PLOS Open Science Indicators public dashboard data and queries

We created Open Science Indicators (OSIs) in partnership with DataSeer to measure open science behaviors and identify ways in which we can further advance adoption of best practices. The OSI dashboard prototype makes it easier to explore OSI data from more than 160,000 open access articles from PLOS journals and other publishers to see trends in preprint posting, data sharing, code sharing, study registration and protocol sharing. It enables exploration of open science behaviors through comparing research fields, countries, funders, and institutions. The dashboard is created in Looker Studio using Google BigQuery to process a version of the OSI data in the cloud. The SQL query provided here joins the OSI data to OpenAlex data for the purposes of linking grant and organizational information to each article. The query also utilizes a public table providing a mapping from two letter country codes to formal country names (ISO 3609-1 alpha-2). Note that the query runs in the Google BigQuery environment and uses a PLOS internal version of the OSI dataset that is not publicly accessible so this is provided for transparency and audit purposes. The query creates a single article-level dataset which is saved as a BigQuery Table. This deposit provides a version of this table as a JSON lines extract. For most use cases the public release of the OSI dataset as a CSV file will provide the data in a more useful form. The CSV dataset is therefore recommended for any initial investigation. The dashboard data is provided for full transparency and external audit.For questions about the Open Science Indicators data, visit our FAQ page. To give us feedback or request a demo to explore a specific use case, please get in touch using this form.Data FilesPLOS_dashboard_data.jsonl - JSON representation of the dashboard data with each article in the corpus represented as a JSON object separated by line breaksPLOS_dashboard_query.sql - The query used to generate the dashboard data. The query is written in bigquery SQL and assumes the use of the BigQuery environmentContact details for further information:Iain Hrynaszkiewicz, Director, Open Research Solutions, PLOS, [e-mail] / [e-mail] Cadwallader, Senior Open Research Manager, PLOS, [e-mail] / [e-mail]s to Cameron Neylon for development work on the dashboard.