全部 标题 作者
关键词 摘要


Research on the Hierarchical Training Model of Data Service Ability for University Librarians

DOI: 10.4236/oalib.1103979, PP. 1-11

Subject Areas: Information Science, Library, Intelligence and Philology

Keywords: University Library, Data Service, Hierarchical Training

Full-Text   Cite this paper   Add to My Lib

Abstract

On the basis of elaborating the job responsibilities of the data librarians and the data service ability that should be possessed, put forward that the university library should adopt the data skill hierarchical training and progressive development mode, the general education training mode, the special training mode and the development mode, and introduced the corresponding safeguards.

Cite this paper

Hu, S. (2017). Research on the Hierarchical Training Model of Data Service Ability for University Librarians. Open Access Library Journal, 4, e3979. doi: http://dx.doi.org/10.4236/oalib.1103979.

References

[1]  Cremer, A., Morales, M.E. and Crespo, J. (2012) An Assessment of Needed Competencies to Promote the Data Curation and Management Librarianship of Health Sciences and Science and Technology Librarians in New England. Journal of e-science Librarianship, 1, 18-26.
https://doi.org/10.7191/jeslib.2012.1006
[2]  Patil, T.H. (2012) Data Scientist: The Sexiest Job of the 21st Century. Harvard Ausiuess Review, 10, 1-5.
[3]  Castiglione, A., Gribaudo, M., Iacono, M. and Palmieri, F. (2014) Exploiting Mean Field Analysis to Model Performances of Big Data Architectures. Future Generation Computer Systems, 37, 203-211.
https://doi.org/10.1016/j.future.2013.07.016
[4]  Ayalp, G. and Ocal, M. (2016) Determining Construction Management Education Qualifications and the Effects of Con-struction Management Education Deficiencies on Turkish Construction. Creative Education, 7, 254-268.
https://doi.org/10.4236/ce.2016.72024
[5]  Ribeiro, A., Silva, A. and da Silva, A.R. (2015) Data Modeling and Data Analytics: A Survey from a Big Data Perspective. Journal of Software Engineering and Applications, 8, 617-634.
https://doi.org/10.4236/jsea.2015.812058
[6]  Kord, H., Damani, F. and Parvaresh, A. (2015) The Study of Occupational Stress and Its Relationship with Knowledge Management Based on HSE Model. Creative Education, 6, 1416-1427.
https://doi.org/10.4236/ce.2015.612142
[7]  Asher, A., Henry, C. and Jahnke, L. (2015) The Problem of Data.
http://www.clir.org/pubs/reports/pub154/pub154.pdf
[8]  Pinfield, S., Cox, A.M. and Smith, J. (2014) Research Data Management and Libraries: Relationships, Activities, Drivers and Influences .PloSone, 9, e114734.
https://doi.org/10.1371/journal.pone.0114734
[9]  Bradji, L. and Boufaida, M. (2011) A Rule Management System for Knowledge Based Data Cleaning. Intelligent Information Management, 3, 230-239.
https://doi.org/10.4236/iim.2011.36028
[10]  Azim, R., Rahman, A., Barua, S. and Jahan, I. (2016) Risk Analysis Technique on Inconsistent Interview Big Data Based on Rough Set Approach. Journal of Data Analysis and Information Processing, 4, 101-114.
https://doi.org/10.4236/jdaip.2016.43009
[11]  Vargas, G., Vanderkast, E., García, A. and González, J. (2015) The Blended Librarian and the Disruptive Technological Innovation in the Digital World. Open Access Library Journal, 2, 1-9.

Full-Text


comments powered by Disqus