Bibliographic Indexing Leader
Register for the September 28th webinar
metadata: counts of papers by yer, researcher, institution, province, region and country. scientific fields subfields
metadata in one-credit course as a topic:
publisher – suppliers =- Elsevier processes – Scopus Data
h-index: The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist’s most cited papers and the number of citations that they have received in other publications.
Librarians and APIs 101: overview and use cases
Christina Harlow, Library Data Specialist;Jonathan Hartmann, Georgetown Univ Medical Center; Robert Phillips, Univ of Florida
The era of e-science demands new skill sets and competencies of researchers to ensure their work is accessible, discoverable and reusable. Librarians are naturally positioned to assist in this education as part of their liaison and information literacy services.
Research data literacy and the library
Christian Lauersen, University of Copenhagen; Sarah Wright, Cornell University; Anita de Waard, Elsevier
Data Literacy: access, assess, manipulate, summarize and present data
Statistical Literacy: think critically about basic stats in everyday media
Information Literacy: think critically about concepts; read, interpret, evaluate information
data information literacy: the ability to use, understand and manage data. the skills needed through the whole data life cycle.
Shield, Milo. “Information literacy, statistical literacy and data literacy.” I ASSIST Quarterly 28. 2/3 (2004): 6-11.
Carlson, J., Fosmire, M., Miller, C. C., & Nelson, M. S. (2011). Determining data information literacy needs: A study of students and research faculty. Portal: Libraries & the Academy, 11(2), 629-657.
Courses developed: NTRESS 6600 research data management seminar. six sessions, one-credit mini course
BIOG 3020: Seminar in Research skills for biologists; one-credit semester long for undergrads. data management organization http://guides.library.cornell.edu/BIOG3020
- lack of formal training for students working with data.
- faculty assumed that students have or should have acquired the competencies earlier
- students were considered lacking in these competencies
- the competencies were almost universally considered important by students and faculty interviewed
ideas behind data information literacy, such as the twelve data competencies.
Johnston, L., & Carlson, J. (2015). Data Information Literacy : Librarians, Data and the Education of a New Generation of Researchers. Ashland: Purdue University Press. http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dnlebk%26AN%3d987172%26site%3dehost-live%26scope%3dsite
NEW ROLESFOR LIbRARIANS: DATAMANAgEMENTAND CURATION
the capacity to manage and curate research data has not kept pace with the ability to produce them (Hey & Hey, 2006). In recognition of this gap, the NSF and other funding agencies are now mandating that every grant proposal must include a DMP (NSF, 2010). These mandates highlight the benefits of producing well-described data that can be shared, understood, and reused by oth-ers, but they generally offer little in the way of guidance or instruction on how to address the inherent issues and challenges researchers face in complying. Even with increasing expecta-tions from funding agencies and research com-munities, such as the announcement by the White House for all federal funding agencies to better share research data (Holdren, 2013), the lack of data curation services tailored for the “small sciences,” the single investigators or small labs that typically comprise science prac-tice at universities, has been identified as a bar-rier in making research data more widely avail-able (Cragin, Palmer, Carlson, & Witt, 2010).Academic libraries, which support the re-search and teaching activities of their home institutions, are recognizing the need to de-velop services and resources in support of the evolving demands of the information age. The curation of research data is an area that librar-ians are well suited to address, and a num-ber of academic libraries are taking action to build capacity in this area (Soehner, Steeves, & Ward, 2010)
REIMAgININg AN ExISTINg ROLEOF LIbRARIANS: TEAChINg INFORMATION LITERACY SkILLS
By combining the use-based standards of information literacy with skill development across the whole data life cycle, we sought to support the practices of science by develop-ing a DIL curriculum and providing training for higher education students and research-ers. We increased ca-pacity and enabled comparative work by involving several insti-tutions in developing instruction in DIL. Finally, we grounded the instruction in the real-world needs as articu-lated by active researchers and their students from a variety of fields
Chapter 1 The development of the 12 DIL competencies is explained, and a brief compari-son is performed between DIL and information literacy, as defined by the 2000 ACRL standards.
chapter 2 thinking and approaches toward engaging researchers and students with the 12 competencies, a re-view of the literature on a variety of educational approaches to teaching data management and curation to students, and an articulation of our key assumptions in forming the DIL project.
Chapter 3 Journal of Digital Curation. http://www.ijdc.net/
chapter 4 because these lon-gitudinal data cannot be reproduced, acquiring the skills necessary to work with databases and to handle data entry was described as essential. Interventions took place in a classroom set-ting through a spring 2013 semester one-credit course entitled Managing Data to Facilitate Your Research taught by this DIL team.
chapter 5 embedded librar-ian approach of working with the teaching as-sistants (TAs) to develop tools and resources to teach undergraduate students data management skills as a part of their EPICS experience.
Lack of organization and documentation presents a bar-rier to (a) successfully transferring code to new students who will continue its development, (b) delivering code and other project outputs to the community client, and (c) the center ad-ministration’s ability to understand and evalu-ate the impact on student learning.
skill sessions to deliver instruction to team lead-ers, crafted a rubric for measuring the quality of documenting code and other data, served as critics in student design reviews, and attended student lab sessions to observe and consult on student work
chapter 6 Although the faculty researcher had created formal policies on data management practices for his lab, this case study demonstrated that students’ adherence to these guidelines was limited at best. Similar patterns arose in discus-sions concerning the quality of metadata. This case study addressed a situation in which stu-dents are at least somewhat aware of the need to manage their data;
chapter 7 University of Minnesota team to design and implement a hybrid course to teach DIL com-petencies to graduate students in civil engi-neering.
stu-dents’ abilities to understand and track issues affecting the quality of the data, the transfer of data from their custody to the custody of the lab upon graduation, and the steps neces-sary to maintain the value and utility of the data over time.
more on Scopus in this IMS blog