1. Resource Curation and Automated Resource Discovery

2. NIF Resources NIF is cataloging websites that house information about databases, atlases, software tools, data, transgenic mice and other things that we consider of value to the neuroscience community.

3. Definition of Resource Individual resource boundary: shall be considered an individual resource if it is maintained by a single entity, and has the properties of one or more individual web pages that are related by a theme and html links.

4. Resource Nomination Registry (4500) Registry (4500) Public Registry (2100) Public Registry (2100) NIF Web (499,952) NIF Web (499,952) Level 2/3 (24) Level 2/3 (24) User Feedback *Automated tools Web Crawl Registry Subset Nomination Check: -Links -Annotation -Vocabulary *Automated updates Level 2 tools *In Development

5. Resource is Nominated NIF Staff, Contact at Meetings, Web Form Resource is Nominated NIF Staff, Contact at Meetings, Web Form In NIF already? Assign Metadata -short name, long name, url -description (short description 1-3 sentences, longer description) -parent organization (physical location, university) -support (grant numbers) -keywords (species, technique, structure, age, level, disease, topic) Assign Metadata -short name, long name, url -description (short description 1-3 sentences, longer description) -parent organization (physical location, university) -support (grant numbers) -keywords (species, technique, structure, age, level, disease, topic) Decision: Should it be included? Assign resource type Do not include Keep Record Do not include Keep Record

6. Resources Difficult to Categorize Link aggregates Large organizations (NIH) Poorly documented databases Private data sites Clinical trials that are still recruiting –Experimental protocol Commercial entities Journals –JOVE –supplemental materials

7. CINdy the resource curation tool

9. Resource Ontology (BRO) Data Resource: provides access to data; database, atlas, book Software Resource: software programs or source code Material Resource: reagents, tissue samples or organisms Funding Resource: grants or contracts Training Resource: educational materials, training programs Job Resource: employment opportunities People Resource: access to individual people’s web sites

10. NIF Service vs BRO Service

11. Solutions Consolidating Classes Synonyms where appropriate: ex. Material storage service vs. Material storage repository. Temporary mapping, where appropriate –*Deprecated terms must be maintained* Data loss Moving forward with a joint descriptive terminology!

12. Evolution of the NIF Resource Ontology ObjectFunctionTarget Audience Data TypeData Format Materials -Biomaterials -Reagents Software People Grants Jobs Information Service -Storage -Production Funding Job Service Community- building General Kids Student Medical Researcher Structured -Database -Atlas Unstructured -Journal -Webpage Text RDF Text Picture Video

14. Resource Boundary? Software Library –Software tool Plugin: I2B2 Our solution: use url as a uniqueness qualifier –Our problem: a single url may house several resources –Individual plugins can have individual urls

15. Boundary cont. Individual resource boundary: shall be considered an individual resource if it is maintained by a single entity, and has the properties of one or more individual web pages that are related by a theme and html links. Solution to random boundary problem: Human Curator

16. Issues of Scope Single line or short paragraph + keywords –Resource discovery problem *Stanford ontologies description is very short (as are many) finding this resource by keyword will be difficult unless we index the content of the website. Data dump –Small vs. Large databases –Updates

17. Internal referencing Stanford example: –License: “same as bioportal” – does not match any license types in any list. –Problem: non standard terminology, reference to another project (no url), can create loops also true in publications: ex., used same protocol as paper X, which used the same protocol as paper Y –Automated text mining tools have a hard time recognizing these

18. What can we gain from automated systems? Basic information: Name, url, contact info Some keywords Some descriptive text No resource boundary No resource description

19. How do we help the computers? Common naming project (neurocommons) http://sharedname.org/page/Main_Page Automated uri’s Community building: –Shared data models –Shared ontology –RDF entity tags? (mouse vs mouse)