Ten Quick Tips for Finding Research Data

Data Discovery Paradigms IG

Group co-chairs: Siri Jodha Khalsa, Anita de Waard, Mingfang Wu, Fotis Psomopoulos

Supporting Output title:  Ten Quick Tips for Finding Research Data

Authors: Kathleen Gregory, Siri Jodha Khalsa, William K. Michener, Fotis E. Psomopoulos, Anita de Waard, Mingfang Wu

DOI: will be provided by the group.

Citation: Kathleen Gregory, Siri Jodha Khalsa, William K. Michener, Fotis E. Psomopoulos, Anita de Waard, Mingfang Wu (2017): Ten Quick Tips for Finding Research Data.



Over the past decades, science has experienced rapid growth in the volume of data available for research - from a relative paucity of data in many areas to what has been recently described as a data deluge. Data volumes have increased exponentially across all fields of science and human endeavour, including data from sky, earth and ocean observatories; social media such as Facebook and Twitter; wearable health monitoring devices; gene sequences and protein structures; and climate simulations. This brings opportunities to enable more research, especially cross-disciplinary research that could not be done before. However, it also introduces challenges in managing, describing and making data findable, accessible, interoperable and reusable by researchers. 

When this vast amount and variety of data are made available, finding relevant data to meet a research need is increasingly a challenge. In the past when data were relatively sparse, researchers discovered existing data by searching literature, attending conferences and asking colleagues. In today’s data-rich environment, with accompanying advances in computational and networking technologies, researchers increasingly conduct web searches to find research data. The success of such searches varies greatly and depends to a large degree on the expertise of the person looking for data, the tools used and, partially, on luck.  This article offers ten quick tips that researchers can follow to more effectively and precisely discover data that meets their specific needs. A list of useful resources and examples from the article are listed in the final Resources section. 



Review period start: 
Monday, 11 December, 2017 to Monday, 15 January, 2018
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