scholarly journals Modifying researchers’ data management practices

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 253-265 ◽  
Author(s):  
Susan Hickson ◽  
Kylie Ann Poulton ◽  
Maria Connor ◽  
Joanna Richardson ◽  
Malcolm Wolski
Keyword(s):  
Data Management ◽  
Best Practice ◽  
Management Practices ◽  
Social Science Research ◽  
Science Research ◽  
Current Data ◽  
Research Centre ◽  
Data Collection And Analysis ◽  
Management Plans

Data is the new buzzword in academic libraries, as policy increasingly mandates that data must be open and accessible, funders require formal data management plans, and institutions are implementing guidelines around best practice. Given concerns about the current data management practices of researchers, this paper reports on the initial findings from a project being undertaken at Griffith University to apply a conceptual (A-COM-B) framework to understanding researchers’ behaviour. The objective of the project is to encourage the use of institutionally endorsed solutions for research data management. Based on interviews conducted by a team of librarians in a small, social science research centre, preliminary results indicate that attitude is the key element which will need to be addressed in designing intervention strategies to modify behaviour. The paper concludes with a discussion of the next stages in the project, which involve further data collection and analysis, the implementation of targeted strategies, and a follow-up activity to assess the extent of modifications to current undesirable practices.

scholarly journals Video Use in Social Science Research and Program Evaluation

2002 ◽  
Vol 1 (3) ◽  
pp. 22-43 ◽  
Author(s):  
Barbara Rosenstein
Keyword(s):  
Program Evaluation ◽  
Social Science Research ◽  
Science Research ◽  
Video Observation ◽  
The Past ◽  
Moving Images ◽  
Technological Advances ◽  
Data Collection And Analysis ◽  
Situational Assessment ◽  
Giving Feedback

In light of technological advances in producing, viewing and storing moving images, it is appropriate to survey the literature concerning the use of moving images in research over the past few decades. A review of the literature shows that the use of video technology for research falls into three areas: observation (including data collection and analysis), a mechanism for giving feedback, and a means for distance learning and consulting via videoconferencing. This article addresses the first two areas — observation and feedback. It begins with a survey of the use of video observation as a tool for research and documentation. A section on feedback, divided into three sections: performance, interaction and situational assessment follows. A separate section is devoted to the use of video for Program Evaluation. The article concludes with a discussion of epistemological methodological issues and the ethics involved in such a technologically advanced medium.

Building Australia’s Scalable Drone Cloud

2021 ◽  
Author(s):  
Jens Klump ◽  
Tim Brown ◽  
Rohan Clarke ◽  
Robert Glasgow ◽  
Steve Micklethwaite ◽  
...  
Keyword(s):  
Data Management ◽  
Best Practice ◽  
Management Practices ◽  
Agricultural Research ◽  
Terrestrial Ecosystem ◽  
Large Data ◽  
Sensor Data ◽  
Research Network ◽  
Ecosystem Research ◽  
Plant Phenomics

<p>Remotely Piloted Aircraft (RPA), commonly known as drones, provide sensing capabilities that address the critical scale-gap between ground- and satellite-based observations. Their versatility allows researchers to deliver near-real-time information for society.</p><p>Key to delivering RPA information is the capacity to enable researchers to systematically collect, process, manage and share RPA-borne sensor data. Importantly, this should allow vertical integration across scales and horizontal integration across different RPA deployments. However, as an emerging technology, the best practice and standards are still developing and the large data volumes collected during RPA missions can be challenging.</p><p>Australia’s Scalable Drone Cloud (ASDC) aims to coordinate and standardise how scientists from across earth, environmental and agricultural research manage, process and analyse data collected by RPA-borne sensors, by establishing best practices in managing 3D-geospatial data and aligned with the FAIR data principles.</p><p>The ASDC is building a cloud-native platform for research drone data management and analytics, driven by exemplar data management practices, data-processing pipelines, and search and discovery of drone data. The aim of the platform is to integrate sensing capabilities with easy-to-use storage, processing, visualisation and data analysis tools (including computer vision / deep learning techniques) to establish a national ecosystem for drone data management.</p><p>The ASDC is a partnership of the Monash Drone Discovery Platform, CSIRO and key National Collaborative Research Infrastructure (NCRIS) capabilities including the Australian Research Data Commons (ARDC), Australian Plant Phenomics Facility (APPF), Terrestrial Ecosystem Research Network (TERN), and AuScope.</p><p>This presentation outlines the roadmap and first proof-of-concept implementation of the ASDC.</p>

scholarly journals A Report of Data-Intensive Capability, Institutional Support, and Data Management Practices in Social Sciences

2016 ◽  
Vol 11 (1) ◽  
pp. 156 ◽  
Author(s):  
Wei Jeng ◽  
Liz Lyon
Keyword(s):  
Social Sciences ◽  
Data Management ◽  
Data Science ◽  
Management Practices ◽  
Information Science ◽  
Institutional Support ◽  
Current Data ◽  
Management Support ◽  
Model Framework ◽  
Data Intensive

We report on a case study which examines the social science community’s capability and institutional support for data management. Fourteen researchers were invited for an in-depth qualitative survey between June 2014 and October 2015. We modify and adopt the Community Capability Model Framework (CCMF) profile tool to ask these scholars to self-assess their current data practices and whether their academic environment provides enough supportive infrastructure for data related activities. The exemplar disciplines in this report include anthropology, political sciences, and library and information science. Our findings deepen our understanding of social disciplines and identify capabilities that are well developed and those that are poorly developed. The participants reported that their institutions have made relatively slow progress on economic supports and data science training courses, but acknowledged that they are well informed and trained for participants’ privacy protection. The result confirms a prior observation from previous literature that social scientists are concerned with ethical perspectives but lack technical training and support. The results also demonstrate intra- and inter-disciplinary commonalities and differences in researcher perceptions of data-intensive capability, and highlight potential opportunities for the development and delivery of new and impactful research data management support services to social sciences researchers and faculty. 

scholarly journals The History, Advocacy and Efficacy of Data Management Plans

2018 ◽  
Author(s):  
Nicholas Smale ◽  
Kathryn Unsworth ◽  
Gareth Denyer ◽  
Daniel Barr
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Best Practice ◽  
Research Data ◽  
Research Management ◽  
Extensive Literature ◽  
Multiple Use ◽  
Funding Body ◽  
Management Plans ◽  
Recent Developments

AbstractData management plans (DMPs) have increasingly been encouraged as a key component of institutional and funding body policy. Although DMPs necessarily place administrative burden on researchers, proponents claim that DMPs have myriad benefits, including enhanced research data quality, increased rates of data sharing, and institutional planning and compliance benefits.In this manuscript, we explore the international history of DMPs and describe institutional and funding body DMP policy. We find that economic and societal benefits from presumed increased rates of data sharing was the original driver of mandating DMPs by funding bodies. Today, 86% of UK Research Councils and 63% of US funding bodies require submission of a DMP with funding applications. Given that no major Australian funding bodies require DMP submission, it is of note that 37% of Australian universities have taken the initiative to internally mandate DMPs.Institutions both within Australia and internationally frequently promote the professional benefits of DMP use, and endorse DMPs as ‘best practice’. We analyse one such typical DMP implementation at a major Australian institution, finding that DMPs have low levels of apparent translational value. Indeed, an extensive literature review suggests there is very limited published systematic evidence that DMP use has any tangible benefit for researchers, institutions or funding bodies.We are therefore led to question why DMPs have become the go-to tool for research data professionals and advocates of good data practice. By delineating multiple use-cases and highlighting the need for DMPs to be fit for intended purpose, we question the view that a good DMP is necessarily that which encompasses the entire data lifecycle of a project. Finally, we summarise recent developments in the DMP landscape, and note a positive shift towards evidence-based research management through more researcher-centric, educative, and integrated DMP services.

scholarly journals Outside the R1: Equitable data management at the undergraduate level

2021 ◽  
Vol 45 (2) ◽  
Author(s):  
Elizabeth Blackwood
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Undergraduate Curriculum ◽  
Research Data ◽  
Management Skills ◽  
State University System ◽  
Final Project ◽  
Research Data Management ◽  
Management Plans ◽  
Regional Universities

Universities within the California State University System are given the mandate to teach the students of the state, as is the case with many regional, public universities. This mandate places teaching first; however, research and scholarship are still required activities for reaching retention, tenure, and promotion, as well as important skills for students to practice. Data management instruction for both faculty and undergraduates is often omitted at these institutions, which fall outside of the R1 designation. This happens for a variety of reasons, including personnel and resource limitations. Such limitations disproportionately burden students from underrepresented populations, who are more heavily represented at these institutions. These students have pathways to graduate school and the digital economy, like their counterparts at R1s; thus, they are also in need of research data management skills. This paper describes and provides a scalable, low-resource model for data management instruction from the university library and integrated into a department’s capstone or final project curriculum. In the case study, students and their instructors participated in workshops and submitted data management plans as a requirement of their final project. The analysis will analyze the results of the project and focus on the broader implications of integrating research data management into undergraduate curriculum at public, regional universities. By working with faculty to integrate data management practices into their curricula, librarians reach both students and faculty members with best practices for research data management. This work also contributes to a more equitable and sustainable research landscape.

scholarly journals Ecological illiteracy can deepen farmers' pesticide dependency

2019 ◽  
Author(s):  
Kris Wyckhuys ◽  
KL Heong ◽  
Francisco Sanchez-Bayo ◽  
Felix Bianchi ◽  
Jonathan Lundgren ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Management Practices ◽  
Arable Land ◽  
Global Environmental Change ◽  
Social Science Research ◽  
Science Research ◽  
Biodiversity Loss ◽  
Ecological Literacy ◽  
Ecological Concepts ◽  
Knowledge Intensive

Over 2.5 billion smallholders cultivate the world’s arable land, strategically positioned to tackle multiple Anthropocene challenges. When consciously adopting ecologically-based pest management practices, they can improve resource use efficiency, slow biodiversity loss, resolve environmental pollution and safeguard human health. Yet, the effective implementation of knowledge-intensive management practices requires underlying ecological concepts to be well-understood. Here, drawing upon published social science research spanning 1910-2016, we illuminate deficiencies in the world’s farmers’ ecological literacy and in their valuation of insect-mediated ecosystem services. Though tribal people and indigenous folk possess sophisticated knowledge of insects that occur within farm settings, contemporary farmers know a mere 2.0 pestiferous herbivores and 0.8 pest-killing organisms (out of a respective 8 and 3 taxa). Ecosystem services such as biological control are annually worth hundreds of dollars ha-1 but remain unknown to nearly 70% of farmers globally. Also, agricultural systems with deficient ecological literacy tend to foster a greater dependency upon chemically-synthesized pesticides. If this ‘cognitive handicap’ can be remediated, farmers could become biodiversity stewards and champions in redressing multiple aspects of global environmental change.

scholarly journals Research data management in Turkey: perceptions and practices

2017 ◽  
Vol 35 (2) ◽  
pp. 271-289 ◽  
Author(s):  
Arsev Umur Aydinoglu ◽  
Guleda Dogan ◽  
Zehra Taskin
Keyword(s):  
Data Management ◽  
Online Survey ◽  
Management Practices ◽  
Cost Effective ◽  
Science Research ◽  
Research Data ◽  
Content Type ◽  
Research Data Management ◽  
Data Practices ◽  
The Subject

Purpose The massive increase in research data being produced nowadays has highlighted the importance of research data management (RDM) to science. Research data not only have to be cost effective but also reliable, discoverable, accessible, and reusable. In this regard, the purpose of this paper is to investigate the perceptions and practices of Turkish researchers on the subject of RDM. Design/methodology/approach An online survey was distributed to the academicians in 25 universities in Turkey, and 532 responses were gathered. Findings Results indicate that although Turkish researchers are aware of the benefits of data management, are willing to share their research data with certain groups, and have decent preservation habits, they express that they lack the technical skills and knowledge needed for RDM. In addition, no institutionalized support (staff, training, software, and hardware) is provided to researchers. Research limitations/implications A well-structured data strategy or policy that includes resource allocation (awareness, training, software/hardware) and is supported by Turkish research agencies is required for better data management practices among researchers in Turkey. Originality/value This is the first study that investigates the data practices of Turkish academics who produce around 30,000 scientific articles annually that are indexed by Web of Science. It contributes to the growing literature on RDM.

scholarly journals Support Your Data: A Research Data Management Guide for Researchers

2018 ◽  
Vol 4 ◽  
pp. e26439 ◽  
Author(s):  
John Borghi ◽  
Stephen Abrams ◽  
Daniella Lowenberg ◽  
Stephanie Simms ◽  
John Chodacki
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Current Data ◽  
Research Data Management

Researchers are faced with rapidly evolving expectations about how they should manage and share their data, code, and other research materials. To help them meet these expectations and generally manage and share their data more effectively, we are developing a suite of tools which we are currently referring to as "Support Your Data". These tools, which include a rubric designed to enable researchers to self-assess their current data management practices and a series of short guides which provide actionable information about how to advance practices as necessary or desired, are intended to be easily customizable to meet the needs of a researchers working in a variety of institutional and disciplinary contexts.

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