Copy Cataloging

Linked Data copy catalogers will perform essentially the same tasks in a BIBFRAME ecosystem as they have traditionally in a MARC ecosystem: searching databases, finding existing bibliographic data, making local edits, checking access points, and saving data into a local system. During a Phase One implementation as defined in Section V above, the only required additional step is to synchronize thin MARC records with the existing ILS. The diagrams below illustrate the steps (workflow) used to perform copy cataloging. For demonstration purposes, OCLC WorldCat is used as an example of an external Linked Data data source (OCLC publishes its bibliographic data in and the BIBFLOW Scribe interface (as discussed in Section VI above) is assumed as a Linked Data cataloging workbench:

Figure 20: Step One of Linked Data copy cataloging workflow

In Step one, the copy cataloger uses the interface to see if a local bibliographic graph already exists for the item being cataloged. If a local graph does exist, a new local Holding is added to the local triplestore. If not, the cataloger moves to Step Two:

Figure 21: Step Two of Linked Data copy cataloging workflow

Step Two involves retrieving data about the item being cataloged from OCLC. This can be performed in one of two ways. Figure 14 in Section VI above depicts a system tested as part of the BIBFLOW project that allows users to scan the barcode of an item and automatically retrieve OCLC graph data based upon the extracted ISBN. Similarly, the BIBFRAME Scribe tool allows a cataloger to manually input an ISBN to perform the same search, or to perform a Title and or Author search. In both cases, the cataloger may be required to disambiguate results, as a single ISBN or search return can reflect multiple Work graphs. This same disambiguation is similarly required in a MARC ecosystem, and does not reflect an additional effort. Once an appropriate OCLC Work record has been identified, the Linked Data cataloging interface retrieves the graph for that resource from OCLC. This graph includes all information currently stored in exchanged MARC records. When a graph is pulled, its data is used to auto-fill all fields in the cataloging workbench for review by the cataloger.

Figure 22: Step Three of Linked Data copy cataloging workflow

Step Three involves using similar lookup functionality to automatically discover URIs for authority entries. Using services such as VIAF, Library of Congress Authorities, and Getty Authorities, catalogers can search for authorities using human readable forms and automatically pull Linked Data representations of the authority, including URIs.

Figure 23: Step Four of Linked Data copy cataloging workflow

Once the cataloger is satisfied with the graph data pulled from OCLC and any made modifications, the final step in the human cataloging workflow is to push the new graph to the triplestore. In the case of items for which there is currently a local bibliographic graph, this involves adding an appropriate bibliographic record to the database as well as required Instance and Holding data. In a completely native Linked Data ecosystem, one in which all systems that surround the library’s cataloging data have been converted to communicate directly with the triplestore, Step Four is the final step in the copy cataloging process. In cases where the cataloger is working in a hybrid ecosystem (prior to the completion of Phase Two as defined in Section VI above), a final, machine-automated step will be required:

Figure 24: Step Five of Linked Data copy cataloging workflow

In cases where the library is currently not operating in a completely Linked Data ecosystem, when a cataloger pushes a new graph to the triplestore (or modifies an existing one), these changes must be propagated to any systems still relying on MARC data. This transaction is handled by a machine process and requires no human interaction.

As illustrated above, transition to a Linked Data ecosystem has no negative impact on the human workflows involved in copy cataloging and will improve efficiency in many cases due to the ability to auto-lookup and create graphs for items. Specific benefits of Linked Data copy cataloging include:

1. Catalogers do not need to search OCLC database separately because the lookup services embedded in the Linked Data cataloging workbench can retrieve both bibliographic and authority data, with associated URIs, and automatically put retrieved data into appropriate fields (auto-populate)
2. Catalogers do not need to have in-depth knowledge of BIBFRAME data model or BIBFRAME vocabularies because the data mapping between Data Source (e.g. OCLC – and BIBFRAME has been done behind the scenes
3. Catalogers do not need to input URIs manually because the machine will record and save them into the triplestore automatically; they just need to identify and select the correct entry associated with a URI
4. Automated methods such as barcode scanning can be used to perform record creation in a fraction of the time currently required

One potential issue stands as a barrier to proper BIBFRAME implementation using the proposed model. (the Linked Data framework used by OCLC) does not differentiate title proper from the remainder of the title, but they are differentiated in the BIBRAME specification. For our implementation, we opted to include the complete title in the BIBFRAME Title Proper element. This approach was taken because a full text search (or index) of a combined title element would return a successful search for any portion of the title. Given the nature of current full-text search capabilities, more discussion about whether multiple title elements are still useful and, if so, how to reconcile OCLC and LOC data will be necessary.

Transitioning to Linked Data cataloging using the proposed model raises the following questions for community consideration:

1. As per the discussion immediately above and given the nature of current full-text search capabilities, more discussion about whether multiple title elements are still useful and, if so, how to reconcile OCLC and LOC data will be necessary
2. How much data is needed in local triplestore? If most of the things can be identified by their associated URIs, and library discovery systems that sit on top of the local triplestore can pull information from external resources, how much data does the library still want or need in its local system?
3. If changes are made to source data, is it necessary to send the revised information back to the sources? If yes, what will we need to make this happen as an automatic process?

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