Open Data Sets

Access open datasets, documentation, licensing, and citation guidance for reuse and reproducibility.

Data Sets for Research, Learning, and Innovation

The CoU Data Sets hub is a living open-data infrastructure that supports reproducible research, applied innovation, and skills-based learning across City Open University programs. Each record is published with metadata, licensing, and citation guidance so it can be reused by students, faculty, partners, and communities.

Our strategic aim is to become a dominant research center for online-learning universities by connecting datasets to publications, grants, and learning labs—while ensuring strong ethics, privacy, and quality assurance.

What you can do here

  • Discover datasets by discipline, year, type, or author using smart search and filters.
  • Download dataset packages, code, and documentation for replication and learning.
  • Export citations (APA / BibTeX / RIS) and track reuse signals (downloads & citations).
  • Submit a new dataset through CoU’s review workflow and compliance checks.

Designed to be OpenPlus-ready: datasets can be synchronized with records, dashboards, and reporting—while maintaining a white content background elsewhere on the page.

What Lives in CoU Data Sets

CoU supports both traditional and non-traditional research data so our programs stay aligned with today’s digital market needs (analytics, AI, open education, public policy, health replication, entrepreneurship, and technology-enabled research methods).

Category Typical content Program alignment
Learning & LMS Analytics Engagement logs, assessment patterns, retention signals Education, Data Science, Management
AI & Digital Innovation Benchmarks, fairness metrics, evaluation sets, prompt libraries Engineering & Computer Sciences
Health & Replication De-identified indicators, codebooks, replication-friendly datasets Health Sciences, Public Health
Policy & Governance Policy indicators, compliance matrices, civic data extracts Law & Governance, Public Administration
Entrepreneurship & Market Insights Market signals, innovation ecosystems, forecasting sets Business, Digital Innovation
Licensing & reuse
Datasets include recommended licenses and attribution. Preferred: CC BY (reuse with credit) or CC0 (maximal openness) when appropriate.
Versioning & integrity
Each dataset can publish versions with change logs so projects cite the exact dataset used.

Dataset Browser (Smart Search + Filters)

Search by question, not only by keyword. This demonstration uses sample records; your real portal can populate results from OpenPlus / repository services.

Showing 0 results • Downloads: 0 • Citations: 0 • Countries: 0

Catalogue exports (partner & accreditor ready)

Provide machine-readable catalogue exports for auditing, integration, and transparency. (Planned: JSON/CSV + version archive.)

How CoU Uses Data Sets in Teaching & Learning

Data sets are integrated into CoU programs to make learning practical and market-aligned. Students learn to acquire, document, clean, analyze, and communicate evidence—skills essential for modern digital industries.

Course labs
Structured labs with datasets and starter notebooks to master research design, evaluation, and reporting.
Capstones & theses
Cite dataset versions for consistent findings and publish supporting datasets alongside dissertations.
Industry projects
Partners contribute anonymized data; students learn governance and adoption pathways.
OER learning packs
Bundle datasets with open resources to create reusable global learning packages.
Program-aligned learning paths (examples)
Program Dataset focus Outcome
Education & Instructional Design Learning analytics, accessibility evidence Retention strategies, adaptive interventions
Computer Science & AI Evaluation sets, fairness metrics Responsible AI, deployment readiness
Business & Entrepreneurship Market insights, forecasting sets Data-driven strategy and innovation

Governance, Ethics, and Quality Assurance

A strong dataset portal is not only a catalogue—it is a trust system. CoU applies ethical review, privacy safeguards, metadata standards, and quality assurance so our datasets can be used confidently by researchers, accreditors, and partners.

  1. Prepare: dataset files, readme, codebook, license, and optional notebooks.
  2. Review: DMP + ethics checklist; de-identification notes where needed.
  3. Submit: via Submit for steward and compliance checks.
  4. Publish: assign DOI + version; connect to Records and Analytics.
  5. Track & improve: reuse signals (downloads/citations) and publish new versions with change logs.

Research Search

Search connects to the repository smart search.

Live Metrics

0Downloads
0Citations
0Countries

Numbers are editable placeholders—ready for real analytics integration.

AI Research Assistant

Ask for keywords, search strategy, or how to format citations.