Syndicated from http://www.stm-publishing.com/
January 22, 2020
To accelerate the implementation of research data solutions, The International Association of Scientific, Technical and Medical Publishers (STM) has launched the ‘STM 2020 Research Data Year’ – a dedicated action plan to increase the number of journals with data policies, expand the number of journals depositing data links and grow the volume of citations to datasets.
In any field of study, the sharing of data is one of the most fundamental aspects of maintaining the integrity of research. The availability of research data plays a vital role in ensuring reproducibility and the ongoing development of Open Science. Acknowledging this, funders are increasingly developing data sharing policies for research funded by them.
The STM 2020 Research Data Year will directly support researchers by assisting publishers to: Share: accelerate the number of journals with data policies and articles with Data Availability Statements (DAS); Link: accelerate the number of journals that deposit the data links to the SCHOLIX framework for linking datasets and publications; and Cite: accelerate the citations to datasets.
A range of collaborative cross-industry activities have been initiated to share best practices and offer training material to make it quick and easy for publishers to accelerate their research data implementations. These include a dedicated website resource, regular international workshops and webinars encouraging the exchange of experiences and lessons learned, and dedicated support for implementation efforts including on-site visits.
Current participants in the program include Cambridge University Press, Elsevier, DeGruyter, Karger Publishers, Oxford University Press, Sage Publishing, Springer Nature, Taylor & Francis and Wiley. Progress towards the goals of the 2020 Research Data Year will be tracked and displayed on a website dashboard which will show how publishers are steadily implementing new data policies, encouraging data sharing and making the links and citations to and from datasets and scholarly journal articles more widely available.