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Open Science is revolutionising the way people do research and share knowledge. In this context, it has become more and more important to identify what research outputs comply with good Open Science practices. OpenScore is a rating system that allows users to:

• Easily identify in what respect a certain paper follows good OS practises
• Interact with papers by rating them

• Author/co-authors
• Reader
• Rater
• Funders
• Peer reviewer
• Publisher
• Archivists

To learn more about use cases, check out this page.

• Looking for a collaborator
• Writing my own paper
• Grant Management Officers (GMOs)
• Choosing which articles to read
• Planning and conducting a dissertation research project

• Paper is published -> Reader views paper -> Reader chooses to view/edit ratings -> Rating is posted to social media
• User comes to Rating Site -> User Filters all available articles by ratings
• User wants to compare the OpenScores of articles addressing an issue -> Users search among all available articles by title

• Does this paper contain code?
• Is the code reproducible/runnable?
• Does the paper contain a funding statement?
• Is the data posted to an open repository?
• Is the data reusable?
• Are the Methods described properly?
• Are the protocols deposited to https://www.protocols.io/
• Does this paper contain videos?
• Does this paper contain original research?
• Is the data in this paper machine readable?
• Can the results in this paper be reproduced without proprietary software?
• Is this paper well-written?
• Is this paper written in proper structure?

• Sign-in using ORCID
• Search for similar articles
• Journal weighting (e.g. Some journals require authors to share datasets, and others only recommend it. If authors are not required to upload a dataset but do it anyway, positive votes may count double)
• Rating datasets and metadata
• Open Science Badges integration
• Compare the composition of two different OpenScores