Includes some map-viz tools.

Carrying out the Survey There are 4 main working spreadsheets for the survey of  Top/Bottom Science/Social Science Journals – approximating to 400 journals. Each journal has now been reviewed…

TEI repo and publishing platform. In development at time of bookmarking.

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Research highlights differing methods of reporting central line infections in hospitals.

Where gazetteers meet GIS software. TEI knows about this problem, but can't solve it all by itself.

Followup on the Ahluwalia case. This is a case where smart lab precautions around data didn't stop the fraud, but made detecting it and assigning responsibility after the fact possible.

Objective:Cornell University’s Research Data Management Service Group (RDMSG) surveyed NSF principal investigators (PIs) at Cornell in order to understand how well-prepared researchers are to meet the new NSF data management planning requirement, to build our own understanding of the potential impact on campus services, and to identify service gaps. Methods: We administered a 43-question online survey, which included questions about the respondents’ research and research data, their interest in assistance with the creation of data management plans, and questions for each of the five general areas cited in the NSF’s Grant Proposal Guide (2011) section on data management plans. Results and Discussion: Respondents produce a wide variety of types and formats of data, although most expect to share relatively small amounts of data. Respondents are generally uncertain as to whether the data they produce conforms to disciplinary standards. The majority create no metadata; of those that do, most do not create metadata according to a particular standard. Most researchers do not express a need for advice regarding intellectual property issues. Researchers report using a variety of strategies (on-campus and commercial) for backing up and for providing access to their data sets. Conclusions: The overarching finding from our survey is that there is much uncertainty about what the new requirement means and how to meet it, and researchers welcome offers of assistance. To the extent that Cornell researchers are representative of NSF PIs, our findings reveal something about researchers’ readiness to meet the new requirement, and their attitudes towards it.

This article describes the curriculum, implementation, and results of the research data management training offered by the University of Minnesota (UMN) Libraries. The UMN Libraries have offered the workshop titled, “Creating a Data Management Plan for Your Grant Application,” to more than 300 researchers and faculty since late 2010. With University partnerships, this training satisfies the requirement for the continuing education component to maintain PI eligibility. Based on workshop feedback, the authors conclude that academic libraries can provide support to researchers with federal mandates to share their research data by providing timely, discussion-based training and resources on how to create a data management plan. The unanticipated benefits for library staff education and professional development on this topic are explored.

How to "free your metadata" by improving its quality via Google Refine. Source of exercises?

An exclusive look inside Ground Truth, the secretive program to build the world's best accurate maps

Points out why a lot of metadata standards for data are kinda obtuse.

Two years after questions surfaced about work by former Harvard psychology professor Marc Hauser, an official government report is finally out. It’s not pretty. The findings by the Office of …

Research output is becoming increasingly digital. In the sciences research output now takes the form of large and small datasets, three-dimensional images and s

Symmetry is an online magazine about particle physics and its connections to other aspects of life and science, from interdisciplinary collaborations to policy to culture.