these use cases are work in progress
Building on and distilled from the preliminary use cases and a revised subset , this page represents a further refined set of use cases to guide the ontology and engineering work for the project. The use cases divide into six "clusters" reflecting the data available to research institutions and libraries, and the core LD4L mission of leveraging the intellectual input of librarians, domain experts and scholars as they produce, curate and use scholarly information resources.
Cluster 1: Bibliographic + curation data
Use Case 1.1: Build a virtual collection
Example story: As a faculty member or librarian, I want to create a virtual collection or exhibit containing information resources from multiple collections across multiple universities either by direct selection or by a set of resource characteristics, so that I can share a focused collection with a <class, set of researchers, set of students in a disciplinary area>. This use case is focused on individual creation of a set of resources – a virtual collection or exhibit – along with descriptive information for the collection and possible arrangement and annotation of resources in the collection. The base use case is that any virtual collection will be publicly accessible and thus authentication is required only for user creating the collection (and not for users of the collection). The inter-institutional aspect of this use case is not supported by current systems. It is expected that the collection URI will support both human and LD views.
Use Case 1.2: Tag scholarly information resources to support reuse
Example story: As a librarian, I would like to be able to tag scholarly information resources from one or multiple institutions into curated lists, so that I can feed these these lists into subject guides, course reserves, or reference collections. I'd like these lists to be portable (into Drupal, into LibGuides, into Spotlight! or Omeka, into Sakai, e.g.) and durable. I'd like these lists/tags to selectively feed back into the discovery environment without having to modify the catalog records. This use case is similar to 1.1 in a number of ways, and perhaps the data model would be the same. However, the likely scale of tagging is much larger (perhaps selection of O(100,000) items to populate a virtual subject library from the central library catalog) and does not include the need for detailed curation (textual annotation, ordering, structure, description). It is expected that such tagging would also be maintained/curated over long periods whereas virtual collections may be disposable or ephemeral. It is also expected that creation and maintenance might be a collaborative process. There are possible ties to shared selection work such as that between Stanford and Berkeley, and between Columbia and Cornell.
Cluster 2: Bibliographic + person data
Use Case 2.1: See and search on works by people to discover more works, and better understand people
Example story: As a researcher, I'd like to see / search on works <by, about, cited by, collected, taught> by University faculty <in an OPAC, profiles system>, to discover works of interest based on connection to people, and to understand people based on their relation to works. Example story: As a researcher, I’d like to see a list of works from the most prolific authors in my field at my institution and at other institutions. This use case is demonstrates pivoting on combined profile system and catalog data, perhaps even between systems. Need to be careful to distinguish demonstration of this use case from the faculty finder functionality of existing profile systems. Must understand how much catalog data adds (perhaps more in non-journal disciplines) and value of cross-institutional data.
Cluster 3: Leveraging external data including authorities
Cluster 4: Leveraging the deeper graph (via queries or patterns)
Cluster 5: Leveraging usage data
Cluster 6: Three-site services
Earlier use cases work
All child pages (delete when finished messing about with this...
