SLiDInG 6

Today, the Semantic Web Lab hosted the 6th Scottish Linked Data Interest Group workshop at Heriot-Watt University. The event was sponsored by the SICSA Data Science Theme. The event was well attended with 30 researchers from across Scotland (and Newcastle) coming together for a day of flash talks and discussions. Live minutes were captured during the day and can be found here.

I gave a talk on the successes and challenges of FAIR data. My slides are embedded below.

Congratulations Qianru Zhou

This morning Qianru Zhou successfully her PhD thesis “Ontology-driven knowledge based autonomic management for telecommunication networks: Theory, implementation and applications”, receiving minor corrections. Congratulations!

Supervisors:

External examiner: James Irvine (University of Strathclyde)

Internal examiner: Mauro Dragone (Engineering and Physical Sciences)

 

UK Ontology Network 2018

This week I went to the UK Ontology Network meeting hosted at Keele University. There was an interesting array of talks in the programme showing the breadth of work going on in the UK.

I gave a talk on the Bioschemas Community  (slides below) and Leyla Garcia presented a poster providing more details of the current Bioschema Profiles.

The UK Ontology Network is going through a reflection phase and would like interested parties to complete the following online survey.

 

Bioschemas Samples Hackathon

Last week the Bioschemas Community hosted a workshop. The focus of the meeting was to get web resources describing biological samples to embed Schema.org mark up in their pages. The embedded mark up will enable the web resources to become more discoverable, and therefore the biological samples also.

I was not able to attend the event but Justin Clark-Casey has written this blog post summarising the event.

NAR Database Paper

The new year started with a new publication, an article in the 2018 NAR Database issue about the IUPHAR Guide to Pharmacology Database.

  • Simon D. Harding, Joanna L. Sharman, Elena Faccenda, Chris Southan, Adam J. Pawson, Sam Ireland, Alasdair J. G. Gray, Liam Bruce, Stephen P. H. Alexander, Stephen Anderton, Clare Bryant, Anthony P. Davenport, Christian Doerig, Doriano Fabbro, Francesca Levi-Schaffer, Michael Spedding, Jamie A. Davies, and {NC-IUPHAR}. The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY. Nucleic Acids Research, 46(D1):D1091-D1106, 2018. doi:10.1093/nar/gkx1121
    [BibTeX] [Abstract] [Download PDF]

    The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb, www.guidetopharmacology.org) and its precursor IUPHAR-DB, have captured expert-curated interactions between targets and ligands from selected papers in pharmacology and drug discovery since 2003. This resource continues to be developed in conjunction with the International Union of Basic and Clinical Pharmacology (IUPHAR) and the British Pharmacological Society (BPS). As previously described, our unique model of content selection and quality control is based on 96 target-class subcommittees comprising 512 scientists collaborating with in-house curators. This update describes content expansion, new features and interoperability improvements introduced in the 10 releases since August 2015. Our relationship matrix now describes ∼9000 ligands, ∼15 000 binding constants, ∼6000 papers and ∼1700 human proteins. As an important addition, we also introduce our newly funded project for the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb, www.guidetoimmunopharmacology.org). This has been ‘forked’ from the well-established GtoPdb data model and expanded into new types of data related to the immune system and inflammatory processes. This includes new ligands, targets, pathways, cell types and diseases for which we are recruiting new IUPHAR expert committees. Designed as an immunopharmacological gateway, it also has an emphasis on potential therapeutic interventions.

    @Article{Harding2018-GTP,
    abstract = {The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb, www.guidetopharmacology.org) and its precursor IUPHAR-DB, have captured expert-curated interactions between targets and ligands from selected papers in pharmacology and drug discovery since 2003. This resource continues to be developed in conjunction with the International Union of Basic and Clinical Pharmacology (IUPHAR) and the British Pharmacological Society (BPS). As previously described, our unique model of content selection and quality control is based on 96 target-class subcommittees comprising 512 scientists collaborating with in-house curators. This update describes content expansion, new features and interoperability improvements introduced in the 10 releases since August 2015. Our relationship matrix now describes ∼9000 ligands, ∼15 000 binding constants, ∼6000 papers and ∼1700 human proteins. As an important addition, we also introduce our newly funded project for the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb, www.guidetoimmunopharmacology.org). This has been ‘forked’ from the well-established GtoPdb data model and expanded into new types of data related to the immune system and inflammatory processes. This includes new ligands, targets, pathways, cell types and diseases for which we are recruiting new IUPHAR expert committees. Designed as an immunopharmacological gateway, it also has an emphasis on potential therapeutic interventions.},
    author = {Harding, Simon D and Sharman, Joanna L and Faccenda, Elena and Southan, Chris and Pawson, Adam J and Ireland, Sam and Gray, Alasdair J G and Bruce, Liam and Alexander, Stephen P H and Anderton, Stephen and Bryant, Clare and Davenport, Anthony P and Doerig, Christian and Fabbro, Doriano and Levi-Schaffer, Francesca and Spedding, Michael and Davies, Jamie A and , {NC-IUPHAR}},
    title = {The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY},
    journal = {Nucleic Acids Research},
    year = {2018},
    volume = {46},
    number = {D1},
    pages = {D1091-D1106},
    month = jan,
    OPTnote = {},
    OPTannote = {},
    url = {http://dx.doi.org/10.1093/nar/gkx1121},
    doi = {10.1093/nar/gkx1121}
    }

My involvement came from Liam Bruce’s honours project. Liam developed the RDB2RDF mappings that convert the existing relational content into an RDF representation. The mappings are executed using the Morph-RDB R2RML engine.

To ensure that we abide by the FAIR data principles, we also generate machine processable metadata descriptions of the data that conform to the HCLS Community Profile.

Below is an altmetric donut so you can see what people are saying about the paper.