Data of the article Analysis of the self-archiving policies of journals in the highest ran

127 journals from the highest rank category of the Finnish Publication Forum classification in computer science, physics, and electronic engineering were analyzed for their self-archiving policies. The data, extracted in August 2017 by AM Rousi of Aalto University, categorizes journals by gold or hybrid models and applies Laakso's publisher policy coding framework to green open access rules. It includes publisher identification and notes the shortest applicable embargo period for institutional or subject repositories.

Use Cases

• Classify journals by publishing model (gold vs. hybrid) based on the description's stated methodology.
• Analyze green open access embargo policies for hybrid journals using the applied Laakso coding framework.
• Map publisher prevalence across top-ranked Finnish journals in the specified scientific fields.
• Study multi-disciplinary journal classification where approximately 30 journals belong to more than one field.

Strengths

• Data covers 127 individual journals from a defined, high-ranking classification tier.
• Applies a standardized policy coding framework (Laakso, 2014) for consistent analysis.
• Explicitly records the shortest applicable embargo, providing a clear metric for policy comparison.

Limitations

• Data is from August 2017; policies may have changed significantly since extraction.
• Row count and column-level documentation are unknown, limiting pre-download assessment of structure.
• The description does not specify the exact fields or values present in the CSV file.

Provenance

Source

Aalto University, author AM Rousi.

Collection Method

Journals identified via the Finnish Publication Forum search using Ministry of Education field filters; policies analyzed via Laakso's coding framework.

Time Range

Data extracted August 2017.

Freshness

Last updated date is unknown; data is from 2017.

Geography

Focus on journals within the Finnish journal classification system.