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ERA-Nets as Information Sources. Gerry Lawson, UK Natural Environment Research Council. The BiodivERsA ERA-Net. Information WP1. Best Practice WP2. Strategy for Common Call WP3. Links with Developing Countries WP4. Coordinated Call for Proposals. Pan-European Research (art 169).
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ERA-Nets as Information Sources Gerry Lawson, UK Natural Environment Research Council
The BiodivERsA ERA-Net Information WP1 Best Practice WP2 Strategy for Common Call WP3 Links with Developing Countries WP4 Coordinated Call for Proposals Pan-European Research (art 169) Management, information and dissemination WP5
Joint/common calls • (fixed for 2005/2006) 32 % all 4 • Joint activities 3 all • Common strategic issues 2 all • Information exchange • & best practices 1 Coordination of national Programmes ERA-NET - Facts and Figures Level of ambition of selected CA projects
Activity Collation Problems • All ERA-Nets collect Programme information • Most collect information on Projects • A few maintain databases of Programmes • A very few include databases of Project info • Some collect data on Facilities and Infrastructures • None collect information on Project Outputs (?) • Most have problems with Classification • Most have problems with Gap Analysis • Most have problems Analysing Spend (salaries/overheads/shared grants/allocation to keywords) • Many don’t consider studentships • Some don’t record EU Region or country of work.
Yet more problems • Programme databases have little detail & defy classification • Several countries have no Thematic Programmes • Project databases are structured differently in each country. • Each country has its own classification system and wont use anyone elses! • Re-classification is time consuming and subjective. • Few organisations split funding across classifiers. • Machine classification of abstracts (indexing) still needs subjective editing. • Context searches (Google, Autonomy, Collexis) are avaiable but don’t help much with classification.
Which is why we need Ontologies? • An ontology is a formal knowledge organization (representation system). • It contains concepts, information about these concepts, relations between these concepts • and instances, • and it contains information about the relations between instances and concepts
Too many ontologies? Existing Thesauri and Knowledge Organization Systems (KOSs) Dedicated KOSs e.g., ASFA thesaurus e.g., the Multilingual Forestry Thesaurus e.g., the Sustainable Development website classification e.g., biological taxonomies such as NCBI and ITIS Other thematic thesauri Non-dedicated KOSs CABI Thesaurus AGROVOC NAL Thesaurus GEmetGEMET
What is the starting point? • FAO maintains the multilingual thesaurus AGROVOC since the early 80s • Other consistent thesauri are maintained by CABI in England and the National Agricultural Library in the States • Various other knowledge organization systems are scattered around the world • The existing systems are language biased with English as the leading language – but GEMET is multilingual • BiodivERsA is using 960 terms in the CBD controlled vocabulary (thesaurus) and creating an Authority File with synonyms. • It is hoped that keywords allocated to each abstract will allow clustering & classification.
Using CERIF for a Programme Database. i. Geographical criteria : Applicant nationality Click add after each selection Choose the country from the list
Classifications and & keywords (free/controlled) Research Topic Main scientific disciplines Choose specific fields Click add after each selection
And specific detail of Programmes Next steps • Populate with projects from 19 members (Dec 06) • Extend to non-members with tropical biodiversity projects (Feb 07) • Use Indexing to apply keywords (via Authority File – Feb 07) • Invite authors to update & add cvs (Mar 07) • Confirm gap analysis (Mar 07) • Add research outputs and facilities (June 07) • Liaise with other relevant ERA-Nets (e.g. SKEP, CIRCLE, MARIN-ERA) and NoEs. • Participate in any EU Research Ontology Initiative – e.g. with CORDIS. www.eurobiodiversa.org