What makes a good use case?
- which of them is really linked data enabled, vs. what you could do with MARC if put in a big database
- what can be done easily with linked data, even if it could be done without
- examples tying library data together with other information
- and working across institutions
What intersections of our data sources will be strong enough to support compelling use cases?
We need to choose a key set of use cases that address the challenges articulated in the grant proposal for the project. Here are some specific points that we want to make sure that the use cases address:
- Pragmatic value. They have real value to our core constituencies: librarians, researchers, teachers, students, etc.
Community added-value. They leverage the unique value that librarians and scholars add to materials when they select, annotate, or reference the resources.
- Cross-institutional data. They clearly demonstrate the value in combining data from our three different institutions - ideally in a way that shows how that value will grow as more institutions join in.
- Leverage existing data and services. They leverage existing efforts in this space
- Integration into the Web. They show how research libraries can integrate with existing popular and useful Web sites and services, e.g., Wikipedia.
- Cross-discipline. They show examples from a variety of disciplines.
- Help core missions. They demonstrate value for teaching and learning, and research.
- Multi-data. They cover a broad range of scholarly information resource types.
- Unusual data. They show how non-traditional data can be useful.
- Media "photogenic": They clarify to the mainstream media the value of LOD and this project, and excite that media about the prospects
- They show interesting ways to use the aggregated data for analysis or visualization.
- They take advantage of data on how the materials are being used.
We need to be careful to not put in effort in areas where other projects are already working.
Virtual Collections (3,11,35)
Build a virtual collection from items across institutions, regardless of their original collection and metadata.
Metadata Assignment (24)
Assign information about an item in a Linked Data way, such as subject/tag. A potential implementation strategy for designating virtual collections.
Discovery of Related Items (12,19,21,22,23,25,29,38,42)
Using the graph of relationships between items, improve:
- discovery algorithms
- discovery interfaces
Based on information about the Items:
- geo/temporal provenance and topic
- other metadata
Highlight specific people (6)
Given a set of people, highlight them when they are referenced from Items (eg faculty authors)
Display relationships between people (9)
Given a set of people and their relationships to each other, display the relationships in relevant contexts
Display intersection of metadata about people (42)
Given a set of people and their relationships to other objects, use the metadata from those objects to generate sets of people and display those sets in relevant contexts
Improve Discovery based on Usage (1,16)
Given usage information about a set of objects, improve discovery and ranking of those objects in appropriate interfaces.