Today I gave the keynote presentation (slides below) at the Crusade for Big Data in the AAL domain workshop as part of the EU Ambient Assisted Living Forum. I gave an overview of the way that the Open PHACTS project has overcome various Big Data challenges to provide a production quality data integration platform that is being used to answer real pharmacology business questions.
The workshop then broke out into five breakout groups to discuss open challenges facing the AAL community that are posed by Big Data. The breakout groups were:
- Privacy and Ethics
- Business models for sustainability
- Data reuse and interoperability
- Data quality
- Feedback to the users
The organisers of the workshop (Femke Ongenae and Femke De Backere) will be sharing the outcomes of the brainstorming by proposing several working groups to focus on the issues in the area of AAL.
We are delighted to announce that Open PHACTS has been awarded first place in the Linked Open Data Award of the inaugural European Linked Data Contest (ELDC). An international jury of ambassadors from over 15 European countries elected Open PHACTS as the winner, judged by the following criteria:
Gerhard receiving ELDC award
- Shows a high degree of innovation
- triggers network effects
- embraces open standards
- proves technological matureness
- shows great potential to be utilised in multiple domains
- achieves a high degree of comprehensibility for the users
The ELDC has been established to recognise Europe’s crème de la crème of linked data and semantic web. Prizes are awarded to stories, products, projects or persons presenting novel and innovative projects, products and industry implementations involving linked data. The ELDC also aims to build a directory of the best European projects in the domains of linked data and the semantic web. Open PHACTS is honored to be chosen as the first winner of the ELDC’s Linked Open Data Award, and to be included in this directory.
Today I had the pleasure of visiting the Urban Big Data Centre (UDBC) to give a seminar on Data Integration in a Big Data context (slides below). The idea for the seminar came about due to my collaboration with Nick Bailey (Associate Director of the UBDC) in the Administrative Research Data Centre for Scotland (ADRC-S).
In the seminar I wanted to highlight the challenges of data integration that arise in a Big Data context and show examples from my past work that would be relevant to those in the UBDC. In the presentation, I argue that RDF provides a good approach for data integration but it does not solve the basic challenges of messy data and generating mappings between datasets. It does however lay these challenges bare on the table, as Frank van Harmelen highlighted in his SWAT4LS keynote in 2013.
The first use case is drawn from my work on the EU SemSorGrid4Env project where we were developing an integrated view for emergency response planning. The particular use case shown is that of coastal flooding on the south coast of England. Although this project finished in 2011, I am still involved with developing RDF and SPARQL continuous data extensions; see the W3C RDF Stream Processing Community Group for details.
The second use case is drawn from my work on the EU Open PHACTS project. I showed the approach we developed for supporting user controlled views of the integrated data through Scientific Lenses. However, I also talked about the successes of the project and the fact that is currently being actively used for pharmacology research and receiving over 20million hits a month.
I finished the talk with an overview of the Administrative Data Research Centre for Scotland (ADRC-S) and my work on linking birth, marriage, and death records. I am hoping that we can adopt the lenses approach together with incorporating feedback on the linkages from the researchers who will use the integrated views.
In the discussions following the talk, the notion of FAIR data came up. This is the idea that data should be Findable, Accessible, Interoperable, and Reusable by both humans and machines. RDF is one approach that could lead to this. The other area of discussion was around community initiatives for converting existing open datasets into an RDF format. I advocated adopting the approach followed by the Bio2RDF community who share the tasks of creating and maintaining such scripts for biological datasets. An important part of this jigsaw is tracking the provenance of the datasets, for which the W3C Health Care and Life Sciences Community Profile for Dataset Descriptions could be beneficial (there is nothing specific to the HCLS community in the profile).
After 3 years hard work, countless telephone conferences, issues and drafts, the W3C Health Cara and Life Sciences Community Group (HCLS) have finally published their community profile for describing datasets. The profile deals with different versions of a dataset with each version being published in multiple formats. Below is the announcement from the W3C.
The Semantic Web Health Care and Life Sciences Interest Group has published a Group Note of Dataset Descriptions: HCLS Community Profile. Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. This document describes a consensus among participating stakeholders in the Health Care and the Life Sciences domain on the description of datasets using the Resource Description Framework (RDF). This specification meets key functional requirements, reuses existing vocabularies to the extent that it is possible, and addresses elements of data description, versioning, provenance, discovery, exchange, query, and retrieval. Learn more about the Data Activity.
Today I attended the SICSA Databases for the Environmental and Social Sciences event hosted by Andy Cobley from the University of Dundee. I gave the below talk on the challenges of linking data.
Many areas of scientific discovery rely on combining data from multiples data sources. However there are many challenges in linking data. This presentation highlights these challenges in the context of using Linked Data for environmental and social science databases.