Zzzoot

F rancine Berman's call for a research data census in the U.S. recognizes the reality that the valuable research assets produced by public (and private) research funding is uncounted, mostly unmanaged, and destined to be, or in the process of being, degraded, damaged and lost. Lost to future research, re-use, re-purposing. While a census is useful when your knowledge about a topic is effectively zero , as in this case, I don't think that it is a good ongoing solution to this particular problem. Distributed and open research data repositories, open standards like OAI-PMH , rich metadata (and the tools to create/manage them) and the will of funding agencies and research organizations can all come together to make a real-time census possible. But an initial census is clearly needed, in order properly discover the complete nature of the research data problem, in order to plan the processes, infrastructure and organizations to properly deal it. Berman, F. 2010. We Need a Research D...

Research data and metadata - usually derived from an experiment or series of experiments - is in the hot focus of the researcher during the experiment and the subsequent interpretation, paper writing and publishing. But once the researcher has moved on to their next effort, this data is very much at risk. Often (read ' the-rule-rather-than-the-exception '), the data is not properly managed and archived, and resides as a single copy on the researcher's desktop or maybe research server. In addition, the metadata is minimal or non-existent, and if it does exist is only interpretable by the researcher and their colleagues or students. Over time, the chance that this data will be lost or useful knowledge about it forgotten by the researcher increases, and the information content of the data and metadata rapidly decreases. Some events can seriously accelerate this decrease: data loss (media failure, computer replacement, other serious accidents or failures, etc); change of care...

In the recent editorial ( Am Nat 2010. Vol. 175, pp. 145–146 ) of The American Naturalist , it was announced that the journals " The American Naturalist , Evolution , the Journal of Evolutionary Biology , Molecular Ecology , Heredity , and other key journals in evolution and ecology..." would be introducing data archiving policies supporting access, re-use and long term preservation. These policies are to be put in place in one year, and the example policy for the The American Naturalist is given: This journal requires, as a condition for publication, that data supporting the results in the paper should be archived in an appropriate public archive, such as GenBank, TreeBASE, Dryad , or the Knowledge Network for Biocomplexity. Data are important products of the scientific enterprise, and they should be preserved and usable for decades in the future. Authors may elect to have the data publicly available at time of publication, or, if the technology of the archive allow...

I recently discovered the (at least partial) root of some of the excellent activity in the area of research data management in the UK: the UK government's Science & innovation investment framework 2004-2014 . Of particular interest: 2.23 The growing UK research base must have ready and efficient access to information of all kinds – such as experimental data sets, journals, theses, conference proceedings and patents. This is the life blood of research and innovation [emphasis added] . Much of this type of information is now, and increasingly, in digital form. This is excellent for rapid access but presents a number of potential risks and challenges. For example, the digital information from the last 15 years is in various formats (versions of software and storage media) that are already obsolete or risk being so in the future. Digital information is also often transient in nature, especially when published formally or informally on websites; unless it is collected and archived...

The Interagency Working Group on Digital Data to the National Science and Technology Council (U.S.) has release its report, Harnessing the Power of Digital Data for Science and Society" . " The report lays out a strategic vision for ´a digital scientific data universe in which data creation, collection, documentation, analysis, preservation, and dissemination can be appropriately, reliably, and readily managed, thereby enhancing the return on our nation’s research and development investment by ensuring that digital data realize their full potential as catalysts for progress in our global information society .' "

One of the implications of research data archiving is that there will likely be large datasets on a variety of subjects. How third parties will analyse these data in a scalable fashion has not entirely been addressed. But the recent conference examines some of the issues for a class of data, images and signals : Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry (Third International Conference, MDA 2008 Leipzig, Germany, July 14, 2008) and includes: Burcu Yılmaz, Mehmet Göktürk, Natalie Shvets (2008). User Assisted Substructure Extraction in Molecular Data Mining. Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, 5108 , 12-26 DOI: 10.1007/978-3-540-70715-8_4 Franco Chiarugi, Sara Colantonio, Dimitra Emmanouilidou, Davide Moroni, Ovidio Salvetti (2008). Biomedical Signal and Image Processing for Decision Support in Heart Failure. Advances in Mass Data Analysis of Imag...