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Cluster Collections

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Authors: Gordon Dunsire , Karen Coyle

Collections Cluster


Specific bibliographic resources are the focus of most interactions between an individual user and a library service. The metadata required to support those interactions are therefore determined by the principles and practice of item-level description.

The environment which supports library services is the collection, so metadata that apply to the collection as a whole are required. These can be determined by collection-level description.

All types of library collection require metadata, and not just those designated as "special" or with specific titles. Collections may have collection-level granular structure; that is, sub-collections which themselves have sub-collections. Collections may overlap; an item can belong to more than one collection. For example, the entire library stock may be treated as a collection for acquisition and preservation processes, while financial control might be exerted separately for each sub-collection if based, say, on academic faculty budgets. Collections of different carrier types are typically managed with different storage systems and lending privileges. Different item-level metadata schema and formats may be used for different collections, such as music, manuscript, image, and film.

Topic in the Context of Linked Data

The fine granularity of linked data can improve interoperability between heterogenous collection-level metadata created by multiple institutions with different functional requirements. Linked data from non-library sources, such as transportation networks, can enrich user-centred information about obtaining items from within a collection. Linked data from multiple libraries can provide information about alternate access to the same item held in different collections. Linked data bridges different levels of granularity; in particular, it is easy to integrate metadata about a collection as a whole into metadata about each item in the collection, using "is part of/contains" links between item and collection.

Scenarios (Case Studies)

This cluster is based on the following submitted use cases and scenarios:

[1] Use_Case_AuthorClaim

  • Experts categorise documents to form subject-based collections.

[2] Use_Case_Community_Information_Service

  • Users identify and classify collections of special interest to the community.

[3] Use_Case_Nearest_physical_collection

  • Users identify the nearest location of a physical collection containing the item they wish to obtain.

[4] Use_Case_Digital_resources_with_access_restrictions

  • Users identify restrictions on access to online resources at all stages of resource discovery involving local and remote systems.

[5] Use_Case_Library_Address_Data

  • Users have a mobile device application which lists libraries in the vicinity of the current geo-coordinates, with information about each library, including address, type (e.g. special, public, university library), subject coverage, access conditions (open to all, or restricted to staff and/or students), opening hours, availability of WiFi access, study places, and coffee/soft drink vending machines, etc., and links to navigation software on the mobile device, the library online catalogue, etc.

[6] Use_Case_Collection-Level_Description

  • Users have a single point of access to retrieve information about collections held by different organizations in different physical and electronic locations, including collection scope, strength, access conditions, and contact details.

Scenarios (Extracted Use Cases)

Vocabularies and Technologies



Problems and Limitations

Missing Vocabularies

Many useful collections are not described by any metadata. Libraries with many special collections may only supply minimal metadata such as title and provenance note. Collection-level metadata are often unstructured, consisting of undifferentiated, descriptive text with little or no vocabulary control. Metadata about collection locations can be incomplete, or disconnected from resource discovery metadata.

Data incompatibilities or lacks

There are very few comprehensive data sets based on directories of libraries, including address and other location information, and contact and other agent information. The information tends to be fragmented into consortia, sector, and subject-based groupings.

The International Standard Identifier for Libraries and Related Organisations (ISIL) offers a method for assigning an identifer to a library organization. Organizations do not always register individual physical branch libraries. The ISIL Registration Authority coordinates national agencies for assigning identifiers. There is no consolidated list of libraries and codes, and each agency uses a different interface to list or search national identifiers.

There are some national services using identifiers for libraries, but they generally do not interoperate.

There is no standard typology of memory institution types. Existing typologies are tied to one of the three primary entities in collection-level description: Collection itself, Location (sub-entities physical and electronic), and Agent (sub-entities person and corporate body/family). Typologies may be based on material format of the items in the collection, administration or curation of the collection, architecture and type of building housing the collection, audience level, subject, etc. Developing a single typology that fits all entities is difficult.

Community guidance/organization issues

The definition and identification of "What is a collection?" may vary between organizations, sectors, and domains. The principle of "functional granularity", by which a collection is identified by an organization for functional purposes (administrative, financial, access conditions, format, etc.), encourages differences in treatment at the local level.

Technology availability/questions

Very few library resource discovery systems support collection-level metadata or integrate it with item-level metadata.