By Paul E. Uhlir, Board on Research Data and Information, Policy and Global Affairs, National Research Council
The expansion of digital publishing of literature has created new demanding situations, reminiscent of the necessity for mechanisms for bringing up on-line references in ways in which can guarantee discoverability and retrieval for a few years into the longer term. the expansion in on-line datasets provides similar, but extra complicated demanding situations. It is dependent upon the power to reliably establish, find, entry, interpret, and confirm the model, integrity, and provenance of electronic datasets. information quotation criteria and stable practices can shape the root for elevated incentives, acceptance, and rewards for medical info actions that during many instances are presently missing in lots of fields of study. The rapidly-expanding universe of on-line electronic info holds the promise of permitting peer-examination and assessment of conclusions or research in response to experimental or observational facts, the mixing of information into new sorts of scholarly publishing, and the facility for next clients to make new and unexpected makes use of and analyses of an identical data-either in isolation, or together with, different datasets.
The challenge of bringing up on-line info is advanced via the shortcoming of proven practices for concerning parts or subsets of information. there are various tasks in numerous enterprises, international locations, and disciplines already underway. a tremendous set of technical and coverage ways have already been introduced by way of the U.S. nationwide details criteria association (NISO) and different criteria our bodies relating to continual identifiers and on-line linking.
The workshop summarized in For Attribution -- constructing facts Attribution and quotation Practices and criteria: precis of a world Workshop was geared up through a guidance committee less than the nationwide examine Council's (NRC's) Board on study facts and data, in collaboration with a global CODATA-ICSTI job staff on info quotation criteria and Practices. the aim of the symposium was once to envision a few key concerns on the topic of facts identity, attribution, quotation, and linking to assist coordinate actions during this region across the world, and to advertise universal practices and criteria within the clinical neighborhood.
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Extra resources for For Attribution -- Developing Data Attribution and Citation Practices and Standards: Summary of an International Workshop
However, are we focusing too much only on the technical challenges? The real challenge is the culture of citing datasets and providing a proper citation. We therefore need to focus on both the technical and the social and cultural challenges. DR. MINSTER: There is a well-known trick to put the subtle error in one of your papers and then everybody is going to cite your publication. You can do the same with data. If we stop insisting that every single granule of a database should have its own identifier and be quoted by those who use it, it would be in the interest of the data provider to just give miniscule granules.
The MESUR project was funded by the Andrew W. Mellon Foundation in 2006 to study science itself from largescale usage data. The project was involved with large-scale usage data acquisition, deriving Copyright © National Academy of Sciences. All rights reserved. For Attribution -- Developing Data Attribution and Citation Practices and Standards: Summary of an International Workshop ATTRIBUTION AND CREDIT: BEYOND PRINT AND CITATIONS 17 structural models of scholarly influence from said usage data, and surveying a range of impact metrics from the usage and citation it collected.
Elder, and G. Liston. 2002, Updated July 2004. CLPX-Ground: ISA snow pit measurements. Edited by M. Parsons and M. J. Brodzik. Boulder, CO: National Snow and Ice Data Center. html. In this example, we have a description of a dataset. It shows the proper citation of certain data out of the total number of entries, who is responsible for the dataset, who edited it, what was the location, and when it was last accessed online. , time-series weather records); it is often much less important than a specific version number or revision date of the dataset.