BSOS Data Curation Fellowship

One of the biggest challenges for faculty within the social sciences teaching statistics and data science courses is developing data examples that are relevant, interesting, and structured. Using project-based learning and incorporating real-life datasets is invaluable for learning how exactly data science can be applied in the discipline, but the burden on faculty to clean, manage, and test the datasets is huge. The BSOS Data Repository was built as a response to calls from faculty across various BSOS departments about the need for high quality social science datasets. The University of Maryland Teaching and Learning Transformation Center (TLTC) Experiential Learning program-level grant gave us the opportunity to build this data repository and launch a new Data Curation Fellowship to provide a unique experience for undergraduate students to learn more about the upstream parts of the data project lifecycle and contribute to a real data resource that serves University of Maryland faculty.

Fellowship Overview

The BSOS Data Curation Fellowship was developed at the University of Maryland's College of Behavioral and Social Sciences to build up the data repository and give students the opportunity to learn to curate, clean, document, and publish social science datasets for teaching and research. Our fellowship teams work with real research data from psychology, public health, elections, and more, turning raw datasets into well-documented resources. The Data Curation Fellowship gives BSOS students hands-on experience in data management, documentation, and scholarly communication. Students learn industry-standard practices for data cleaning, quality assurance, and metadata creation while working on datasets that directly support faculty research and undergraduate instruction.

What students do: Identify relevant and interesting sources of raw data, collect and combine data sources, detect and handle missing values, standardize formats, create comprehensive codebooks, write dataset documentation, and publish datasets via CKAN for public access.

Faculty Mentors

Student Teams — Fellowship Cohorts, 2023–2026

Fellowship cohorts are listed in reverse chronological order so the current 2026 groups appear first. Cohort naming follows the original fellowship structure: 2023, 2025, and 2026 were organized as Groups, while 2024 was organized as Teams.

Technical Implementation & Repository

Repository Architecture & Technical Implementation by Namit — The data curation platform runs on a CKAN-based repository with PostgreSQL backend, live analytics dashboards, and automated quality metrics. Namit designed and deployed the full platform infrastructure, including CKAN customizations, the analytics dashboard, deployment pipeline, and site integrations that enable students to publish and manage curated datasets at scale.

Curation Workflow

Usage Guidelines

• Browse & Discover — Use the Groups page to explore datasets by thematic cluster or fellowship cohort.
• Evaluate Quality — Each dataset page includes an Instructor Snapshot sidebar showing row/column counts, null percentages, and quality scores.
• Download Data — CSV and JSON exports are available directly from dataset pages. Use the Data Preview to inspect records before downloading.
• Read Documentation — Use the dataset notes, codebooks, and supporting files on each dataset page to understand provenance, variables, and curation decisions.
• Explore Analytics — Visit the Interactive Dashboard for repository-wide trends, method breakdowns, and thematic coverage.

History & Origins

The first Data Curation Fellowship ran in Spring 2023, and the datasets that were curated as part of that fellowship formed the initial data repository. The current website hosted on CKAN was developed in 2024, with undergraduate students who were part of the 2024 fellowship contributing the maintaining the repository.

Funding & Support

The BSOS Data Repository and the Data Curation Fellowship were launched with support from the University of Maryland Teaching and Learning Transformation Center Experiemential Learning program-level grant. Continued support for the data repository and undergraduate fellowship come from the Social Data Science major.