Abstract

During the last years the call for publishing and sharing research data has become ubiquitous. Besides moral appeals towards transparency as a basic principle of science, more and more policies and regulations start to push researchers to make their research data available to the scientific community and the general public. In addition to research funding organizations, publishers are most influential in this regard as they are able to boost the practice of data sharing by incentives that are highly attractive for researchers: publications and hence reputation in academia. In consequence more and more datasets are published by researchers – in very different ways, using the quite heterogeneous tools and publishing solutions currently available.However, these data publications do not necessarily increase transparency in research. Publishing research data might even contribute to an increase in noise and opacity. Mere disclosure of date has very little value per se, as The Royal Society in its report “Science as an open enterprise” (2012) noticed. The report asks for “intelligent openness” where data are not just published but effectively communicated. To accomplish intelligent openness, data have to be accessible, intelligible, assessable and usable (p. 14).The presentation will take up this consideration and explore the challenges involved. Communicating data aims at enabling receivers (i. e. data users) to correctly interpret and appropriately use the published research data. As will be shown by examples of published datasets from the field of behavioral and social sciences, currently this aim is by no means generally achieved. In seeking to comply with data policies of funders and publishers researcher may be inclined to publish datasets that are hardly intelligible and not usable. Additionally there is a lack of data publishing infrastructures (including technical tools as well as standards and social practices) supporting researchers in communicating data in a meaningful way to their different audiences. Obviously, it is much easier to share data within the own research community than across research fields, disciplines or even cultures. In general, the less the researchers who publish data and the audience who wants to use these data share a common context (increasing “distance-from-data-origin”, Baker & Yarmey 2009), the more demanding communicating research data will become.Thus, publishers face considerable challenges when trying to advance from publishing to communicating research data. Developing solutions pointing in this direction should be, nevertheless, of primary concern, as publishing without communicating might ultimately be just a waste of resources. Therefore, besides exploring the challenges, the presentation will also try to identify steps that might help to approach the ambitious goal of communicating research data.

Highlights

  • The Pioneer Plaque: “to show scientifically educated inhabitants of some other star system, who might intercept it millions of years when Pioneer was launched, from where, and by what kind of beings”

  • Data must be located in such a manner that it can readily be found

  • Data must provide an account of the results of scientific work that is intelligible to those wishing to understand or scrutinise them

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Summary

Publishing data

Our message We need technical solutions to publish data. We need concepts and tools to effectively communicate these data. „ Publishing research data “can [...] be as easy as spending a minute creating a figShare account and another minute uploading your file and adding a title and subject keywords. Click a button and your data has a permanent home and DOI. Levelling up to Open Research Data By Deborah Fitchett, Digital Access Coordinator at Lincoln University

Data Publication at Figshare
Research Team near remote
Full Text
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