Metadata Research Focuses: Moving Images

Increasing Access to Archival Information About Moving Images

Through Linked Open Data
Moving Images Metadata

Our research process includes two major steps: for the first part, we have been examining archival descrip0ve and authority standards to see what informa0on may be useful as linked data. We are also looking at finding aid and authority exemplars, which we pulled from major sources of archival finding aids such as the OhioLink EAD repository. After reviewing standards and sample finding aids and authority records, we iden0fy common elements among them and consider the possibili0es for linking archival informa0on to linked open data proper0es—we are looking at both major access points and poten0al hidden access points not currently able to be linked easily because of how they are currently encoded.

In the second part of the research, we have iden0fied datasets that have poten0al to be relevant to users of archival collec0ons. These datasets are analyzed to discover what ontologies, metadata schemas, and/or applica0on profiles that are used. We also look at sample records and any documenta0on that we can find, using informa0on found on the Data Hub. Then, we attempt to crosswalk across datasets, to see how well a par0cular type of informa0on will match. We use categories common to ontology alignment such as equivalent, close match, broad match, narrow match, and related. Through this process, we iden0fy the major classes and proper0es useful to archives data.

This is one example of a mapping table that is generated as a result of the analysis we’re doing with the standards, ontologies, and datasets. In this mapping of EAD to FOAF, which focuses on personal, family, and corporate body names, we can make a couple of general statements about how well these two data models relate. First, we can say that for the EAD data elements , , and , at the class level they are narrower than the closest FOAF class equivalent, except in the case of Person. Matching to the property level, however, FOAF tends to be narrower in scope than the closest equivalent in EAD. Matching names found in EAD records to the property foaf:name would provide a basic level of interoperability, but would not differen0ate among first, last, and nicknames. Thus, EAD and FOAF are not completely equal in the granularity of their data models. Another observa0on that we have made in EAD is that there are several places in the EAD record where names can be found, but which are not and cannot be tagged as such, such as in the ScopeContent and BiogHist tags. The poten0al to link addi0onal names to external datasets is therefore untapped at this 0me, but revisers of the standard may wish to consider adding such func0onality to future versions of EAD.

This work was supported by a grant from IMLS. It is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.