Implementing ideas from the semantic web makes the discovery, reuse and more importantly, curation of digital resources easier

Ben O'Steen

Implementing ideas from the semantic web makes the discovery, reuse and more importantly, curation of digital resources easier.Please note that this article is distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/2.0/uk/

O'Steen, Benjamin

Oxford University Research Archive (ORA)

Cherry-picking the semantic web

ORA - Oxford University Research Archive

Oxford University Research Archive

Cherry-picking the semantic webImplementing ideas from the semantic web makes the discovery, reuse and more importantly, curation of digital resources easier.Libraries and institutions have long realised that to make their resources as accessible and as relevant as possible, the resources need to be put on the web and in as free a form as possible. Researchers can go online with minimal technical know-how and they are able to find information they may not have found otherwise. However, enabling this is not as trivial as it might seem to the user - it requires massive amounts of computing power and engineering. Users take advantage of powerful supercomputers every day, often without realising it - massive computing clusters are put to task, reading and cataloguing all the web pages that can be found, thereby powering the search engines we all use. Large teams of highly skilled people are employed to write the code which controls how the information is catalogued and how this catalogue is then searched.Yet, with all the time, money and sheer individual effort spent on search engine technology, how often does the first hit match exactly what we are looking for? How many useless pages do we have to look through before we find something relevant? Why are we in this position in the first place?"Garbage in, Garbage out". The majority of websites are written with only human readers in mind and this tends to cause a lot of the contextual information on the page to be unreadable - "garbage" - to a web crawler. Whilst natural language-processing and other related algorithms can extract some form of meaning from the text, these approaches are based around the idea of 'recovering' the information, rather than 'reading' it. The distinction between recovering and reading parallels the distinction between code-breaking and reading the code with a key; A code-breaker may eventually break the code, but it is far easier for the message to be readable in the first place.Unlike mathematically-based codes, languages keep evolving and changing and are contextual; a phrase's meaning can depend on who is 'saying' it, to whom and when. A successful method that 'breaks the code' for one piece of text, may not work well on a second text. If the recovered information's accuracy cannot be trusted, this affects every service that might re-use it.Linked Data or lack of itThere is an issue with the way that information on the internet is interconnected, or rather, the way it really isn't connected in a way that we can make sense of. The basic, crude and vague link mechanism is used everywhere, but it can be very hard indeed to qualify what this link means; A link on a webpage can be used to cite a work, to reference data, to criticize, to agree with or disagree with, to refute or support, to convey a emotion, or simply to point to a funny picture of a cat.In my opinion at least, the easiest way to improve both the accuracy and the relevance of search engines is for content providers to represent knowledge in a global way, knowledge such as a description of a resource and also how that resource interrelates to other resources on a global scale. Even a cursory glance at what the semantic web is all about should indicate that it and the standards around it are a tight match to what we seem to need.The idea of making the pages of a site machine-readable - that is, making the information presented to a human reader similarly understandable by a machine - is not a new one, but is rarely implemented as a priority.The Oxford University Research Archive has a remit to store, preserve and - if copyright and/or IPR are not issues - to disseminate the research publications and other research output produced by members of the University of Oxford. Content includes copies of journal articles, conference papers, theses and other types of research publications.As the lead developer on this project, I feel a strong responsibility to make sure that the work is as discoverable and as re-useable as possible. The quote that I often think of is that "the coolest thing that will be done with your data, will be thought of by someone else."​[1]​ Data on the scale of the web is really only going to be manipulated by computer agents, and so it follows that to provide discoverable and re-useable content, the archive's interface will have to be machine-readable.Oxford University's Research Archive - making the archive machine-readableThe archive's architecture has been consciously designed so that the open access research can be re-used and easily found, and a good deal of how this is done is through semantic web concepts and technologies.The developmental approach we have taken is that of a gradual adoption of useful semantic concepts rather than trying to do everything at once. We believe that these ideas will make the content easier to find and curate. It is not necessary to adopt every semantic web standard at once - it is possible to cherry-pick the most useful parts and techniques and implement those first.The most important thing to realise was that the research material and the information about that material can be modelled by linking one 'thing' to another. 'Things' include authors, editors, departments, grants, the research itself, and so on - the 'metadata' of a work, as well as the work itself. The way in which this modelling can be captured is through the Resource Description Framework (RDF) standard.RDF is machine-readable, and uses "vocabularies" of nouns and verbs that are intended to be globally accessible. (These vocabularies are better known as ontologies.) With it, the archive is able to express ideas such as 'This person is an author, and they have authored this work and co-edited works x,y and z. Work z is a derivative of work y."By making these simple ideas both human- and machine-readable, we have found that it has some very beneficial knock-on effects:•	Treating people, departments and so on as things in their own right, it becomes much easier to adopt the idea of distributed authorities of information; this puts the control back in the hands of the people, subject specialists and departments and will lead to a more efficient way to maintain these lists.•	Taxonomies described using an RDF ontology called SKOS are very readily reuseable and more precise than simple text phrases - the cataloguing scheme is bound to the subject, rather than having to be qualified elsewhere.•	The internal structure of each digital object in the archive is exposed as an RDF document makes backups and other preservation activities very much easier - this description has been proved sufficient to migrate content from one repository to another, without loss of contextual information and without needing access to the internal systems of either.•	Linking the key players together in this way makes it easy to explore the connections between them - the mapping between subject taxonomies can be exploited to find works which may use different wordings (or languages even) in describing their topics, but are about the same thing.•	Information can be repurposed - portals and web interfaces become just views on the set of data - the emphasis on people means that a 'social' networking tool is just as possible as a departmental listing of research using the same data.The use of semantic ideas and technology, while they break away from traditional methods, they enable so much benefit in terms of enhancing discovery, re-usability and also curation, that to not look at what the semantic web can do for you may be a very bad move indeed.This article is due to be published in Talis Nodalities magazine (http://www.talis.com/nodalities/ (​http:​\/​​\/​www.talis.com​\/​nodalities​\/​​)) Creative Commons Attribution licence applies http://creativecommons.org/licenses/by/2.0/uk/ (​http:​\/​​\/​creativecommons.org​\/​licenses​\/​by​\/​2.0​\/​uk​\/​​) Ben O’SteenUniversity of OxfordJune 2008^1	  CRIG http://www.ukoln.ac.uk/repositories/digirep/index/CRIG

Cherry-picking the semantic web

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