Online from: 1983
Subject Area: Library and Information Studies
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|Title:||Modeling the digital content landscape in universities|
|Author(s):||Paul Conway, (School of Information, University of Michigan, Ann Arbor, Michigan, USA)|
|Citation:||Paul Conway, (2008) "Modeling the digital content landscape in universities", Library Hi Tech, Vol. 26 Iss: 3, pp.342 - 354|
|Keywords:||Assets management, Content management, Digital libraries, Digital storage|
|Article type:||Research paper|
|DOI:||10.1108/07378830810903283 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||©Paul ConwayThe author thanks Karen Markey and Soo Young Rieh at Michigan's School of Information and Tim Pyatt at Duke for their careful reading and very helpful comments on an earlier draft of this article.|
Purpose – Digital content is a common denominator that underlies all discussions on scholarly communication, digital preservation, and asset management. This past decade has seen a distinctive evolution in thinking among stakeholders on how to assemble, care for, deliver, and ultimately preserve digital resources in a college and university environment. At first, institutional repositories promised both a technical infrastructure and a policy framework for the active management of scholarly publications. Now other approaches that take a broader view of digital content hold sway, the result being confusion rather than clarity about where digital content originates, who the stakeholders are, and how to establish and adjust asset management priorities. This article seeks to present a model for plotting the range of digital content that might be amenable to management as digital assets in higher education.
Design/methodology/approach – The article reviews differing perspectives on digital content, outlines a generalized model, and suggests how the model could be used for examining the distribution of campus digital assets and fostering dialog on management priorities across stakeholder communities.
Findings – A multivariate model of digital content provides a rich framework for analyzing asset management priorities in a university setting. The model should be applied and tested in a variety of university settings.
Practical implications – The model is a tool for establishing asset management priorities across campus units that produce digital content.
Originality/value – The paper offers an original model for evaluating the asset values of digital content produced or acquired in a university context.
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