Linked Data

ISWC 2016 Trip Report

It has now been almost two months since ISWC 2016 where I was the Resources Track chair with Marta Sabou. This has given me time to reflect on the conference, in between a hectic schedule of project meetings, workshops, conferences, and a PhD viva.

The most enjoyable part of the conference for me was the CoLD Workshop Debate on the State of Linked Data. The workshop organisers had arranged for six prominent proponents of the Linked Data to argue that we have failed and that Linked Data will die away.

  1. Ruben Verborgh argued that Linked Data will be destroyed by the need to centralise data, poor infrastructure, and the research community. (Aside: There was certainly concern on the final point as there were only three females in the room.)
  2. Axel Polleres took the moto, “Let’s make RDF great again!” Axel’s central argument was around the fact that most open data is actually published in CSV format and lots can be achieved with 3* open data.

  3. Paul Groth argued that we should be concentrating on making our data processable by machines. What we currently have is a format that is aimed at both but satisfies neither.

  4. Chris Bizer covered cost incentives. While there is an incentive to provide some basic schema markup on pages, i.e. getting picked up by search engines, there is no financial incentive to provide the links to other resources. My take on this is that there is a disincentive as it would take traffic away from your (eCommerce) site and therefore lose you revenue.
  5. Avi Bernstein then did a fantastic impression of a Wee Free minister and telling us that we had all sinned and were following the wrong path; all fire and brimstone.
  6. Juan Reutter argued that we needed to provide a workable ecosystem.

So the question is, has the Linked Data community failed? I think the debate highlighted that the community had made many contributions in a short space of time but that it is time to get this into the main stream. Perhaps our community is not the best for doing the required sales job, but we have had some success, e.g. EBI RDF platform, Open PHACTS Drug Discovery Platform, BBC Olympic Web Site.

The main conference was underpinned by three fantastic and varied keynotes. First was Kathleen McKeown who gave us insights into the extraction of knowledge from different forms of text. Second was Christian Bizer who’s main message was that we as a community need to take structured data in whatever form it comes; just like search engines have exploited metadata and page structure for a long time. Finally was Hiroaki Kitano from the Sony Corporation. This has got to be the densest keynote I have ever heard with more ideas per minute than a dance tune has beats. His challenge to the community was that we should aim to have an AI system win a scientific nobel prize by 2050. The system should develop a hypothesis, test it, and generate a ground breaking conclusion worthy of the prize.

There were many great and varied talks during the conference. It really is worth looking through the programme to find those of interest to you (all the papers are linked and available). As ever the poster and demo session, advertised in the minute madness session, demonstrated the breadth and cutting edge work going on in the community. As did the lightning talk session.

The final day of the conference was particularly weird for me. As the chair of a session I ended up sharing a bottle of fine Italian wine with a presenter during his talk, it would have been rude not to; and experiencing an earthquake during a presentation on an ontology for modelling the soil beneath our cities, in particular the causes of damage to that soil.

The conference afforded some opportunities for fun as well. A few of the organising committee managed to get visit the k-computer; the worlds fifth fastest super-computer which is cooled with water. The computer was revealed in a very James Bond, “Now I’m going to have to kill you!” reveal of the evil enemy’s master plan. There was also a highly entertaining Samurai sword fighting demonstration during the conference banquet.

During the conference, my Facebook feed was filled with exclamations about the complexity of the toilets. Following the conference, it was filled with exclamations of returning to lands of uncivilised toilets. Make of this what you will.

HCLS Tutorial at SWAT4LS 2016

On 5 December 2016 I presented a tutorial [1] on the Heath Care and Life Sciences Community Profile (HCLS Datasets) at the 9th International Semantic Web Applications and Tools for the Life Sciences Conference (SWAT4LS 2016). Below you can find the slides I presented.

The 61 metadata properties from 18 vocabularies reused in the HCLS Community Profile are available in this spreadsheet (.ods).

[1] Unknown bibtex entry with key [Gray2016SWAT4LSTutorial]
[Bibtex]

Raasay House

Will the real Kevin Macleod please line up?

Last week I attended the Digitising Scotland Project Colloquium at Raasay House (featured image above) on the Isle of Raasay. The colloquium was a gathering of historians and computer scientists to discuss the challenges of linking the vital records of the people of Scotland between 1851 and 1974.

The Digitising Scotland Project is having the birth, marriage, and death records of Scotland transcribed from the scans of the original hand written registration books. This process is not without its own challenges, try reading this birth record of a famous Scottish artist and architect, but the focus of the colloquium was on what happens after the records have been transcribed.

Each Scottish vital record identifies several individuals, e.g. on a birth record you will have the baby, their parents, the informant, and the registrar. The same individuals will appear on multiple records relating to events in their own life, e.g. an individual will have a birth record, potentially one or more marriage records, and a death record, assuming that they have not emigrated. They can also appear in the records of other individuals, e.g. as a mother on a birth record, the mother-of-the-bride on a marriage record, or the doctor on a death record. The challenge is how to identify the same individual across all the records, when all you have is a name (first and last) and potentially the age.

The problem is compounded in an area like Skye, which was one of the focus regions of the Digitising Scotland project, because there is a relatively small distribution of names on which to draw upon. For example, a name like Kevin Macleod will appear on multiple records. In some cases the name will correspond to a single Kevin Macleod, in other cases it will be a closely related Kevin Macleod, e.g. Kevin Macleod the father of Kevin Macleod, and in others the two Kevin Macleods will not be related at all. The challenge is how to develop a computer algorithm that is capable of making these distinctions.

The colloquium was a great opportunity for historians and computer scientists to discuss the challenges and help each other to develop a solution. However, first we had to agree on a common understanding for terms such as “record” and “individual”.

Overall, we made great progress on exchanging ideas and techniques. We heard how similar challenges are being addressed in a related project focusing on North Orkney, how historians approach the record linkage challenge, and about work for automatically classifying causes of death to their ICD10 code and jobs to HISCO. There was also time to socialise and enjoy some of the scenery of Raasay, which is a beautiful island the size of Manhattan but with a population of only 160.

View from the meeting room

View from the meeting room

Sunset over Portree, Skye

Sunset over Portree, Skye

HCLS Community Profile for Dataset Descriptions

My latest publication [1] describes the process followed in developing the W3C Health Care and Life Sciences Interest Group (HCLSIG) community profile for dataset descriptions which was published last year. The diagram below provides a summary of the data model for describing datasets which covers 61 metadata terms drawn from 18 vocabularies.Overview of the HCLS Community Profile for Dataset Descriptions

[1] Unknown bibtex entry with key [Dumontier2016HCLS]
[Bibtex]