Data management FEATURE


As well as the financial consequences, poor data management can have a significant impact on time and other resources. For example, since the year 2000, more than 80,000 patients have taken part in clinical trials based on research that was later retracted because of error or fraud[5]


. Meanwhile, the


number of peer-reviewed paper retractions due to error has grown over fivefold since 1990[6]


. At best, that’s a lot of wasted time and effort, but, at worse, drug discovery is halted and careers are severely affected. Given the above, it is perhaps unsurprising that as many as 34 developed countries have signed up to the Declaration on Access to Research Data from Public Funding. In addition, key funding bodies such as the NIH, MRC and Wellcome Trust now request that data-management plans be part of applications.


Looking after your data The time has come to start better protecting our scientific data. The starting point is to make the capturing of research data more efficient through the better use of technology. There are a host of generic tools available that can be used to fit into existing research workflows. Some such tools proving popular are Evernote, cloud storage services like Google Drive and Dropbox, and code hosting sites like GitHub. While many offer a range


of benefits, these tools haven’t been designed with the scientific community in mind. For this reason, tools specifically for academics are starting to be developed to suit their needs. For example, Digital Science’s Figshare tool is a cloud-based repository where researchers can store their data outputs privately, share them with colleagues, or make them publicly available and citable with a permanent DOI. Figshare is increasingly


More energy must be put into safeguarding this data for the future benefit of science


being used by institutions to host and manage all file types of research data, securely in the cloud. Institutions can also use it to promote collaboration internally and facilitate backup and organisation, without having to share data with the wider world until researchers are ready to publish. Digital Science has also recently developed Projects, an application that lets researchers safely manage and organise their research data on the desktop. It provides a visual timeline to make finding files easy, backup functionality to help seamlessly recover


previous versions of files, annotation features and a structured hierarchy to encourage users to organise their files. In the future, we hope


to see data


management taken more seriously by everyone involved in making science happen, from individual researchers through to institutions and governments. While all are clearly dedicated to improving human existence through exploration and discovery, more energy must be put in to safeguarding this data for the future benefit of science.


Nathan Westgarth is a product manager for research tools at Digital Science. He manages Projects, which aims to help scientific researchers organise their data in a safe, simple and structured way


FURTHER INFORMATION [1] [2] [3] [4] [5] [6]


Why manage research data? In G. Pryor (Ed.), Managing research data (pp. 1-16), Facet Publishing


The availability of research data declines rapidly with article age, Current Biology (24)1: 94-97


On the reproducibility of science: unique identification of research resources in the biomedical literature, PeerJ 1:e148


2013 Global R & D Funding Forecast, Advantage Business Media


Problems with scientific research: How science goes wrong, The Economist


Why has the number of scientific retractions increased?, PLOS ONE 8(7): e68397


MEETING THE RESEARCH DATA MANAGEMENT CHALLENGE


Jisc’s Rachel Bruce describes some of the changes required to ensure that managing research data is a high priority for research institutions


W


ith the drive for open data and the expansion in terms of the size, variety and complexity of data that researchers and institutions are handling, the


need to manage these datasets effectively has never been more pertinent.


Managing research data is not simply a concern for higher-education research managers or information professionals, but is a cross-institutional issue. It is an area that institutions are increasingly taking the lead in when it comes to establishing research


data policies. However, there is, of course, still room for improvement. Many factors are driving this improvement and bringing about a cultural change when it comes to curating, retaining and storing vital research data. EPSRC


(the UK’s Engineering and


Physical Sciences Research Council) sent a clear message on compliance by stating that institutions that receive its funding for research must have developed a roadmap in 2011 outlining support for researchers in implementing responsible and sustainable reuse of their data. Furthermore it stated that


Why is data management crucial for the research community? In addition to compliance obligations, institutions want and need to demonstrate research excellence. By making their studies and data discoverable, the hope is that it will drive new and exciting research efforts. If


APRIL/MAY 2014 Research Information 11


institutions must be compliant with these roadmaps by 2015. Arguably, this has been a key driver for institutions, but there are many other factors influencing the development of research data management.


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