Ben Birch

Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide

The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines. We distributed surveys to a multinational sample of scientific researchers at two different time periods (October 2009 to July 2010 and October 2013 to March 2014) to observe current states of data sharing and to see what, if any, changes have occurred in the past 3–4 years. We also looked at differences across age, geographic, and discipline-based groups as they currently exist in the 2013/2014 survey. Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors. However, there is also increased perceived risk associated with data sharing, and specific barriers to data sharing persist. There are also differences across age groups, with younger respondents feeling more favorably toward data sharing and reuse, yet making less of their data available than older respondents. Geographic differences exist as well, which can in part be understood in terms of collectivist and individualist cultural differences. An examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines. Implications of these findings include the continued need to build infrastructure that promotes data sharing while recognizing the needs of different research communities. Moving into the future, organizations such as DataONE will continue to assess, monitor, educate, and provide the infrastructure necessary to support such complex grand science challenges.

Academic librarians and research data services: preparation and attitudes

Research funding bodies recognize the importance of infrastructure and services to organize and preserve research data, and academic research libraries have been identified as locations in which to base these research data services (RDS). Research data services include data management planning, digital curation (selection, preservation, maintenance, and archiving), and metadata creation and conversion. We report the results of an empirical investigation into the RDS practices of librarians in US and Canadian academic research libraries, establishing a baseline of the engagement of librarians at this early stage of widespread service development. Specifically, this paper examines the opinions of the surveyed librarians regarding their preparedness to provide RDS (background, skills, and education), their attitudes regarding the importance of RDS for their libraries and institutions, and the factors that contribute to or inhibit librarian engagement in RDS.

Perceived Value of Scholarly Articles

When faced with an abundance of articles, readers must weigh the relative importance of various characteristics to select which articles to read. Over 400 researchers in 12 countries responded to a questionnaire that asked them to rank seven article characteristics and rate 16 article profiles. After article topic, the next most highly ranked characteristics were online accessibility and source of article. Conjoint analysis revealed the highest rated profiles to be (i) article written by a top‐tier author, in a top peer‐reviewed journal, available online at no personal cost to the reader; and (ii) article written by a top‐tier author, in a peer‐reviewed journal not in the top tier, available online at no personal cost to the reader. There were significant differences in characteristic rankings by discipline and geographic location.

Planning mobile sensor net deployment for navigationally-challenged sensor nodes

This wok describes novel algorithms for planning the deployment of a large number of navigationally-challenged mobile sensor nodes in known indoor environments. Due to cost and power constraints, our mobile sensor nodes have the ability to move and communicate, but they cannot detect or avoid obstacles or localize to the environment. Additionally, they have only minimal capabilities for detecting other robot team members, through the use of a crude camera. Our deployment process, therefore, uses an assistive navigation technique that enables a more capable leader robot, equipped with a laser rangefinder and a camera, to guide several mobile sensor nodes to their deployment positions. To ensure the successful deployment of the mobile sensor nodes, we have developed an autonomous planning process that plans the positions of the sensor nodes based upon a number of constraints, including maintaining line of sight maximizing visibility coverage, avoiding placement in doorways, minimizing obstruction of corridors, and so forth. Additionally, because of the navigational constraints of simple robots following a leader to these deployment positions, our algorithm also derives two leader waypoints for each sensor position, which on strain the motion of the leader path to the deployment position. These leader

Academic Libraries Follow-Up dataset

This is the data set to the Libraries Follow-Up only. This is the planned 1st follow-up for DataONE Libraries stakeholders