Seminar talk given at the EBI on 5 April 2017.
Abstract: Machine processable descriptions of datasets can help make data more FAIR; that is Findable, Accessible, Interoperable, and Reusable. However, there are a variety of metadata profiles for describing datasets, some specific to the life sciences and others more generic in their focus. Each profile has its own set of properties and requirements as to which must be provided and which are more optional. Developing a dataset description for a given dataset to conform to a specific metadata profile is a challenging process.
In this talk, I will give an overview of some of the dataset description specifications that are available. I will discuss the difficulties in writing a dataset description that conforms to a profile and the tooling that I’ve developed to support dataset publishers in creating metadata description and validating them against a chosen specification.
In December 2016 I presented at the Smart Descriptions and Smarter Vocabularies workshop on the Health Care and Life Sciences Community Profile for describing datasets, and our validation tool (Validata). Presentations included below.
The purpose of the workshop was to understand current practice in describing datasets and where the DCAT vocabulary needs improvement. Phil Archer has written a very comprehensive report covering the workshop. A charter is being drawn up for a W3C working group to develop the next iteration of the DCAT vocabulary.
On 5 December 2016 I presented a tutorial  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).
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For the last 5 years I have had the pleasure of working with the Open PHACTS project. Sadly, the project is now at an end. To celebrate we are having a two day symposium to look over the contributions of the project and its future legacy.
The project has been hugely successful in developing an integrated data platform to enable drug discovery research (see a future post for details to support this claim). The result of the project is the Open PHACTS Foundation which will now own the drug discovery platform and sustain its development into the future.
Here are my slides on the state of the data in the Open PHACTS 2.0 platform.
I was asked to speak at the School (Faculty) of Mathematical and Computer Sciences (MACS) Christmas conference. I decided I would have some fun with the presentation.
Title: Project X
Abstract: For the last 11 months I have been working on a top secret project with a world renowned Scandinavian industry partner. We are now moving into the exciting operational phase of this project. I have been granted an early lifting of the embargo that has stopped me talking about this work up until now. I will talk about the data science behind this big data project and how semantic web technology has enabled the delivery of Project X.
You can find more details of flood defence work in this paper.