1. EMODNET Chemistry 2 Semantic Suggestions Roy Lowry and Adam Leadbetter British Oceanographic Data Centre

2. Semantic Issues Parameter semantic issues encountered during the pilot – Naming of the aggregated products – Inability to aggregate across multiple P01 codes – Difficulty mapping local parameter vocabularies to P01 – P01 scalability issues – Inability to discover a specified contaminant

3. Aggregation Naming Problem – During the pilot a lot of (circular) e-mail traffic concerned the labelling of aggregated parameters Solution – Naming needs to be governed – Governance decisions need to be implemented as a controlled vocabulary

4. P01 Aggregation Issues Problem – Aggregation tools create an aggregated parameter for every P01 code in the source dataset – Different P01 codes used for parameters that are not significantly different (or even not different at all) – Fixes for this (retagging source data or merging channels in the aggregation tool) is both labour intensive and error prone

5. P01 Aggregation Issues Solution – Define each aggregation as a set of P01 codes – Store and serve resultant mapping in the NERC Vocabulary Server – Update aggregation tools to access mapping and use it to dynamically merge channels with different P01 codes

6. P01 Mapping Difficulties Problem – There’s a lot (>28000) of codes in P01 – Finding the code needed for a given local parameter vocabulary term seems to cause a lot of difficulty – Text generated from a semantic model isn’t always intuitive (e.g. [dissolved plus reactive particulate phase] = ‘unfiltered’)

7. P01 Mapping Difficulties Solutions – Mapping based the semantic model (matrix, substance, taxon, gender, organ) rather than the preferred label text – Improvements to the search algorithm in the client (e.g. Addition of ‘excluding’ clause) – Exposure of P01 subsets through NVS2 concept schemes (thesauri) – Training in how to map

8. P01 Scalability Issues Problem – Many contaminants in many different biological entities = a number of P01 codes that is predicted to be unmanageable Solution (not favoured) – Redesign formats to use discrete semantic model not P01 code Different formats for different data types Moves complexity from semantic domain into the data files

9. P01 Scalability Issues Solution (preferred) – Retain P01 as a register of semantic element combinations – Automate concept registration (part of a semantic model-based mapping tool perhaps) – Use NVS V2 concept schemes to expose P01 subsets to make navigation easier

10. Contaminant Discovery Issues Problem – Parameter discovery (CDI interface) is based on P02 – P02 groups contaminants with variable granularity Good for PCBs Not so good for ‘other organic contaminants’ – A search for datasets with cadmium in Mytilus edulis flesh isn’t possible – The nearest is metals in biota, which will give many unwanted hits

11. Contaminant Discovery Issues Possible Solution – Mine the P01 codes in the SeaDataNet file stock into the CDI metadatabase – Use these for drill-down parameter discovery in the CDI search engine

12. Taking This Forward Some of the solutions presented are ODIP pilot candidates Specifications of these are currently vague Not absolutely clear who should be doing what and when Meeting (Liverpool or London if easier) to develop the specifications and an implementation roadmap