scholarly journals Planning Data Management Education Initiatives: Process, Feedback, and Future Directions

2014 ◽  
Vol 3 (1) ◽  
Author(s):  
Christopher Eaker ◽  
Web Services ◽  
2019 ◽  
pp. 2230-2254
Author(s):  
Amandeep Kaur Kahlon ◽  
Ashok Sharma

The major concern in this chapter is to understand the need of system biology in prediction models in studying tuberculosis infection in the big data era. The overall complexity of biological phenomenon, such as biochemical, biophysical, and other molecular processes, within pathogen as well as their interaction with host is studied through system biology approaches. First, consideration is given to the necessity of prediction models integrating system biology approaches and later on for their replacement and refinement using high throughput data. Various ongoing projects, consortium, databases, and research groups involved in tuberculosis eradication are also discussed. This chapter provides a brief account of TB predictive models and their importance in system biology to study tuberculosis and host-pathogen interactions. This chapter also addresses big data resources and applications, data management, limitations, challenges, solutions, and future directions.


2018 ◽  
Vol 12 (2) ◽  
pp. 246-254 ◽  
Author(s):  
Veronica A Ikeshoji-Orlati ◽  
Clifford B Anderson

This paper examines the intersection of legacy digital humanities projects and the ongoing development of research data management services at Vanderbilt University’s Jean and Alexander Heard Library. Future directions for data management and curation protocols are explored through the lens of a case study: the (re)curation of data from an early 2000s e-edition of Raymond Poggenburg’s Charles Baudelaire: Une Micro-histoire. The vagaries of applying the Library of Congress Metadata Object Description Schema (MODS) to the data and metadata of theMicro-histoirewill be addressed. In addition, the balance between curating data and metadata for preservation vs. curating it for (re)use by future researchers is considered in order to suggest future avenues for holistic research data management services at Vanderbilt.


Author(s):  
Tina M Griffin

Introduction It is known that graduate students work with research data more intimately than their faculty mentors. Because of this, much data management education is geared toward this population. However, student learning has predominantly been assessed through measures of satisfaction and attendance rather than through evaluating knowledge and skills acquired. This study attempts to advance assessment efforts by asking students to report their knowledge and practice changes before, immediately after, and six months following education. Methods Graduate students in STEM and Health sciences disciplines self-enrolled in an eight-week data management program that used their research projects as the focus for learning. Three surveys were administered (pre, post, and six months following) to determine changes in students’ knowledge and practices regarding data management skills. The survey consisted of approximately 115 Likert-style questions and covered major aspects of the data life cycle. Results & discussion Overall students increased their data management knowledge and improved their skills in all areas of the data life cycle. Students readily adopted practices for straightforward tasks like determining storage and improving file naming. Students improved but struggled with tasks that were more involved like sharing data and documenting code. For most of these practices, students consistently implemented them through the six month follow up period. Conclusion Impact of data management education lasts significantly beyond immediate instruction. In depth assessment of student knowledge and practices indicates where this education is effective and where it needs further support. It is likely that this effect is due to the program length and focus on implementation.


2015 ◽  
pp. 147-153
Author(s):  
Marcia G. Ory ◽  
SangNam Ahn ◽  
Samuel D. Towne ◽  
Matthew Lee Smith

2017 ◽  
Vol 15 (3) ◽  
pp. 268-302 ◽  
Author(s):  
J. B. Arbaugh ◽  
Carlos J. Asarta ◽  
Alvin Hwang ◽  
Charles J. Fornaciari ◽  
Regina F. Bento ◽  
...  

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