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Batch processing at Columbia is managed centrally by Systems personnel scripting processes directly into the Production server. Scheduling of all batch processing (including Cron jobs) is easily coordinated. Large batch processing jobs at Cornell are also handled by Systems personnel but a good amount batch processing is conducted by technical services personnel who have defined batch job responsibilities. With this model, record loads are easier to coordinate with the arrival of material shipments. The locally developed LStools is used along with the Strawn tools "Location Changer" and "Record Reloader" “Location Changer” and “Record Reloader” to load and extract files.
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Notable at Columbia is that the batch processing personnel in LITO are in the Digital Programs and Technology Services section. Monographs Processing Services and Monographs Acquisitions are the central technical services operations of the libraries and the beneficiary client of many batch processes. MPS and MAS are in the Bibliographic Services and Collection Development section. Batch processing and technical services therefore operate in different divisions. The East Asian technical services unit reports to the Director of the C.V. Starr Library, reporting to the AUL for Collections and Services, yet another division. Additional batch processing and reporting needs may arise from the technical services units of Barnard College and the Health Sciences Libraries that share the same catalog and fall outside the libraries' libraries’ organizational structure. The time resources of Columbia's Columbia’s batch processing staff in LITO are highly utilized for multiple reporting and project development efforts across all four divisions of the Libraries.
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An extensive listing of all batch jobs at Columbia and Cornell exists in the Batch Inventory spreadsheet and there are links to detailed process descriptions in the Outline. One of the fundamental differences in the use of MARC records for approval receipts is that Columbia creates Purchase orders and line items as part of the load whereas Cornell loads only bib and holdings records. Reports of each load arrive as emails to acquisitions staff. Duplicates that are detected via ISBN matching are manually resolved by an MPS supervisor and records are merged. Frequently this requires the deletion and recreation of line items in order to delete the duplicate record. Columbia uses Voyager operators named with the vendor code to display in the history as the creators of the bibliographic and holdings records. Approval items load with the default "sho" “sho” locations. Shelf ready approvals load with locations and items, a report of item barcodes is sent to acquisitions staff who scan them as soon as possible to ensure the OPAC reads "In “In transit to library" library” rather than "Not “Not checked out"out”.
The approval records for Columbia's Columbia’s major vendors (YBP, Casalini, Aux Amateurs and Harrassowitz) are loaded via a scripted cron job, and the records can appear in the catalog before the materials arrive in acquisitions. LTS staff at Cornell is able wait until materials are received to load the records.
Export of Columbia's Columbia’s records to OCLC takes place every Wednesday for records last edited in the week 10 days before export (it is assumed all edits are by then complete). Cornell sends a nightly export of new cataloging which are triggered by a cataloging statistic in the 948 field. OCLC keys are added as 035 fields from a return report for both libraries. Columbia sends a separate file for East Asian titles as they also load institutional records. Many record sets have a 965 marker that serves to enable easy selection and collection identification and to apply the policy of not uploading certain eresource collections to OCLC. Cornell uses an 899 field for aggregating vendor packages and a 995 field to prevent export. Columbia excludes from export EL 5 preliminary records processed for Precat/Offprecat while Cornell includes records with EL 3, 5 and 8 in its uploads.
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There are multiple inter-dependencies at both institutions listed in bullet points in the Outline. At Columbia, units from all four administrative units depend on the LITO staff either for batch processing, financial and voyager reporting or system development. As a result, there are competing priorities for the time and expertise of LITO personnel. LITO in turn depends on staff in CERM and technical services (including East Asian) to identify any errors in batch processing that are not detected by the load routines. Selectors depend on technical services and LITO to implement desired MARC record services, and technical services and LITO depend on vendors to maintain reliable service performance. HSL depends on timely loading of eresource records to avoid ordering duplicate content. Monographs Recon Projects, the ReCAP coordinator, Collection Development and Access Services likewise rely on LITO support. Limitations mostly consist of EOFY demands and vendor's vendor’s ability to meet requirements for MARC services.
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If possible, establish baseline productivity numbers for activities and projects at each institution to allow for future assessment of potential changes and development associated with 2CUL TSI
Both CULs use Voyager's Voyager’s bulk import to create approval MARC records with purchase orders. The main difference is related to different workflows. While Columbia loads almost all approval titles, almost 23,000, with purchase order line items included, Cornell does not. Cornell only creates purchase order line items through bulk import for the vendors, Harrassowitz and Casalini. For the remaining of the 17,400 approval volumes loaded, most of them were loaded without line items. Cornell also loads records for various LC acquisition programs.
While we both use POOF to load records and create purchase orders for firm ordered titles, we differ both in number of line items loaded for firm orders. Columbia uses POOF and YBP's YBP’s GOBI for their source while Cornell uses both POOF and WorldCat Selection. This yields a significant difference in the number of loaded records with Columbia producing around 9,000 firm order line items while Cornell produced 14,000 firm orders through bulk loading.
Columbia and Cornell have several Voyager extract and export projects to OCLC. While Cornell does daily exports via a nightly cron job of new cataloging to OCLC, Columbia does weekly extracts. Cornell totaled approximately 250 thousand versus Columbia's Columbia’s 170 thousand last fiscal year. Columbia also sends preliminary records to OCLC for materials in their circulating backlog, encoding level 5, once a year for another almost 17 thousand and loaded improved records for 9,900. Cornell uses this process, locally called Batchmatch, to send records with encoding levels, 3, 5, and 8, to OCLC on a monthly basis, for a total extract of 37 thousand records with updated records for 4150. 2CUL institutions both send extracts for OCLC institutional records to be created. Columbia for their East Asia program sent 19,000 records to OCLC last fiscal year. Cornell sends pre-1900 imprints and bibliographic records for the Law Library which totaled 222,000. Cornell also sends updates to its own manuscript and archival collections totaling another 7900 records as well as exporting all cataloged holdings and changes made to the holdings totaling over 1 and ¾ million holding records exported last fiscal year.
Serial Solutions is the primary source for MARC data for both institutions e-resources. While Columbia discourages getting metadata from other sources, they do upon occasion get their metadata directly from the vendor. Cornell while it prefers Serial Solutions, if the metadata is superior elsewhere will go to that source whether it's it’s OCLC collection sets or from the vendor. Last year Columbia batch processed over 80,000 e-journal and 440,000 e-book records while Cornell handled 14,000 e-journals and 270,000 e-book records.
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