rjurban VRA2007 matchmaking

A Good Visual Resource Is Hard to Find: 

A Good Visual Resource Is Hard to Find Thoughts on a VRA Matchmaking Commons VRA 2007 Kansas City

Background: 

Background A collection registry & item-level metadata repository hosted by the University of Illinois at Urbana-Champaign Test assumptions of the IMLS/NISO Framework of Guidance For Building Good Digital Collections Enhance visibility & utility of digital collections & content funded by IMLS Research & experiment with interoperability, OAI-PMH Collection identity, metadata normalization & enrichment for specific audiences, portal interface & functional design Collaborative effort of UIUC Library & Library School Period of Performance: Oct. 2002 – Sept. 2007

IMLS-DCC Collection Registry: 

IMLS-DCC Collection Registry http://imlsdcc.grainger.uiuc.edu 169 NLG primary collection records 136 IMLS NLG projects represented

Institutions by Type: 

Institutions by Type Palmer, C., Zavalina, O., & Mustafoff, M. (forthcoming) Trends in Metadata Practices: A Longitudinal Study of Collection Federation. JCDL 2007.

Types of items: 

Types of items Palmer, C., Zavalina, O., & Mustafoff, M. (forthcoming) Trends in Metadata Practices: A Longitudinal Study of Collection Federation. JCDL 2007.

Types of Metadata: 

Types of Metadata Palmer, C., Zavalina, O., & Mustafoff, M. (forthcoming) Trends in Metadata Practices: A Longitudinal Study of Collection Federation. JCDL 2007.

Item Level Metadata: 

Item Level Metadata The ability to reliably share information about VRA works will depend on metadata quality and shareability. Responsibility for metadata needs to be shared by all members of a VRA commons. What level of compliance to standards is sufficient to make the commons work? User needs must drive design. What are the functions that metadata needs to support? What extensions are needed to make a “commons”? VRA 2007 Kansas City

From Quality Metadata to Shareable Metadata: 

From Quality Metadata to Shareable Metadata Promotes search interoperability - “the ability to perform a search over diverse sets of metadata records and obtain meaningful results” (Priscilla Caplan) Is human understandable outside of its local context Is useful outside of its local context Preferably is machine processable VRA 2007 Kansas City

Metadata as a view of the resource: 

Metadata as a view of the resource There is no monolithic, one-size-fits-all metadata record Metadata for the same thing is different depending on use and audience Affected by format, content, and context Descriptive vs. administrative vs. technical, etc.

Characteristics of Shareable Metadata: 

Characteristics of Shareable Metadata Content: the view is appropriate for the resource Consistency: views should use consistent practices within a defined set Coherence: the view is understandable within its use context Context: the view is appropriate for its use context Communication: data providers expose information about metadata creation and maintenance practices Conformance to: Standards Data fields & structures (CDWA, CRM, ISBD) Data Format Standards (XML, etc.) Data Content Standards (CCO, etc.) Controlled Vocabularies (AAT,LCSH etc.) Data Exchange Standards (OAI, Z39.50, etc.) C’s S’s

Using OAI For Matchmaking: 

Using OAI For Matchmaking OAI is a “low barrier” protocol for metadata sharing, however… Only 19% of IMLS National Leadership Grant projects have adopted OAI Lack of technical infrastructure Off-the-shelf systems don’t support (or offer limited support) Sharing metadata not a priority Barriers to Metadata Sharing via the OAI Protocol A White Paper by Sarah L. Shreeves IMLS Digital Collections and Content Project University of Illinois at Urbana-Champaign September 2005 http://imlsdcc.grainger.uiuc.edu/3YearReport/docs/BarriersToInteroperability.pdf VRA 2007 Kansas City

Using OAI for Matchmaking: 

Using OAI for Matchmaking Explicit agreements between data providers, harvesters and service providers will be needed How often should harvests occur? Can harvested metadata be modified? What metadata can be harvested? Can harvested metadata be shared with other harvesters? Harvested metadata Will be Modified

OAI-PMH vs. Distributed Sharing: 

OAI-PMH vs. Distributed Sharing Pros Harvesting records allows service providers to optimize harvested records for local services Can optimize indexes and database infrastructure for large-scale retrieval Currently limited to exchanges of metadata Able to stand between diverse local data sets and external views Cons Local updates need to be re-harvested and integrated into services

From Shareable Metadata to Shareable Assets: 

From Shareable Metadata to Shareable Assets DLF Aquifer Asset Action Experiment http://rama.grainger.uiuc.edu/assetActions Goal was explore “deep sharing” of digital library objects Centralized Metadata - Distributed Assets Uses “actionable” URLs to display multiple image formats (I.e. thumbnail, full size, etc.) and descriptive labels. Image Annotation FOAF Image Schema Personal Collection Building “bookbag” feature Export collected images in multilple formats (PDF, e-mail, RDF, XML, RTF) Metadata Sharing Export records in Dublin Core XML

From Shareable Metadata to Shareable Assets: 

From Shareable Metadata to Shareable Assets Open Archives Initiative - Object Reuse and Exchange (ORE) Objectives: Develop, identify, and profile extensible standards and protocols to allow repositories, agents, and services to interoperate in the context of use and reuse of compound digital objects beyond the boundaries of the holding repositories. http://www.openarchives.org/ore/

The Collections Conundrum: 

The Collections Conundrum How to make a match between users and collections that are not digitized yet? How are “collections” important to VRA users? How to make a match between users and collection which may contain relevant items? What are the collections development policies of a commons?

The Collections Conundrum: 

The Collections Conundrum Dublin Core Collection Application Profile Implications for VRA Core? Collections-level descriptions can tell a user things about items that item-level metadata may lack. What properties are essential to the collection, but non-essential to the item and vice versa? Collections-level descriptions can help users scope their searching. Palmer, C.L., et al. (2006). Collection Definition in Federated Digital Resource Development. http://imlsdcc.grainger.uiuc.edu/docs/ASIST06FinalSubmittedVersion.pdf

Slide20: 

Richard Urban Graduate School of Library & Information Science University of Illinois at Urbana-Champaign rjurban@uiuc.edu http://isrl.uiuc.edu/~rjurban