Making Visualization Work for Institutional Repositories: Information Visualization as a means to browse electronic theses and dissertations

Authors : Leila Belle Sterman, Susan Borda


An attractive repository with clear, well-structured and accessible content can be a powerful recruitment and publicity tool for administrators, fundraisers, and others trying to bolster support for repositories.

Digitizing ETDs is a lengthy and often arduous process. Once that process is completed, it is often a victory that suffices. As a result, collections frequently receive no further treatment. We demonstrate the benefits of visualizing repository content.


The goal of the project was to create an interactive visualization to make our newly digitized theses and dissertations more discoverable.

By leveraging the institutional organization of College, Department and Year of Graduation, we visualized data to help users understand ETD content as a whole and find specific items more easily.


The process begins with data cleanup involving extracting and normalizing repository metadata, then the data is processed and the Data-Driven Documents (D3) JavaScript library is used to generate the actual visualization.

Benefits of Visualizations to Users: The visualization allows for the sort of happenstance discovery of materials that are celebrated about shelf browsing and a way to compare the productivity of each college and department at our university. It also illustrates our institution’s changes in emphasis over time.


Visualizations have vast potential for creating engaging user interfaces for digital library content. We would like to explore how people are using the visualization as we move forward with this process to visualize multiple collections.

URL : Making Visualization Work for Institutional Repositories: Information Visualization as a means to browse electronic theses and dissertations


Discovery and Reuse of Open Datasets: An Exploratory Study

Authors : Sara Mannheimer, Leila Belle Sterman, Susan Borda


This article analyzes twenty cited or downloaded datasets and the repositories that house them, in order to produce insights that can be used by academic libraries to encourage discovery and reuse of research data in institutional repositories.


Using Thomson Reuters’ Data Citation Index and repository download statistics, we identified twenty cited/downloaded datasets. We documented the characteristics of the cited/downloaded datasets and their corresponding repositories in a self-designed rubric.

The rubric includes six major categories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description.


Our small-scale study suggests that cited/downloaded datasets generally comply with basic recommendations for facilitating reuse: data are documented well; formatted for use with a variety of software; and shared in established, open access repositories.

Three significant factors also appear to contribute to dataset discovery: publishing in discipline-specific repositories; indexing in more than one location on the web; and using persistent identifiers.

The cited/downloaded datasets in our analysis came from a few specific disciplines, and tended to be funded by agencies with data publication mandates.


The results of this exploratory research provide insights that can inform academic librarians as they work to encourage discovery and reuse of institutional datasets.

Our analysis also suggests areas in which academic librarians can target open data advocacy in their communities in order to begin to build open data success stories that will fuel future advocacy efforts.

URL : Discovery and Reuse of Open Datasets: An Exploratory Study