Peer Review

Harvard Dataverse: Cross-Disciplinary Repository

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Reviewed:: Sep 25, 2021 by Sociology

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Ratings

Overall Rating:

Content Quality:

Effectiveness:

Ease of Use:

Overview:

Harvard Dataverse is a free cross-disciplinary repository open to all researchers from any discipline, both inside and outside of the Harvard community where you can share, archive, cite, access, and explore research data.

Type of Material:

Collection

Recommended Uses:

This would be useful for finding data for student research projects, as well as data acquisition for general research.

This would require a tutorial within a research course so students can learn how to use it to its fullest extent. Therefore, this would fit in best in either a face to face course or detailed virtual tutorial.

The students would then apply this instrument to the data they collect from their particular research study. The dataset can then be shared with the other students.

Technical Requirements:

High speed internet, data management/statistics software

Identify Major Learning Goals:

This is an extensive set of data, databases, and dataverses (their term). It covers a very wide range of subjects that includes Chemistry, Medicine, Law and Social Sciences, and even more. It also includes tools for searching, uploading and extracting data.

Potential goals might include:

-Demonstration of depositing data into a Dataverse repository, which can be customized or embedded into a website with our Theme + Widgets feature, researchers make their datasets more discoverable to the scientific community.

-Demonstrate depositing research data in a Dataverse repository (including the Harvard Dataverse Repository) and how this may fulfill funding agency requirements for data management plans.

-Deposit replication datasets in a public repository.

Target Student Population:

College Upper Division, Graduate School, Professional researchers and faculty

Prerequisite Knowledge or Skills:

Students would need to have at least basic statistics and data collection skills as well as general computer literacy.

Content Quality

Rating:

Strengths:

-Includes a comprehensive set of descriptors of how this tool can be used

-A comprehensive user guide

-The user can enter their own dataset and can compare with similar datasets in the dataverse

Bearing in mind that the content has been uploaded by others, with unknown quality control, the breadth of material is simply huge.

Concerns:

-Would be helpful to have examples in the descriptions of use; this would make this a tutorial.

-Judgment should be used for individual data sets.

Potential Effectiveness as a Teaching Tool

Rating:

Strengths:

-Easy to navigate the website and the tool.

-Can easily assist the researcher in storing a dataset and find similar ones for their research.

-The datasets are cataloged, sorted and searchable. An instructor could select representative data for student projects with relative ease.

Concerns:

It would be somewhat difficult for students to teach themselves to use this resource.

Ease of Use for Both Students and Faculty

Rating:

Strengths:

-Easy to use with categories on the left side of the search page.

-Can look up by dataset or dataverse.

-Files are available for download.

-The data tools are well-organized. Navigating the website is easy.

Concerns:

Other Issues and Comments:

The plan is for this to be updated.

It is formatted in a way familiar for those who do research in various library search engines.

This is an extensive, well-produced resource.

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