeseer. Note that I donlt really want to harvest all the Citeseer data, pop it into a database of my own, and then run queries on that; I just want a quick and dirty API to make a handful of calls to particular queries for a proof of concept hack;-)
Here’s what the Citeseer HTML page looks like:
It has a URL of the form: http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.122.728
The tabbed results pages have their own URLs:
– Active Bibliography, of the form http://citeseer.ist.psu.edu/viewdoc/similar?doi=10.1.1.122.7284&type=ab
– Co-Citation, of the form http://citeseer.ist.psu.edu/viewdoc/similar?doi=10.1.1.122.7284&type=cc
– Clustered Documents, of the form http://citeseer.ist.psu.edu/viewdoc/similar?doi=10.1.1.122.7284&type=sc
Here’s what I’m guessing:
– the ‘front page’ results are links to papers that reference/cite the target article, ordered by the number of times that they themselves have been cited; this is a subset of the total set of papes that cite the target article;
– the Active Bibliography is a subset of the articles that are referenced from/cited by the target article that have themselves been recently cited elsewhere (?! I’m guessing – the Citeseer site doesn’t seem to provide an explanation anywhere?)
– the co-citations are… I have no idea? Other papers that have been cited by papers that cite the target paper?
– Clustered Documents – these seem to be other Citeseer records relating to the same paper; do they all have the same citation info? I have no idea?????
As far as the OAI interface goes, it seems we can grab an individual record using a query of the form:
which returns a result of the form:
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"> <responseDate>2011-12-08T16:24:31+00:00</responseDate> <request identifier="oai:CiteSeerX.psu:10.1.1.122.7284" metadataPrefix="oai_dc" verb="GetRecord">http://citeseerx.ist.psu.edu/oai2</request> <GetRecord> <record> <header> <identifier>oai:CiteSeerX.psu:10.1.1.122.7284</identifier> <datestamp>2009-05-28</datestamp> </header> <metadata> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:title>The structure and function of complex networks</dc:title> <dc:creator>M. E. J. Newman</dc:creator> <dc:description> Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks. </dc:description> <dc:contributor> The Pennsylvania State University CiteSeerX Archives </dc:contributor> <dc:publisher/> <dc:date>2009-05-28</dc:date> <dc:date>2008-12-04</dc:date> <dc:date>2003</dc:date> <dc:format>application/pdf</dc:format> <dc:type>text</dc:type> <dc:identifier> http://citeseerx.ist.psu.edu/citeseerx/viewdoc/summary?doi=10.1.1.122.7284 </dc:identifier> <dc:source> http://www.cs.berkeley.edu/~christos/classics/graphsurvey.pdf </dc:source> <dc:language>en</dc:language> <dc:relation>10.1.1.109.4049</dc:relation> <dc:relation>10.1.1.120.3875</dc:relation> <dc:relation>10.1.1.31.1768</dc:relation> <dc:relation>10.1.1.153.5943</dc:relation> <dc:relation>10.1.1.37.234</dc:relation> <dc:relation>10.1.1.18.2720</dc:relation> <dc:relation>10.1.1.30.6583</dc:relation> <dc:relation>10.1.1.25.5619</dc:relation> <dc:relation>10.1.1.104.3739</dc:relation> <dc:relation>10.1.1.56.6742</dc:relation> <dc:relation>10.1.1.117.7097</dc:relation> <dc:relation>10.1.1.15.8793</dc:relation> <dc:relation>10.1.1.33.1635</dc:relation> <dc:relation>10.1.1.139.1580</dc:relation> <dc:relation>10.1.1.30.9552</dc:relation> <dc:relation>10.1.1.184.8874</dc:relation> <dc:relation>10.1.1.24.6195</dc:relation> <dc:relation>10.1.1.16.478</dc:relation> <dc:relation>10.1.1.31.3763</dc:relation> <dc:relation>10.1.1.25.7011</dc:relation> <dc:relation>10.1.1.37.5917</dc:relation> <dc:relation>10.1.1.84.9512</dc:relation> <dc:relation>10.1.1.7.1950</dc:relation> <dc:relation>10.1.1.129.6877</dc:relation> <dc:relation>10.1.1.25.1360</dc:relation> <dc:relation>10.1.1.16.1168</dc:relation> <dc:relation>10.1.1.115.8316</dc:relation> <dc:relation>10.1.1.143.1502</dc:relation> <dc:relation>10.1.1.130.1956</dc:relation> <dc:relation>10.1.1.20.814</dc:relation> <dc:relation>10.1.1.21.838</dc:relation> <dc:relation>10.1.1.16.2407</dc:relation> <dc:relation>10.1.1.23.9684</dc:relation> <dc:relation>10.1.1.62.7557</dc:relation> <dc:relation>10.1.1.16.6906</dc:relation> <dc:relation>10.1.1.2.4033</dc:relation> <dc:relation>10.1.1.43.7796</dc:relation> <dc:relation>10.1.1.25.1174</dc:relation> <dc:relation>10.1.1.10.4509</dc:relation> <dc:relation>10.1.1.27.3417</dc:relation> <dc:relation>10.1.1.120.9902</dc:relation> <dc:relation>10.1.1.20.5323</dc:relation> <dc:relation>10.1.1.86.8584</dc:relation> <dc:relation>10.1.1.3.3888</dc:relation> <dc:relation>10.1.1.1.9569</dc:relation> <dc:relation>10.1.1.78.4413</dc:relation> <dc:relation>10.1.1.142.7059</dc:relation> <dc:relation>10.1.1.161.114</dc:relation> <dc:relation>10.1.1.143.1242</dc:relation> <dc:relation>10.1.1.58.2706</dc:relation> <dc:relation>10.1.1.35.8293</dc:relation> <dc:relation>10.1.1.85.7061</dc:relation> <dc:relation>10.1.1.129.709</dc:relation> <dc:relation>10.1.1.16.5260</dc:relation> <dc:relation>10.1.1.7.4603</dc:relation> <dc:relation>10.1.1.37.2417</dc:relation> <dc:relation>10.1.1.37.2641</dc:relation> <dc:relation>10.1.1.117.3665</dc:relation> <dc:relation>10.1.1.122.6034</dc:relation> <dc:relation>10.1.1.11.7594</dc:relation> <dc:relation>10.1.1.20.9298</dc:relation> <dc:relation>10.1.1.27.4715</dc:relation> <dc:relation>10.1.1.94.2340</dc:relation> <dc:relation>10.1.1.196.2257</dc:relation> <dc:relation>10.1.1.1.2728</dc:relation> <dc:relation>10.1.1.58.3869</dc:relation> <dc:relation>10.1.1.33.6972</dc:relation> <dc:relation>10.1.1.35.4242</dc:relation> <dc:relation>10.1.1.28.9399</dc:relation> <dc:relation>10.1.1.12.2717</dc:relation> <dc:relation>10.1.1.6.61</dc:relation> <dc:relation>10.1.1.7.6756</dc:relation> <dc:relation>10.1.1.15.4857</dc:relation> <dc:relation>10.1.1.58.2087</dc:relation> <dc:relation>10.1.1.10.352</dc:relation> <dc:relation>10.1.1.110.6845</dc:relation> <dc:rights> Metadata may be used without restrictions as long as the oai identifier remains attached to it. </dc:rights> </oai_dc:dc> </metadata> </record> </GetRecord> </OAI-PMH>
I’m guessing the dc:relation elements refer to the papers listed on the ‘front page’ of the results for a given paper, that is, they are the most heavily cited papers that cite the target paper?
So a few questions that arise:
– what do the different results listings on the HTML pages actually refer to?
– what do the results in the OAI query above relate to?
– is it possible to get a list of all the papers cited/referenced by a target article? (Or failing that, is it possible to get hold of the Active Bibliography relations, which are presumably a subset of the complete set of bibliographic references contained within a paper?)
– is it possible to get a list of all the paper that cite/reference a particular target article?
If you can answer any or all of the above questions, please feel free to post the answer(s) in a comment below…:-)
A couple of months ago, when I started looking at the idea of emergent social positioning in online social networks, I was focussing on trying to model the positioning of certain brands and companies, in part with a view to trying to identify ones that were associated with innovation, or future thinking in some way.
Based on absolutely no evidence at all, I surmised that one useful signal in this regard might be the context in which companies or brands are mentioned in popular, MBA-related business books, the sort of thing that Harvard Business Review publish, for example.
Here’s how my thinking went then:
– generate a bipartite network graph that connects the book’s index terms with page numbers of the pages they appear on based on the index entries* in a given book. A bipartite graph is one that contains two sorts or classes of node (in this case, index term nodes and book page number nodes). The index terms are likely to include companies, brands, people and ideas/concepts. Sometimes, particular index terms may be identified as companies, names, etc, through presentational mark up – a bold font, or italics, for example. These presentational conventions can often be mapped onto semantic equivalents. Terms might also be passed through something like the Reuters’ Open Calais service, or TSO’s Data Enrichment Service.
– collapse the network graph by generating links between things that are connected to the same page number and remove the page number nodes from the graph. You now have a graph that connects brands, people and other index terms with each other, where edges represent the relation “is on the same page in the same book as”. If companies and other index terms appear on several pages together, we might reflect this by increasing the weight of the edge that connects them, for example by using edge weight to represent the number of pages where the two terms co-exist.
(*This will be obvious to some, but not to others. To a certain extent, a book index provides a faceted/search term limited search engine interface to a book, that returns certain pages as results to particular queries…)
Note that we can generate a network for a specific book, in which case we can render a graphical summary of the content, relations within and structure of that book, or we can generate more comprehensive networks that summarise the index term relations across several books.
My thinking then was that if we can grab the indexes of a set of business books, we could map which companies and brands were being associated either with each other or with particular concepts in MBA land.
Which is where the problem lays – because I haven’t found anywhere where I can readily get hold of the indexes of business books in a sensible machine readable format. Given an electronic cpy of a book, I guess I could run some text processing algorithms over it looking for word pairs in close association with each other and generating my own view over the book. But the reason for using an actual book index is at least twofold: firstly, because there has presumably been a a quality process that determines what terms are entered into the index; secondly, because the index, if used by a human reader, will be influencing which parts of the book (and hence which related terms) they will be exposed to.
(It’s maybe also worth noting that books also contain a lot of other structured metadata – tables of contents, lists of figures, titles, headings, subheadings, emphasis, lists, captions, and so on, all of which provide cues as to how the book is structured and how ideas and entities contained within it relate to each other.)
As to why I’m posting this now? I first floated this idea with @edchamberlain following a JISC bibliography data event, and he reminded me of it at the Arcadia Project review a couple of days ago ;-)
Related, sort of: Augmenting OU/BBC Co-Pro Programme Data With Semantic Tags, which looked at mapping corporate mentions in the BBC/OU co-pro business programme The Bottom Line:
Also Citation Positioning.
PS this is clever – and related – via @ostephens: http://www.eatyourbooks.com/ (“‘Tell us which books you own’ We have indexed the most popular cookbooks & magazines so recipes become instantly searchable.”).