Extending the FOAF vocabulary for junkets, personal travel and map generation

As we know, FOAF provides a good way of exposing machine-readable data on people, their activities and interests, and the nature of their relationships with other people, groups or things. FOAF allows us to model social networks much in the same way as a social networking service might (e.g. Facebook). The big difference being that with FOAF the resultant social graph is exposed to the Semantic Web in a distributed way for machine processing (and all the goodness that this might entail…); not held in proprietary databases.

FOAF data has generally always been augmented with other RDF vocabularies. Nothing strange in this; this was anticipated, and reusing and remixing vocabularies and RDF data is a key component of the Semantic Web. My FOAF profile, for example, uses numerous additional vocabularies for enrichment, including Dublin Core, the Music Ontology, and the Contact, Relationship and Basic Geo vocabularies. The latter vocabulary (Basic Geo) provides the hook for this blog posting.

The need to provide geographical coordinates and related data in RDF was recognised early in the life of the Semantic Web, and the Basic Geo (WGS84 lat/long) Vocabulary website lists obvious applications for such data. Although including geographical data within FOAF profiles presents an obvious use (e.g. using Basic Geo to provide the latitude and longitude of, say, your office location), few people do it because few applications actually do anything with it. That was until a couple of years ago when Richard Cyganiak (DERI, National University of Ireland) developed an experimental FOAF widget (FOAF – Where Am I?) to determine geographical coordinates using the Google Maps API and then to spit it out in FOAF RDF/XML for inclusion in a FOAF profile. In his words, "there's no more excuses for [not including coordinates]". With coordinates included, FOAF profiles could be mapped using Alexandre Passant's FOAFMap.net widget (also from DERI), which was developed around the same time and extracts geographical data embedded within FOAF profiles and then maps it using Google Maps. Despite the presence of these useful widgets, FOAF profiles rarely contain location data because, let's face it, are we that interested in a precise geographical location of an office?!

More interesting – and perhaps more useful – is to model personal travel within a FOAF profile. This is consistent with the recent emergence (within the past year or so) of 'smart travel' services on the web, the most notable of which is probably Dopplr. Dopplr essentially allows users to create, share and map details of future journeys and travel itineraries with friends, colleagues, business contacts, etc. so that overlaps can be discovered in journey patterns and important meetings arranged between busy persons. It is also consistent with the personal homepages of academics and researchers. For example, Ivan Herman's (W3C Semantic Web Activity Lead) website is one of many which include a section about upcoming trips. There are others too. From personal experience I can confirm that many an international research relationship has been struck by knowing who is going to be at the conference you are attending next week! People also like to record where they have been and why, and the 'Cities I've Visited' Facebook application provides yet another example of wanting to associate travel with a personal profile, albeit within Facebook.

Of course, Dopplr and Facebook applications are all well and good; but we want to expose these journeys and travel itineraries in a distributed and machine processable way - and FOAF profiles are the obvious place to do it. It is possible to use the RDF Calendar vocabulary to model some travel, but it's a little itchy and can't really tell us the purpose of a journey. Other travel ontologies exist, but they are for 'serious' travel applications and too heavy weight for a simple FOAF profile. It therefore occurred to me that there is a need for a light weight RDF travel vocabulary, ideally for use with FOAF, which can better leverage the power of existing vocabularies such as Basic Geo and RDF Calendar. I documented my original thoughts about this on my personal blog, which I use of more technical musings. Enriching a FOAF profile with such data would not only expose it to the Semantic Web and enrich social graphs, but make applications (similar to those described above) possible in an open way.

To this end I have started authoring the Travelogue RDF Vocabulary (TRAVOC). It's a pretty rough and ready approach (c'mon, 3 -4 hours!) and is really just for experimental purposes; but I have published what I have so far. A formal RDF Schema is also available. Most properties entail being a foaf:Person and I have provided brief examples on my blog.

As noted, TRAVOC has been sewn together in a short order. It would therefore benefit from some further consideration, refinements and (maybe) expansion. Perhaps there's a research proposal in it? Thoughts anyone? In particular, I would be interested know if any of the TRAVOC properties overlap with existing vocabularies which I haven't been able to find. If I have time – and if and when I am satisfied with the final vocabulary - I may acquire the necessary PURLs.

Read all about it: interesting contributions at ISKO-UK 2009

I had the pleasure of attending the ISKO-UK 2009 conference earlier this week at University College London (UCL), organised in association with the Department of Information Studies. This was my first visit to the home of the architect of Utilitarianism, Jeremy Bentham, and the nearby St. Pancras International since it has been revamped - and what a smart train station it is.

The ISKO conference theme was 'content architecture', with a particular focus on:

• "Integration and semantic interoperability between diverse resources – text, images, audio, multimedia
• Social networking and user participation in knowledge structuring
• Image retrieval
• Information architecture, metadata and faceted frameworks"
  

The underlying themes throughout most papers were those related to the Semantic Web, Linked Data, and other Semantic Web inspired approaches to resolving or ameliorating common problems within our disciplines. There were a great many interesting papers delivered and it is difficult to say something about them all; however, for me, there were particular highlights (in no particular order)...

Libo Eric Si (et al.) from the Department of Information Science at Loughborough University described research to develop a prototype middleware framework between disparate terminology resources to facilitate subject cross-browsing of information and library portal systems. A lot of work has already been undertaken in this area (see for example, HILT project (a project in which I used to be involved), and CrissCross), so it was interesting to hear about his 'bag' approach in which – rather than using precise mappings between different Knowledge Organisation Systems (KOS) (e.g. thesauri, subject heading lists, taxonomies, etc.) - "a number of relevant concepts could be put into a 'bag', and the bag is mapped to an equivalent DDC concept. The bag becomes a very abstract concept that may not have a clear meaning, but based on the evaluation findings, it was widely-agreed that using a bag to combine a number of concepts together is a good idea".

Brian Matthews (et al.) reported on an evaluation of social tagging and KOS. In particular, they investigated ways of enhancing social tagging via KOS, with a view to improving the quality of tags for improvements in and retrieval performance. A detailed and robust methodology was provided, but essentially groups of participants were given the opportunity to tag resources using tags, controlled terms (i.e. from KOS), or terms displayed in a tag cloud, all within a specially designed demonstrator. Participants were later asked to try alternative tools in order to gather data on the nature of user preferences. There are numerous findings - and a pre-print of the paper is already available on the conference website so you can read these yourself - but the main ones can be summarised from their paper as follows and were surprising in some cases:

• "Users appreciated the benefits of consistency and vocabulary control and were potentially willing to engage with the tagging system;
• There was evidence of support for automated suggestions if they are appropriate and relevant;
• The quality and appropriateness of the controlled vocabulary proved to be important;
• The main tag cloud proved problematic to use effectively; and,
• The user interface proved important along with the visual presentation and interaction sequence."

The user preference for controlled terms was reassuring. In fact, as Matthews et al. report:

"There was general sentiment amongst the depositors that choosing terms from a controlled vocabulary was a "Good Thing" and better than choosing their own terms. The subjects could overall see the value of adding terms for information retrieval purposes, and could see the advantages of consistency of retrieval if the terms used are from an authoritative source."

Chris Town from the University of Cambridge Computer Laboratory presented two (see [1], [2]) equally interesting papers relating to image retrieval on the Web. Although images and video now comprise the majority of Web content, the vast majority of retrieval systems essentially use text, tags, etc. that surround images in order to make assumptions about what the image might be. Of course, using any major search engine we discover that this approach is woefully inaccurate. Dr. Town has developed improved approaches to content-based image retrieval (CBIR) which provide a novel way of bridging the 'semantic gap' between the retrieval model used by the system and that of the user. His approach is founded on the "notion of an ontological query language, combined with a set of advanced automated image analysis and classification models". This approach has been so successful that he has founded his own company, Imense. The difference in performance between Imense and Google is staggering and has to been seen to be believed. Examples can be found in his presentation slides (which will be on the ISKO website soon), but can observed from simply messing around on the Imense Picture Search.

Chris Town's second paper essentially explored how best to do the CBIR image processing required for the retrieval system. According to Dr. Town there are approximately 20 billion images on the web, with the majority at a high resolution, meaning that by his calculation it would take 4000 years to undertake the necessary CBIR processing to facilitate retrieval! Phew! Large-scale grid computing options therefore have to be explored if the approach is to be scalable. Chris Town and his colleague Karl Harrison therefore undertook a series of CBIR processing evaluations by distributing the required computational task across thousands of Grid nodes. This distributed approach resulted in the processing of over 25 million high resolution images in less than two weeks, thus making grid processing a scalable option for CBIR.

Andreas Vlachidis (et al.) from the Hypermedia Research Unit at the University of Glamorgan described the use of 'information extraction' techniques employing Natural Language Processing (NLP) techniques to assist in the semantic indexing of archaeological text resources. Such 'Grey Literature' is a good test bed as more established indexing techniques are insufficient in meeting user needs. The aim of the research is to create a system capable of being "semantically aware" during document indexing. Sounds complicated? Yes – a little. Vlachidis is achieving this by using a core cultural heritage ontology and the English Heritage Thesauri to support the 'information extraction' process and which supports "a semantic framework in which indexed terms are capable of supporting semantic-aware access to on-line resources".

Perhaps the most interesting aspect of the conference was that it was well attended by people outside the academic fraternity, and as such there were papers on how these organisations are doing innovative work with a range of technologies, specifications and standards which, to a large extent, remain the preserve of researchers and academics. Papers were delivered by technical teams at the World Bank and Dow Jones, for example. Perhaps the most interesting contribution from the 'real world' though was that delivered by Tom Scott, a key member of the BBC's online and technology team. Tom is a key proponent of the Semantic Web and Linked Data at the BBC and his presentation threw light on BBC activity in this area – and rather coincidentally complemented an accidental discovery I made a few weeks ago.

Tom currently leads the BBC Earth project which aims to bring more of the BBC's Natural History content online and bring the BBC into the Linked Data cloud, thus enabling intelligent linking, re-use, re-aggregation, with what's already available. He provided interesting examples of how the BBC was exposing structured data about all forms of BBC programming on the Web by adopting a Linked Data approach and he expressed a desire for users to traverse detailed and well connected RDF graphs. Says Tom on his blog:

"To enable the sharing of this data in a structured way, we are using the linked data approach to connect and expose resources i.e. using web technologies (URLs and HTTP etc.) to identify and link to a representation of something, and that something can be person, a programme or an album release. These resources also have representations which can be machine-processable (through the use of RDF, Microformats, RDFa, etc.) and they can contain links for other web resources, allowing you to jump from one dataset to another."

Whilst Tom conceded that this work is small compared to the entire output and technical activity at the BBC, it still constitutes a huge volume of data and is significant owing to the BBC's pre-eminence in broadcasting. Tom even reported that a SPARQL end point will be made available to query this data. I had actually hoped to ask Tom a few questions during the lunch and coffee breaks, but he was such a popular guy that in the end I lost my chance, such is the existence of a popular techie from the Beeb.

Pre-print papers from the conference are available on the proceedings page of the ISKO-UK 2009 website; however, fully peer reviewed and 'added value' papers from the conference are to be published in a future issue of Aslib Proceedings.

Quasi-facetted retrieval of images using emotions?

As part of my literature catch up I found an extremely interesting paper in JASIST by S. Schmidt and Wolfgang G. Stock entitled, 'Collective indexing of emotions in images : a study in emotional information retrieval'. The motivation behind the research is simple: images tend to elicit emotional responses in people. Is it therefore possible to capture these emotional responses and use them in image retrieval?

An interesting research question indeed, and Schmidt and Stock's study found that 'yes', it is possible to capture these emotional responses and use them. In brief, their research asked circa 800 users to tag a variety of public images from Flickr using their scroll-bar tagging system. This scroll-bar tagging system allowed users to tag images according to a series of specially selected emotional responses and to indicate the intensity of these emotions. Schmidt and Stock found that users tended to have favourite emotions and this can obviously differ between users; however, for a large proportion of images the consistency of emotion tagging is very high (i.e. a large proportion of users frequently experience the same emotional response to an image). It's a complex area of study and their paper is recommended reading precisely for this reason (capturing emotions anyone?!), but their conclusions suggest that:

"…it seems possible to apply collective image emotion tagging to image information systems and to present a new search option for basic emotions."

To what extent does the image above (by D Sharon Pruitt) make you feel happiness, anger, sadness, disgust or fear? It is early days, but the future application of such tools could find a place within the growing suite of image filters that many search engines have recently unveiled. For example, yesterday Keith Trickey was commenting on the fact that the image filters in Bing are better than Google or Yahoo!. True. There are more filters, and they seem to work better. In fact, they provide a species of quasi-taxonomical facets: (by) size, layout, color, style and people. It's hardly Ranganathan's PMEST, but – keeping in mind that no human intervention is required - it's a useful quasi-facet way of retrieving or filtering images, albeit flat.

An emotional facet, based on Schmidt and Stock's research, could easily be added to systems like Bing. In the medium term it is Yahoo! that will be more in a position to harness the potential of emotional tagging. They own Flickr and have recently incorporated the searching and filtering of Flickr images within Yahoo! Image Search. As Yahoo! are keen for us to use Image Search to find CC images for PowerPoint presentations, or to illustrate a blog, being able to filter by emotions would be a useful addition to the filtering arsenal.

Information seeking behaviour at Google: eye-tracking research

Anne Aula and Kerry Rodden have just published a posting on the Official Google Blog summarising some eye-tracking research they have been conducting on Google's 'Universal Search'. Both are active in information seeking behaviour and human-computer interaction research at Google and are well published within the related literature (e.g. JASIST, IPM, SIGIR, CHI, etc.).

The motivation behind their research was to evaluate the effect incorporation of thumbnail images and video within a research set has on user information seeking behaviour. Previous information retrieval eye-tracking research indicates that users scan results in order, scanning down their results until they reach a (potentially) relevant result, or until they decide to refine their search query or abandon the search. Aula and Rodden were concerned that the inclusion of thumbnail images might distract the "well-established order of result evaluation". Some comparative evaluation was therefore order of the day.

"We ran a series of eye-tracking studies where we compared how users scan the search results pages with and without thumbnail images. Our studies showed that the thumbnails did not strongly affect the order of scanning the results and seemed to make it easier for the participants to find the result they wanted."

A good finding for Google, of course; but most astonishing is the eye-tracking data. The speed with which users scanned result sets and the number of points on the interface they scanned was incredible. View the 'real time' clip below. A dot increasing in size denotes the length of time a user spent pausing at that specific point in the interface or result set. Some other interesting discoveries were made – the full posting is essential reading.

A conceptual model of e-learning: better studying effectiveness

My personal development has recently led me to explore and research the effectiveness of e-learning approaches to Higher Education (HE) teaching and learning. Since the late 1990s, e-learning has become a key focus of activity within pedagogical communities of practice (as well as those within information systems and LIS communities who often manage the necessary technology). HE is increasingly harnessing e-learning approaches to provide flexible course delivery models capable of meeting the needs of part-time study and lifelong learners. Of particular relevance, of course, is the Web, a mechanism highly conducive to disseminating knowledge and delivering a plethora of interactive learning activities (hence the role of informaticians).

The advantages of e-learning are frequently purported in the literature and are generally manifest in the Web itself. Such benefits include the ability to engage students in non-linear information access and synthesis; the availability of learning environments from any location and at any time; the ability for students to influence the level and pace of engagement with the learning process; and, increased opportunities for deploying disparate learning strategies, such as group discussion and problem-based or collaborative learning, as well as delivering interactive learning materials or learning objects. Various administrative and managerial benefits are also cited, such as cost savings over traditional methods and the relative ease with which teaching materials or courses can be revised.

Although flexible course delivery remains a principal motivating factor, the use of e-learning is largely predicated upon the assumption that it can facilitate improvements in student learning and can therefore be more effective than conventional techniques. This assumption is largely supported by theoretical arguments and underpins the large amounts of government and institutional investment in e-learning (e.g. JISC e-learning); yet, it is an assumption that is not entirely supported by the academic literature, containing as it does a growing body of indifferent evidence...

In 1983, Richard E. Clark from the University of Southern California conducted a series of meta-analyses investigating the influence of media on learning. His research found little evidence of any educational benefits and concluded that media were no more effective in teaching and learning than traditional teaching techniques. Said Clark:

"[E]lectronic media have revolutionised industry and we have understandable hopes that they would also benefit instruction".

Clark's paper was/is seminal and remains a common citation in those papers reporting indifferent e-learning effectiveness findings.

Is the same true of e-learning? Is there a similar assumption fuelling the gargantuan levels of e-learning investment? I feel safe in stating that such an assumption is endemic - and I can confirm this having worked briefly on a recent e-learning project. And I am in no way casting aspersions on my colleagues during this time, as I too held the very same assumption!!!

It is clear that evidence supporting the effectiveness of e-learning in HE teaching and learning remains unconvincing (e.g. Bernard et al.; Frederickson et al.). A number of comparative studies have arrived at indifferent conclusions and support the view that e-learning is at least as effective as traditional teaching methods, but not more effective (e.g. Abraham; Dutton et al.; Johnson et al.; Leung; Piccoli et al.). However, some of these studies exemplify a lack of methodological rigour (e.g. group self-selection) and many fail to control for some of the most basic variables hypothesised to influence effectiveness (e.g. social interaction, learner control, etc.). By contrast, those studies which have been more holistic in their methodological design have found e-learning to be more effective (e.g. Liu et al.; Hui et al.). These positive results could be attributed to the fact that e-learning, as an area of study, is maturing; bringing with it an improved understanding of the variables influencing e-learning effectiveness. Perhaps electronic media will "revolutionise" instruction after all?

Although such positive research tends to employ greater control over variables, such work fails to control for all the factors considered – both empirically and theoretically - to influence whether e-learning will be effective or not. Frederickson et al. have suggested that the theoretical understanding of e-learning has been exhausted and call for a greater emphasis on empirical research; yet it is precisely because a lack of theoretical understanding exists that invalid empirical studies have been designed. It is evident that the variables influencing e-learning effectiveness are multifarious and few researchers impose adequate controls or factor any of them into research designs. Such variables include: level of learner control; social interactivity; learning styles; e-learning system design; properties of learning objects used; system or interface usability; ICT and information literacy skills; and, the manner or degree to which information is managed within the e-learning environment itself (e.g. Information Architecture). From this perspective it can be concluded that no valid e-learning effectiveness research has ever been undertaken since no study has yet attempted to control for them all.

Motivated by this confusing scenario, and informed by the literature, it is possible to propose a rudimentary conceptual model of e-learning effectiveness (see diagram above) which I intend to develop and write up formally in the literature. The model attempts to improve our theoretical understanding of e-learning effectiveness and should aid researchers in comprehending the relevant variables and the manner in which they interact. It is anticipated that such a model will assist researchers in developing future evaluative studies which are both robust and holistic in design. It can therefore be hypothesised that using the model in evaluative studies will yield more positive e-learning effectiveness results.

Apologies this was such a lengthy posting, but does anyone have any thoughts on this or fancy working it up with me?

All the way from America...

Research is a much abused term. If you ask undergraduate students they will confidently describe a Google based “bash in a couple of terms and hit the return key” as research and subsequently suffer from the delusion that that is all research is. What I have been engaged in for the last week I think could be defined as a “fishing trip”. This is a research approach from the “old days” before the whole world was claimed as available online.

When you were opening a new major area of research you would take yourself off to a monster library (The British Library at Boston Spa was ideal – due to the immense journal collection it possessed) and using printed abstracts and indexes would slowly wade back through the last ten or twenty years of “stuff” as appropriate. At the end of the exercise you would have reasonable confidence that you had covered the field in detail. The subsequent reading of the literature gathered would allow you to patch what gaps there were. As my LCSH topic predates the standard abstracting and indexing services, this older approach was required.

So ensconced on the 5th floor of the Library of Congress Adams building I worked my way through sixty years worth of Library journal about thirty volumes of the Bulletin of the American Library Association and about ten years of the Catalogers’ and classifiers’ yearbook. The most recent volumes consulted were 1940. I would regularly branching off to pick up specialist subject heading lists or contemporary textbooks as I moved forward.

The result of this process can be evaluated in at least two ways. A simple measure of the thickness of the stack of photocopying to be brought back evidences (in a real sense) the extent of the information capture. The other measure came as a surprise to me, it just kind of sneaked up on me as the process developed. My confidence in my knowledge of the topic strengthened as the week proceeded. The previous slow and laborious accumulation of material of the last two years had not inspired my confidence (I was painfully aware of gaps in the process – even though I did not really know what the gaps were!). Having dug in and worked my way through the major sources of information my doubts as to how to proceed have cleared and the next stage in the process seems quite straightforward (at the level of ideas!).

The total luxury of having a whole week to dedicate to nothing else except the research has been massively helpful. I have waked, washed, ate, walked, worked and slept the research. This has allowed effective thinking to occur as those thousand and one well intentioned interruptions that plague my working and home life were simply turned off – along with the mobile phone.

Today is Thanksgiving – the massive American family festival, everything is closed – even the food facility in the hotel – just a continental breakfast – I have to eat out tonight – if I can find somewhere. So the day has been spent sorting my document harvest so I know what I need to copy in my Friday morning visit to the Library.

The real task begins when I get back to Liverpool as I attempt to convert this short sprint in Washington into the steady paced marathon that is required to deliver this research as an academic thesis.

MTSR 2007

A paper some ex-colleagues and I submitted to the International Conference on Metadata and Semantics Research has now been published as part of the conference proceedings. The paper entitled, 'Terminology server for improved resource discovery: analysis of functions and model', is available online for those that might be interested.

The conference took place at the Ionian University in sunny Corfu; however, owing to work pressures (since moving to LJMU) I was unable to present the paper in person and take advantage of warmer climes! Enjoy!