SCONE: reusability, granularity and collection strength

1. SCONE: reusability, granularity and collection strength Gordon Dunsire & Dennis Nicholson Presented at the Collection Description Focus, Workshop 2, Birmingham, 8 Feb 2002

2. Entity relationships • Entities defined in the Heaney analysis • Collections; Locations; Agents; Subjects • Relationships between entities within a single Collection Level Description defined • E.g. Administers, Owns, Describes • Relationships between entities in multiple CLDs defined in SCONE • hierarchical (sub and super entities) • multiple super relationships as well as multiple subs

3. Relational database Location Name Address Town … [Key] Is Administered By [Location Key] [Agent Key] Opening Hours … [Key] Agent Name History … [Key]

4. Collection Level Description Agent A Location Collection Agent B Catalogue (Collection)

5. Granularity Parent/Super Entity Parent/Super Entity Entity (Collection, Agent, Location) Child/Sub Entity Child/Sub Entity

6. Coextensivity and cascade • Entity relationships within a single CLD should be at the same level of granularity • Where a single CLD requires data from different levels, the Collection record must be linked hierarchically to appropriate Collection records at those levels. • Data is then cascaded down the hierarchy from higher to lower level CLDs.

7. Virtual CLDs Collection A Location A Collection B Collection C Location C

8. Reuse & ‘virtual’ duplication • Minimise duplication of stored data • Easier to maintain currency • Improved accuracy • Improved consistency • Reusability • Automatic within SCONE • Better ‘completeness’ of exchange records • Related services • Shared data maintenance; e.g. SLIR, SWOP, ESH

9. Collections • Hierarchies can be complex! • But ‘physicality’ is a constraint • Example: • A collection of books by and about Robert Burns can be a sub-collection of the ‘library’ collection where it is held, a sub-collection of a ‘Complete Burns’ distributed collection, and a sub-collection of a ‘Scottish poetry’ distributed collection. • External content standards • Physical description, Identifiers (UKOLN)

10. Agents • ‘Strict’ hierarchy; no multiple super-agents • Example: • A person (Agent A) is a member (sub-agent) of a library team (Agent B), which is part of (sub-agent) of a library services department • External content standards • Used: AACR2; AAAF • Possible: DNB; membership lists

11. Locations • ‘Strict’ hierarchy; no multiple super-locations • Example: • A shelf (Location A) is contained in (sub-location) of a library room (Location B), which is part of (sub-location) of the library building. • External content standards • Used: OS gazetteer • Possible: GIS datasets

12. In other words, SCONE • Stores data to maximise efficient and effective maintenance. • Presents complete Collection Level Descriptions by integrating relevant data. • Produces flexible output for sharing data with other systems. • Accommodates extensions to the depth, coverage and detail of Collection Level Descriptions

13. SCONE and Collection strength • Conspectus; SCURL: Collaborative Collecting and Dynamic clumping. But: subjective; labour-intensive? • SCONE: Alternatives: Brief tests? List checks? Shelf scans? Automated methods? External evaluation? Citation analysis? User based techniques (Circulation, ILL, DD statistics etc.) ? Professional judgment – key to all? • Interim conclusion: professional judgement in CCD/ user needs environment: agreed methods/peer review • But: an unhelpful, inherently subjective concept? • Strength: strong for who, for what purpose? (CURL) • Disaggregate idea to give users/staff clearer guidance?

14. Collection Strength: Elements • Elements: • What does it all add up to? Compared to what? • Since when? Current intensity? Responsibility? • What about audience level? Experience level? Quality? • Small but significant collections? The strength of distributed collections? Subjective helpful if explicit? • User and Collector needs? What? Why? When? • Browsing in ‘strong’ collections • Dynamic clumping (narrow the focus); And? • In-depth characteristics of a collection?

15. Other Dimensions… • Granularity (as ever) complicates things: • At which level of subject granularity do we measure a collection strength (or element)? • How can we ‘telegraph’ (describe) a strength measured at one level at a higher level? • Does a strength cascade down to a subject sub-division? • Further aspects of ‘strength’: • Aggregation ‘type’? (e.g. Granular characteristics? Passive or active collecting? Pre-formed or dynamic? Levels of ‘cohesion’?) ; Can the ‘strength elements’ of dynamic aggregations be dynamically generated?

16. Collection strength: Reusability • Barriers to reusability: • Need agreement on ‘strength’ elements, how measured and described, what their valid uses and limitations are • Need a common subject scheme or at least a common spine for a terminology mapping (HILT; Consensus) • A HILT2 would involve terminology mapping but ask: • Does ‘map’ need single hierarchical scheme as a ‘spine’ • Which is best long-term option – mapping or single scheme? • Consensus still the key – service staff must be convinced • More on HILT at next workshop

17. Thank you! • g.dunsire@napier.ac.uk • d.m.nicholson@strath.ac.uk • http://scone.strath.ac.uk/ • http://scone.strath.ac.uk/service/index.cfm • http://www.ukoln.ac.uk/metadata/rslp/model/ • http://hilt.cdlr.strath.ac.uk/