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Integrating Library Resource Management Systems into Campus Infrastructure for Research and Education MacKenzie Smith Associate Director for Technology.

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Presentation on theme: "Integrating Library Resource Management Systems into Campus Infrastructure for Research and Education MacKenzie Smith Associate Director for Technology."— Presentation transcript:

1 Integrating Library Resource Management Systems into Campus Infrastructure for Research and Education MacKenzie Smith Associate Director for Technology MIT Libraries NISO Forum Library Resource Management Systems: New Challenges, New Opportunities October 7-8, 2009

2 NISO Forum on LRMS ©MIT, 2009

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5 Integrated Library System NISO Forum on LRMS ©MIT, 2009

6 Institutional Repository NISO Forum on LRMS ©MIT, 2009

7 External Systems NISO Forum on LRMS ©MIT, 2009

8 Course Example NISO Forum on LRMS ©MIT, 2009

9 Thesis Example NISO Forum on LRMS ©MIT, 2009

10 Conceptual Data Models Build on and harmonize bibliographic data models FRBR, ERMI MARC, MODS, Dublin Core, EAD, DDI, FGDC, VRA, CCO… ONIX, PRISM (upstream) XMP, bibTex, RIS (upstream) SCORM, IMS (downstream) flickr, delicious, youtube, iTunesU (everywhere) NISO Forum on LRMS ©MIT, 2009

11 Conceptual Data Models Define new conceptual data models People and Institutions Usage statistics (e.g. COUNTER) Financial transactions Local policies (e.g. RuleML) Local workflows (e.g. BPEL) Etc. NISO Forum on LRMS ©MIT, 2009

12 Data-Oriented Architecture Data-centric Workflow-aware Modular and flexible (SOA) Web architecture is the architecture e.g. RDF and OWL, expressed in XML or JSON, transferred via HTTP NISO Forum on LRMS ©MIT, 2009

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14 Data Layer enterprise data should be logically visible and consolidated by data domain. there are a coherent set of rules for locating, a unified view of, and a standard way to access data for a particular domain (e.g. student data). NISO Forum on LRMS ©MIT, 2009

15 Data & Business Integration Layer a consistent way of interacting with enterprise data, and a coherent strategy for sharing data across systems. key to achieving the goals of the data layer, i.e. logical consolidation and access to data by domain enables easy data mash-up support for new services NISO Forum on LRMS ©MIT, 2009

16 Course Example Revisited NISO Forum on LRMS ©MIT, 2009

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