scholarly journals Better data management, one nudge at a time

2021 ◽  
Vol 45 (2) ◽  
Author(s):  
Hoa Luong ◽  
Daria Orlowska ◽  
Colleen Fallaw ◽  
Yali Feng ◽  
Livia Garza ◽  
...  
Keyword(s):  
Best Practices ◽  
Data Management ◽  
Management Practices ◽  
Effective Means ◽  
Marketing Channels ◽  
Management Skills ◽  
University Of Illinois ◽  
Data Services ◽  
The University ◽  
And Training

How do you help people improve their data management skills? For our team at the University of Illinois at Urbana-Champaign, we decided the answer was "one nudge at a time”. A study conducted by Wiley and Mischo (2016) found that Illinois researchers are aware of data services available but under-utilize them. Many researchers do not consider data management as a concern distinct from researching and producing scholarly work products. In 2017, the RDS piloted the Data Nudge – a monthly, opt-in email service to “nudge” Illinois researchers toward good data management practices, and towards utilizing data services on campus. The aim of the Data Nudge was to address the gap between knowing about a service and using it by highlighting best practices and campus resources. The topics covered in the Data Nudge center around data. Some topics are applicable to everyone, such as data back-up, documentation, and file naming conventions. Other topics are specific to Illinois, like storage options, events, and conferences. After four years, the Data Nudge has accumulated over 400 subscribers through word-of-mouth, marketing channels on campus and inclusion in subject liaisons' instructional workshops. It receives stable open rates averaging at 52% (compared to 19.44% average industry rate for Higher Education*) and many compliments from subscribers. We expect the Data Nudge to continue supplementing workshops and training as an effective means of communication to reach researchers on our campus. In the spirit of re-use, we are in the process of archiving the Data Nudge topics in a reusable format, readily adaptable by other institutions.  Data Nudge link: https://go.illinois.edu/past_nudges

scholarly journals Teaching Research Data Management

2014 ◽  
Vol 6 ◽  
Author(s):  
Wendy Mann
Keyword(s):  
Graduate Students ◽  
Data Management ◽  
Management Training ◽  
Boot Camp ◽  
Research Data ◽  
University Libraries ◽  
Management Skills ◽  
Data Services ◽  
Research Data Management ◽  
The University

In January 2014, Mason Libraries along with four other libraries in Virginia used 4-VA telepresence technology to teach a two-day boot camp to graduate students on research data management. Our workshop generated greater than expected interest from graduate students here at Mason. One lesson learned is that there appears to be a gap in the curriculum across all participating schools regarding the teaching of data management skills to budding researchers. This session will be an overview of the learning outcomes from the Data Management Boot Camp, how the University Libraries' Data Services carries out research data management training, and discussion of future plans for helping researchers organize and manage their data.

scholarly journals Practices and Infrastructures for ML Systems – An Interview Study

2021 ◽  
Author(s):  
Dennis Muiruri ◽  
Lucy Ellen Lwakatare ◽  
Jukka K. Nurminen ◽  
Tommi Mikkonen
Keyword(s):  
Machine Learning ◽  
Best Practices ◽  
Data Management ◽  
Management Practices ◽  
Interview Study ◽  
The State ◽  
Data Driven ◽  
Software Systems ◽  
State Of Practice ◽  
Model Training

<div> <div> <div> <p>The best practices and infrastructures for developing and maintaining machine learning (ML) enabled software systems are often reported by large and experienced data-driven organizations. However, little is known about the state of practice across other organizations. Using interviews, we investigated practices and tool-chains for ML-enabled systems from 16 organizations in various domains. Our study makes three broad observations related to data management practices, monitoring practices and automation practices in ML model training, and serving workflows. These have limited number of generic practices and tools applicable across organizations in different domains. </p> </div> </div> </div>

scholarly journals ACHIEVING DIVERSITY THROUGH ONLINE INTER-INSTITUTIONAL COLLABORATIONS

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Shari McCurdy
Keyword(s):  
Best Practices ◽  
Technology Use ◽  
Culturally Diverse ◽  
Discussion Board ◽  
Asynchronous Discussion ◽  
State University ◽  
Web Based ◽  
University Of Illinois ◽  
The University ◽  
Institutional Boundaries

This paper examines best practices for technology use in online, collaborations between the University of Illinois at Springfield and Chicago State University in class sessions shared across institutional boundaries. We explore the collaborations between these two ethnically and culturally diverse institutions. The University of Illinois at Springfield received two grants in the fall of 2004 to address the challenge of encouraging diversity in online and on campus classes. One grant, from the Illinois Board of Higher Education supported the development of online collaborations between classes at UIS with astudent population that is approximately 9% ethnic minority and Chicago State University with a student population that is more than 90% ethnic. Highlighted are synchronous and asynchronous exchanges using Elluminate Live’s synchronous, web-based two–way audio conferencing and Blackboard’s asynchronous discussion board technologies.

scholarly journals Student Research Data Management Practices at UC Data Day 2017

2017 ◽  
Author(s):  
Amy E Koshoffer ◽  
Keloni Parks
Keyword(s):  
Student Engagement ◽  
Data Management ◽  
Poster Session ◽  
Management Practices ◽  
Research Data ◽  
Student Research ◽  
Research Data Management ◽  
University Of Cincinnati ◽  
The University

This article discusses increasing student engagement surrounding data management and how the University of Cincinnati Libraries tried to engage students with a poster session for its Data Day event in 2017.

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 Towards a Unified University Infrastructure: The Data Management Roll-Out at the University of Oxford

2013 ◽  
Vol 8 (2) ◽  
pp. 235-246 ◽  
Author(s):  
James A. J. Wilson ◽  
Paul Jeffreys
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Policy ◽  
Research Information ◽  
Institutional Level ◽  
Research Data Management ◽  
University Of Oxford ◽  
The University ◽  
And Training ◽  
Roll Out

Since presenting a paper at the International Digital Curation Conference 2010 conference entitled ‘An Institutional Approach to Developing Research Data Management Infrastructure’, the University of Oxford has come a long way in developing research data management (RDM) policy, tools and training to address the various phases of the research data lifecycle. Work has now begun on integrating these various elements into a unified infrastructure for the whole university, under the aegis of the Data Management Roll-out at Oxford (Damaro) Project.This paper will explain the process and motivation behind the project, and describes our vision for the future. It will also introduce the new tools and processes created by the university to tie the individual RDM components together. Chief among these is the ‘DataFinder’ – a hierarchically-structured metadata cataloguing system which will enable researchers to search for and locate research datasets hosted in a variety of different datastores from institutional repositories, through Web 2 services, to filing cabinets standing in department offices. DataFinder will be able to pull and associate research metadata from research information databases and data management plans, and is intended to be CERIF compatible. DataFinder is being designed so that it can be deployed at different levels within different contexts, with higher-level instances harvesting information from lower-level instances enabling, for example, an academic department to deploy one instance of DataFinder, which can then be harvested by another at an institutional level, which can then in turn be harvested by another at a national level.The paper will also consider the requirements of embedding tools and training within an institution and address the difficulties of ensuring the sustainability of an RDM infrastructure at a time when funding for such endeavours is limited. Our research shows that researchers (and indeed departments) are at present not exposed to the true costs of their (often suboptimal) data management solutions, whereas when data management services are centrally provided the full costs are visible and off-putting. There is, therefore, the need to sell the benefits of centrally-provided infrastructure to researchers. Furthermore, there is a distinction between training and services that can be most effectively provided at the institutional level, and those which need to be provided at the divisional or departmental level in order to be relevant and applicable to researchers. This is being addressed in principle by Oxford’s research data management policy, and in practice by the planning and piloting aspects of the Damaro Project.

scholarly journals Research Data Management Education for Future Curators

2013 ◽  
Vol 8 (1) ◽  
pp. 288-294
Author(s):  
Mark Scott ◽  
Richard Boardman ◽  
Philippa Reed ◽  
Simon Cox
Keyword(s):  
Data Management ◽  
Case Studies ◽  
Large Scale ◽  
Management Practices ◽  
Future Generations ◽  
Research Data Management ◽  
Scholarly Communications ◽  
Challenges And Opportunities ◽  
Data Lifecycle ◽  
The University

Science has progressed by “standing on the shoulders of giants” and for centuries research and knowledge have been shared through the publication and dissemination of books, papers and scholarly communications. Moving forward, much of our understanding builds on (large scale) datasets, which have been collected or generated as part of the scientific process of discovery. How will this be made available for future generations? How will we ensure that, once collected or generated, others can stand on the shoulders of the data we produce?Educating students about the challenges and opportunities of data management is a key part of the solution and helps the researchers of the future to start to think about the problems early on in their careers. We have compiled a set of case studies to show the similarities and differences in data between disciplines, and produced a booklet for students containing the case studies and an introduction to the data lifecycle and other data management practices. This has already been used at the University of Southampton within the Faculty of Engineering and is now being adopted centrally for use in other faculties. In this paper, we will provide an overview of the case studies and the guide, and reflect on the reception the guide has had to date.

Coordination of long-term data management in the Gulf of Mexico: Lessons learned and recommendations from two years of cross-agency collaboration

Shore & Beach ◽  
2020 ◽  
pp. 17-22
Author(s):  
Kathryn Keating ◽  
Melissa Gloekler ◽  
Nancy Kinner ◽  
Sharon Mesick ◽  
Michael Peccini ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Data Management ◽  
Management Practices ◽  
Collaborative Work ◽  
Lessons Learned ◽  
The Many ◽  
Diverse Data ◽  
The University ◽  
Term Data

This paper presents a summary of collaborative work, lessons learned, and suggestions for next steps in coordinating long-term data management in the Gulf of Mexico in the years following the Deepwater Horizon oil spill (DWH). A decade of increased research and monitoring following the DWH has yielded a vast amount of diverse data collected from response and assessment efforts as well as ongoing restoration efforts. To maximize the benefits of this data through proper management and coordination, a cross-agency and organization Long-Term Data Management (LTDM) working group was established in 2017 with sponsorship from NOAA’s Office of Response and Restoration (OR&R) and NOAA’s National Marine Fisheries Service Restoration Center (NMFS RC) and facilitated by the University of New Hampshire’s Coastal Response Research Center. This paper will describe the LTDM working group’s efforts to foster collaboration, data sharing, and best data management practices among the many state, federal, academic and non-governmental entities working to restore and improve the coastal environment in the Gulf following the DWH. Through collaborative workshops and working groups, participants have helped to characterize region-specific challenges, identify areas for growth, leverage existing connections, and develop recommended actions for stakeholders at all organizational levels who share an interest in data coordination and management activities.

Research Data Management Practices in University libraries: A study

2017 ◽  
Vol 37 (6) ◽  
pp. 417 ◽  
Author(s):  
Manorama Tripathi ◽  
Archana Shukla ◽  
Sharad Kumar Sonkar
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Research Data ◽  
Data Reuse ◽  
University Libraries ◽  
Research Data Management ◽  
The World ◽  
The University

<p>The paper has studied the research data management (RDM) services implemented by different university libraries for managing, organizing, curating and preserving research data generated at their universities’ departments and laboratories, for data reuse and sharing. It has surveyed the central university libraries and the best 20 university libraries of the world to highlight how RDM is extended to the researchers. Further, it has suggested a model for the university libraries in the country to follow for actually deploying RDM services. </p>

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