Demonstrates scholarly communities learning from one another across institutions

This divides up by subject; others are possible

5 dw

raises the question of alignment of subject terms - library resources use LCSH but (often in unique combination) but few other resources do. OCLC Fast may help. jcr

Also, lib materials often have multiple subject headings.

Could do textual analysis perhaps.

There's work to do here. It may be considered arbitrary.

Heavily focused on the UI. How central should that be to the use cases.

How much should people be able to say about the collection itself and not just its items. Or info about the items but specific to the collection.

Why would I want this? dw

seems far afield.

Out of scope.

Maps are a gnarly type. And how do we get the geolocated items? And this isn't very fresh. Is there a way to show relations among the pins? Or something? - dw May be possible to do autotagging by place names but may not be reliable, and are we tagging author origin, publisher, aboutness? jcr

Perhaps restrict their viewing to a geo location.

We'd need a gazetteer.

Nasty data

Not linked data base

requires a commitment to maintain information on departed faculty in other systems of record, or taking on that task in the library. jcr

we'd be ok with just current data

good one

integrates person data, so good

subject terms used by the media are notoriously different from those used by academics, so requires interpretation and/or mapping, as well as having generalization/granularity issues. jcr

faculty profiling info - too close to what VIVO et al do.

Maybe looking for a topic, come up with results, and find people.

If you a topic, can you suggest a reference librarian.

low priority

LD enough?

note comment above that non-library resources are rarely if ever tagged with LC terms. jcr

cross ref. to #29-31

Doesn't demonstrate linked data, and similar to a couple of others - dw

Population across the three institutions is big enough.

You'd have to log in. (Shelf.io does that)

A top priority for Stanford and something they want to get out of this grant

Privileged or not privileged? My personal list or public?

Great area to explore

A third party app might do this, with the three systems incorporating

(I don't understand this - dw)

As it stands this use case doesn't seem to leverage our work. If the method by which one decided which "John Smith" you wanted used other information about the person, their works, their geography, etc. then it would seem to fit. Still seems a somewhat standalone tool though – sw

I would like to be able to ask questions about the relationships among library data using something like natural language (although I'd be happy to accept some common sense restrictions) and get back interesting results. For example,

"What books were written by Cornell biologists on topics that Harvard and Stanford biologists rarely write books about?"

"What books are available about communication technology that don't use 'Communication' in their title or subtitle?"

"Create a timeline of science books that charts them by how many of those books have illustrations."

"Find all the anthologies that have chapters by both Marshall McLuhan and Neil Postman."

"Create a table that shows how many genetics books were published in England per year versus how many were published in the United States."

"Find me books about Christian Fundamentalism read (or assigned) in Divinity schools in the 1990s but less so after 2000."

"Show me chronologically the usage in medical schools of books under the headings of both vaccination and autism."

"Map by publisher location the clustering of books about American slavery since 1640."

(Library Graph)

(We could limit the NLP issue by creating a pick list of operations, relations, and outcomes. Or maybe there's an Open Source NLP library we could use. I dunno. - dw)

I think the NLP part of this is too much to bite off. I think it would be a reasonable goal for this project to use a structure query language to express and then answer these queries, I think the NLP part would be extremely cool but would need NLP expert collaborators – sw

Keep an eye out for an NLP person who might want to hook up an NLP front end to this, for a demo.

DELETE. **MERGED with 24** Expand on Cornell's Curated List of Library Resources (CuLLR)

I would like to be able to tag and group resources of a specific type, matching some of the affordances of a physical library in the virtual world. Examples include:

• identify books on the virtual shelf of engineering reference handbooks
• identify "classic texts" in physics/astronomy/chemistry
• identify a "reference collection" for entomology

What about extending the use case to inclusion of non-local materials? – sw

See #24

5 (dbk)

5 (sw)

aka LD-powered CuLLR for SearchWorks

ha ha! I added a similar comment to #18. Maybe merge these? – sw

Will use CuLLR

So I can uncover relationships and knowledge that were otherwise hidden.

Maybe do this more as a specific narrative?

SPARQL-based OPAC + directory + circ reporting?

Important

Great if we can come up with some good UI, or subset UI that does interesting things. Is there an existing UI to drop on top of a SPARQL endpoint? We don't know of any.

Make this use case more specific? And we need some concrete examples.

Can we do inferencing?? Make that its own use case?

I'd like to be able to query which library resources were used in courses (as noted by syllabi, reading lists or course reserves) and compare that to a collection's holdings. (This may be at my or another institution)

more specific case of #8

combine with 8. drop 8.

What else do we have that is EAD-related?

#14 would also rely upon decomposition of EAD – sw

I like this one as it uses relatedness along different axes combined with type taxa and and entity – sw

Where is the data linking publications to equipment or facilities? – sw

How do we infer dataset use where there is no citation? – sw