Judging from the discussion afterwards and some reactions on twitter, this was very much welcomed by the audience, especially as an encouragement for members of other universities to get on board the linked data train. I also demoed our latest prototype: DiscOU. It is a “discovery engine” for open educational resources which, in the current demo, can find them from BBC programmes (including iPlayer). We are actually pretty excited about this as it not only applies linked data as well as semantic search techniques to make itself more meaningful and customisable than other recommender tools, but also because it opens the way for a lot of potentially great applications, such as finding open educational resources relevant to museum exhibitions or to courses in other universities.

Now, even more interesting from this presentation and the discussions that followed was the new projects, going beyond Linked Data at the Open University. Linked Universities for example is growing pretty strong, with more datasets, vocabularies and tools being added on a regular basis, and more people getting in touch to discuss the application of linked data in their institution. We also just kicked off a new project, an EU support action called LinkedUp, that is all about web data from across various origins used to create new, innovative educational services. Finally, I’m getting involved in the development of Marimba, a tool developed in Madrid originally for the Spanish National Library to extract linked data from MARC-based library catalogues using customised mappings. We are now working on providing this tool to other universities, including university libraries.

Anybody how would monitor the job vacancies page on the KMi website can see that there are very exciting news coming up: we are hiring a whole team to take care of different aspects of Linked Open Data, at the Open University and beyond. This is exciting because it means that we are given the opportunity to make linked data a core part of the university’s information infrastructure, and through this, to offer to three talented people the chance to shape the way the higher education sector share, reuse and connect open data for the benefits of both teachers and learners. It is exciting also because each of these jobs include both a strong innovative component (working with state-of-the-art technologies and developing applications never seen before) and a direct relationship with the community of users of these technologies, whether it is researchers at the OU, the entire university or even a whole network of universities worldwide.

I describe the jobs quickly below with the links to the complete job descriptions and information about the way to apply. Please contact me if you have any question, or if you just want to discuss the jobs (using email, twitter, comments, or whatever other means…)

Project Officer – Linked Data (1 year)

This is a grade 7 job (for those of you who know what that mean) which basically is about becoming the Linked Data Specialist/Expert/Champion at the Open University. The core of the work here is basically to take care of data.open.ac.uk: ensure that it works and is maintained, keep the data up-to-date with changes in the original sources, identify new sources of data and integrate them, demonstrate and build the practices of Linked Data within the University, especially through dedicated applications. We are therefore expecting candidates to have good technological background (with the ability to develop using languages such as Java, PHP, Javascript) and good communication skills. Naturally, an interest in linked (open) data is strongly recommended.

The deadline for applying is the 19th September 2012. See the vacancy page for details.

Project Officer – REF Publications Linked Data (1 year)

This is also a grade 7 job. One of the most significant areas of application of Linked Data at the Open University (and, I believe, the academic sector in general) is for the management of research communities and research outputs. This job concerns one of such applications, which is especially dedicated to supporting the Research Excellence Framework for evaluating the quality of research realised in the university. This application makes use of data available from data.open.ac.uk and creates its own (private) datasets to support researchers at the Open University (hundreds of them) in managing, annotating and promoting their research output. Ability to programme (in PHP, and possibly in Javascript) as well as experience/interest in managing information in the academic community are of course needed here.

The deadline for applying is the 19th September 2012. See the vacancy page for details.

Research Assistant / Associate — LinkedUp Project (2 years)

More academic in nature (AC1/2), this job is also broader in scope. Working within the LinkedUp European Support Action, the goal here is to create both the technological and the support infrastructure to push forward the application of linked data in the education sector in general. This means in particular that we need somebody able to become an expert in the application of the linked data principles for open educational data, and learning and teaching applications. Beyond the purely technological aspects however, this implies collaborating and engaging with a large network of educational institutions (universities and other organisations) on innovations led by the deployment of Linked Data-based solutions.

The deadline for applying is the 12th September 2012. See the vacancy page for details.

This report is based in large parts on the experience built in the last months of LUCERO, especially in connecting with other organisations and trying to gather common issues and practices, through LinkedUniversities.org.

The report covers the general principles underlying Linked Data technologies and their relevance to the field of education, especially focusing on open and distance learning. It illustrates use case scenarios of Linked Data for learning and teaching through describing existing applications, and details the process of adopting and deploying Linked Data for educational resources and learning-related information. Through publishing it on its website under an open license, COL hopes that this report will become a valuable resource to a wide variety of organisations, raising the general awareness of the benefits of using open Web technologies such as Linked Data for educational purposes.

The winning application of the KMi Linked Data Application Competition has attracted the interest of the ROLE project (Responsive Open Learning Environments – www.role-project.eu). The OpenLearn Linked Data application was originally developed by Fouad Zablith as a showcase of querying data.open.ac.uk for educational resources related with OpenLearn courses. I have now transformed this application into a widget that can be directly embedded into any OpenLearn course as a Moodle block. The widget displays a list of Open University courses, iTunesU podcasts, as well as OpenLearn tags related to the course that the user is currently viewing. As data.open.ac.uk is constantly growing by integrating metadata from more repositories, the widget will also be extended with recommendations about educational resources of additional types. You can try out the current release by logging in as guest at: http://projects.kmi.open.ac.uk/role/moodle/course/view.php?id=3.

This widget is part of the widget bundles developed by ROLE for providing self-regulated learning support. ROLE is aiming at empowering learners for lifelong and personalised learning within a responsive open learning environment. OpenLearn comprises one of the project’s test-beds concerning the transition from formal learning towards informal learning, where the learner is in control of the whole learning process. For more information about the learning technologies developed so far by ROLE, please visit the Showcase Platform (http://www.role-showcase.eu/).

That’s when we thought of organising a linked data application competition in KMi. KMi is full of very smart people, researchers and PhD students with the skills, knowledge and energy to build this sort of apps: lightweight, web or mobile applications to demonstrate one specific aspect and one specific use of the Open University’s linked data. I’m not going to give all the details of the way the competition was organised. We received four incredibly interesting applications (the promise of winning an iPad might have helped). This four applications are now featured on the brand new Data.open.ac.uk Application Page together with other applications currently being developed.

So, congratulations to our winners! The choice was really difficult (and you might not agree with it), as the applications described below are all great examples of the many things that can be achieved through opening up and linking university data.

The Winner: OpenLearn Linked Data (Fouad Zablith)

OpenLearn Linked Data makes use of data from data.open.ac.uk to suggest courses, podcasts and other OpenLearn units that relate to an OpenLearn Unit. The application takes the form of a bookmarklet that, when triggered while browsing the webpage of an OpenLearn unit, will add to the page small windows with links to the relevant course in Study at the OU, to podcasts from the OU podcast repositories and units from OpenLearn that share a common tag.

The great thing about this application is that it addresses scenarios directly relevant to students, prospective students and users of OpenLearn in general. It very naturally exploits the way linked data removes the boundaries that exist between different systems within the Open University, without having to change or integrate these systems.

Second Place: OU Expert Search (Miriam Fernandez)

The OU Expert Search system (accessible inside the OU network only) allows users to find academics at the Open University who are experts in a given domain, providing a ranked list of experts based in particular on their research publications. It uses information about publications in ORO and computes complex measures to provide a ranking of the people who are most likely to be experts in the given domain. It also integrates data obtained from the staff directory of the Open University to provide contact details for the people in the system.

Here as well the strong point of the application is its apparent simplicity. It is very easy to use and has been applied already for example to find Open University experts on Volcanoes (see Stuart’s blog post). Expert search is a complex task, and OU Expert Search, through the use of linked data, makes it look rather simple.

OUExperts (Vlad Tanasescu)

OUExperts is a mobile (android) application to find Open Univeristy experts in a given domain, and connect to their social network. Similarly to the OU Expert Search application, it relies on information related to the scientific publications of OU researchers, as available in ORO. It also finds synonyms of the given keywords, and tries to connect to the pages of the listed researchers.

The interesting aspect of OUExperts, apart from being a mobile application, is the clever attempt to connect to social networking website, so that it is not only possible to find an expert, but also to connect to them on Facebook or LinkedIn.

Buddy Study (Matthew Rowe)

Buddy Study suggests potential contacts and Open University courses to follow for students, based on the analysis of the topics in the user’s Facebook page. The application attempts to extract from the user’s Facebook page prominent topics, which are then matched to the interests of other people, and to the topics covered by courses at the Open University.

In this case, it is the social aspect of a user’s presence online which is used to create connections into the data from the Open University, creating easily accessible entry points to the data.

One of the frustrations that people in organisations all over the world must share (and I’d imagine this is especially true in academic institutions) is that the systems in which our data is locked up have grown organically, often do not talk to each other and are not accessible to anyone but the folk who work with the systems as part of their job. Much of the data tied up in these systems is actually data that we make publicly available through various channels but is only easy to use for the purpose for which that system was developed.  This has ultimately meant that it is difficult for us as an institution to answer questions like ‘Which academics do we have working in the area of x and which courses does that research contribute to?’ or ‘what podcasts, videos, OERs does the OU produce that is relevant to y item in the news?’

One of the massive successes of the LUCERO project is that we have been able to free so much of this data from various silos and link it together (let alone link it to non-OU data as per Mathieu’s previous RED example) so that we can ask interesting and (more importantly) useful questions against it.

A very practical example of this happened regarding the sad news about the Tsunami in Japan.  The OU has some of the world’s experts on earthquakes but no currently-live experts database.  Similarly the OU has a massive collection of podcasts on iTunesU – surely there must be some content that we can  highlight that will help inform the public debate and discussion around recent events? Well of course we do but it turns out that some of our systems make it very easy to find this stuff and it’s be a pain having to visit and query numerous separate locations.  Fortunately a quick call to @fzablith and some cool entries to the OU linked data dev competition proved an enormous help.

Fouad quickly rustled up a SPARQL query which returned all of the OU podcasts related to earthquakes and another returning relevant OpenLearn units (of course I already had the same query in my head, I just wanted to double-check that he would do the same thing ) whilst the Expert Search (OU network only) returned a great list of all our academics who had peer-reviewed work published on the topic.  All very helpful and very quick!

It’s exactly this kind of understanding of what we produce as a university and the greater opportunities it gives us to actually make use of it for a variety of purposes (course production, media relations, reuse in external environments) that makes me excited about what we’ve already achieved and what more we can achieve over the coming years.

In my own particular area of responsibility (web publishing at the OU / social web) I’m really looking forward to making our web CMS (Drupal) contribute to the data we have on data.open.ac.uk and also consume the data.  Whether that’s building a new experts guide which builds on the OU people profile system and pulls in relevant data from data.open.ac.uk and external data sources, or making it easy (a few clicks of a mouse easy) for site builders with particular audiences (subject areas specific / industry specific) to include information on OU courses, podcasts, research OERs, YouTube videos etc.  Watch this space!

It is easy to see the impact this had on traffic to the website

The announcements we made regarding establishing http://data.open.ac.uk and the first data sets were picked up and retweeted extensively, including re-tweets from Andrew Stott (previously UK Government Director of Digital Engagement at the Cabinet Office), and Professor Jim Hendler (a leading expert in the Semantic Web and related technologies)

Twitter has proved effective for immediate dissemination of project milestones, but there is a lot of detailed information that we want to communicate and so we have started to present longer form information, both on this blog, but also through seminars. Mathieu introduced Lucero in a seminar at the Knowledge Media institute (KMi) at the Open University on the 3rd November 2010. A recording of this is now available to view online at the KMi Stadium, and the slides from this presentation are available on Slideshare.  On the same day I gave a presentation to Library staff at the Open University, and the slides are also available on Slideshare.

To reach a wider audience we’ve worked with the Media team at the Open University to issue a press release about the project and data.open.ac.uk. We hope that this will help us reach those who are unlikely to be following the project in detail, but who have an interest in the overall aims and objectives of the project.

We’ll be continuing to disseminate the work of the project through many routes, so keep track through this blog, or by following the team on twitter (@mdaquin, @ostephens, @stuartbrown, @fzablith) and tracking the project hashtag #luceroproject. If you are interested in the type of information you can get from http://data.open.ac.uk you can also look for #queryou where examples of SPARQL queries against the data are being shared (and feel free to add your own).

]]> http://lucero-project.info/lb/2010/11/introducing-lucero/feed/ 1 http://lucero-project.info/lb/2010/10/first-version-of-data-open-ac-uk/ http://lucero-project.info/lb/2010/10/first-version-of-data-open-ac-uk/#comments Mon, 11 Oct 2010 14:51:49 +0000 Mathieu http://lucero-project.info/lb/?p=212 LUCERO is all about making University wide resources available to everyone in an open, linked data approach. We are building the technical and organisational infrastructure for institutional repositories and research projects to expose their data on the Web, as linked data. It is therefore natural for the interface to this data, the SPARQL endpoint and server addressing URIs in this data to be hosted under http://data.open.ac.uk. The first version of the components underlying this site, as well as a small part of the data which will be ultimately exposed there have gone live last week, with a certain level of excitement from all involved.

What is there? The data

The “launch” of data.open.ac.uk happened relatively shortly after the beginning of the LUCERO project. Indeed, we take the approach that the basic data exposure architecture have to be in place, to incrementally integrate data into it. As a first step, we developed extraction and update mechanisms (see the previous blog post of about the LUCERO workflow) for two important repositories at the Open University: ORO, our publication repository, and podcast, the collection of podcasts produced by the Open University, including the ones being distributed through iTunes U.

ORO data concerns scientific publications with at least one member of the Open University as co-author. The source of the data is a repository based on the EPrints open source publication repository system. EPrints already integrates a function to export information as RDF, using the BIBO ontology. We of course used this function, post-processing what is obtained to obtain a representation consistent with the other (future) datasets in data.open.ac.uk, in particular in terms of URI Scheme. The ORO data represents at the moment 13,283 Articles and 12 Patents, in approximately 340,000 triples (see for example the article “Molecular parameters of post impact cooling in the Boltysh impact structure”).

Podcast data is extracted from the collection of RSS feeds obtained from podcast.open.ac.uk, using a variety of ontologies, including the W3C media ontology and FOAF (see for example the podcast “Great-circle distance”). An interesting element of this dataset is that it provides connections to other types of resources at the Open University, including courses (see for example the course MU120, which is being referred to in a number of podcasts). Podcasts are also classified into categories, using the same topics used to classify courses at the Open University, as well as the iTunesU categories, which we represent in SKOS (see for example the category “Mathematics”).

While representing only a small fraction of the data we will ultimately expose through data.open.ac.uk, the new possibilities obtained by exposing openly these datasets in RDF, with a SPARQL endpoint and resolvable URIs are very exciting already. In a blog post, Tony Hirst has shown some initial examples and encouraged others to share their queries to the Open University’s linked data. Richard Cyganiak has also kindly created a CKAN description of our datasets, for others to find and exploit.

The technical aspects

In a previous blog post, we gave an overview of the technical workflow by which data from the original sources would end up being exposed as linked data. The current platform implements parts of this workflow, including updaters and extractors for the two considered datasets. At the centre of the platform is the triple store. After trying several options, including Sesame, Jena TDB and 4Store, we settled for SwiftOWLIM, which is free, scalable and efficient, and includes limited reasoning capabilities, which might end up being useful in the future.

The current platform also implements the mechanisms by which URIs in the http://data.open.ac.uk namespaces are being resolves. Very simply, a URI such as http://data.open.ac.uk/course/a330 can either be re-directed to http://data.open.ac.uk/page/course/a330 or to http://data.open.ac.uk/resource/course/a330 depending on the content being requested by the client. http://data.open.ac.uk/page/course/a330 shows a browsable webpage linking the considered resource to related one, while http://data.open.ac.uk/resource/course/a330 provides the RDF representation of this resource.

A SPARQL endpoint is also available, which allows to query the whole set of data, or individual datasets through their namespaces, http://data.open.ac.uk/context/oro and http://data.open.ac.uk/context/podcast.

What’s next?

Of course, this first version of data.open.ac.uk is only the beginning of the story. We are currently actively looking at the way to represent and extract information about courses and qualifications from the Study At the OU website, as well as at information about places in the OU campus and regional centres (building, car parks, etc.)

More ways to access will also be soon made available, including faceted search/browsing, and links to external datasets are being investigated. All this is going to be gradually integrated into the platform while the existing data is being constantly updated.

As you probably have noticed, this is not exactly the first post on this blog. As you can see from the about page, LUCERO is a JISC funded project and JISC encourage us to use the blog of the project also as a reporting tool. The 7 first posts therefore correspond to the project workplan and, while some of it can be of interest, the rest is mostly bureaucratic things.

To summarize all what that says, LUCERO is a one year project started last June at The Open University (OU), with the goal to set up and launch a complete infrastructure, both technical and organizational, for the exposure of educational and research content as linked data. A higher education organization such the OU typically creates and manages vast amounts of data in different repositories, including library catalogs, publication bases, staff directories, A/V material, course descriptions, etc. Linked data is a set of principles and technologies making it possible to publish data on the Web, in a standard, machine readable format, and where every piece of information is “Web addressable”, i.e., identified by a URI, and so linkable. This allows to seamlessly integrate data, creating on the Web a network of data, much like there is currently a network of documents. This is obviously a very brief and general summary (you can have a look at the Linked Data Horizon Scan document for more), but already, the potential of applying this to large University repositories should appear evident. What LUCERO intends to do is to create a OU Web of Data, connecting all the repositories with each other and with external datasets. More importantly, we want to use this experience to provide reusable software and guidelines for other similar organizations to take advantage of the linked data approach, through setting up and sustaining the exposure of educational content as linked data.

Of course, we don’t start from scratch. Several organizations have already been publishing data online, such as the BBC, the UK government or, closer to us, the ECS school at the University of Southampton. However, the scale of the task in organizational terms, the non-technological issues involved and the endless possibilities implied by releasing and connecting such data clearly makes LUCERO a unique experience. Indeed, one of the goals of LUCERO is also to concretely demonstrate the benefit of linked data, through the development of applications targeting students and researchers, focusing on the domain of Arts. But that should really be the topic of another blog post later in the project, as will be the details of the different datasets we consider, the tools we experiment with and the issues we will need to tackle.