Thoughts on “eResearch”: a Scientist’s Perspective

In response to the burgeoning practice of collaborative, networked, data-intensive research (known as eScience), university and research libraries are devoting significant consideration, effort and resources toward expanding their responsibilities to include research data services. The jargon that the librarianship community uses to discuss data -driven research is inconsistent and confusing, especially to non-librarians. This is problematic because when we attempt to engage research scientists in an effort to provide services, we risk alienating our potential stakeholders by using language that they don’t understand. As a recent transplant to the library community, the difference between librarian and research scientist perceptions of data-driven research, and the vocabulary surrounding it, have been surprising. This paper summarizes the problem of “eResearch,” spoken from the perspective of a recent scientist-turned-data librarian. The main conclusions reached are that “eResearch” is a meaningless term that should be avoided, and that data support services needn’t be couched as an eScience issue

Implementing a Graduate-level Data Information Literacy Curriculum at Oregon State University: Approach, Outcomes and Lessons Learned

Purpose This poster examines the development and inaugural offering of a credit-bearing graduate-level course in data information literacy (DIL). The purpose of the course was to enable students to acquire foundational knowledge and skills in DIL that would support long-term habits in planning, management, preservation and sharing of research data. Setting/Participants Oregon State University Libraries partnered with the Graduate School to facilitate the process of establishing a new credit-bearing course in the OSU catalog. The course is open to graduate students from all disciplines without any prerequisites, and is taught by the Libraries’ Data Management Specialist. Brief Description This poster describes the development and implementation of a new course in data information literacy for graduate students. Curricular materials were drawn from the New England Collaborative Data Management Curriculum (NECDMC), the DataONE Education Modules, and the MANTRA online course materials. The pedagogical approach for the course combined outcomes-centered course design with active learning techniques. The approach was predicated on the idea that getting the students actively engaged with the content and techniques of data management would be more effective than lecture alone. This approach was also driven by the practical reality that while the course content was necessarily discipline agnostic, successful learning outcomes depended on the students’ ability to apply the material to discipline specific standards of practice (e.g. metadata and data documentation, data sharing formats and methods, etc.). The goal was that after taking the course, the students would successfully incorporate data management best practices into their daily workflow. Such behavioral change takes self-reflection ( How does this material relate to me? ) and practice, both of which I strove to offer during class meetings. The 2-credit class met twice per week for 50 minutes. For each meeting a lesson plan was created that included anticipated timing, learning outcomes, lecture content, teaching strategies, student products, the DIL core competency addressed and assessment approach, if any. Lesson plans also included the associated readings and homework assignment, if any. Not every specific learning outcome had an assessment component, but closely related outcomes were assessed together. Periodic course assessment was also performed through anonymous student surveys, with the objective of gauging course efficacy and quality, and to obtain suggested modifications or improvements. The midterm assignment for the course was a scaled back Data Curation Profile, and the final exam assignment was to create a data management plan for their research project. Results/Outcome The inaugural course had an official enrollment of 11 students, including one faculty member enrolled for credit and two as non-credit auditors. I also had an additional faculty member “sitting in” on lectures who did not complete any of the outside assignments. The disciplinary range of the students was broad: six students from the College of Public Health and Human Sciences, two from the College of Forestry, and one each from the Colleges of Veterinary Medicine, Science, and Agriculture. Aside from the faculty members, student degree paths ranged from non-thesis master’s to Ph.D., with some of the students having a very well defined research project already planned and others much less so. With all of the variability in student disciplinary background and experience, in-class learning activities and the homework, midterm and final exam assignments were relied upon to facilitate application of the generalized course content to their individual, discipline-specific circumstances. The content and quality of the students’ assignments demonstrated that this approach was successful. Conclusions The course is not yet complete at the time of this abstract submission, but the poster will summarize the during- and post-class surveys that were used to determine the success and impact of the instruction. Suggested modifications for next year’s course will also be discussed

Implementing a Graduate-Level Research Data Management Course: Approach, Outcomes, and Lessons Learned

INTRODUCTION: As data-driven research becomes the norm, practical knowledge in data stewardship is critical for researchers. Despite its growing importance, formal education in research data management (RDM) is rare at the university level. Academic librarians are now playing a leadership role in developing and providing RDM training and support to faculty and graduate students. This case study describes the development and implementation of a new, credit-bearing course in RDM for graduate students from all disciplines. DESCRIPTION OF PROGRAM: The purpose of the course was to enable students to acquire foundational knowledge and skills in RDM that would support long-term habits in the planning, management, preservation, and sharing of research data. The pedagogical approach for the course combined outcomes-centered course design with active learning techniques. Periodic course assessment was performed through anonymous student surveys, with the objective of gauging course efficacy and quality, and to obtain suggested modifications or improvements. These assessment results indicated that the course content and scope were appropriate and that the active learning approach was effective. Assessments of student learning demonstrated that all major learning objectives were achieved. NEXT STEPS: Information derived from the student surveys was used to determine how the course could be modified to improve student experience and the overall quality of the course and the instruction.This is the publisher’s final pdf. The published article is copyrighted by Amanda L. Whitmire, and can be found at: http://jlsc-pub.org/. This paper should be cited as, "Whitmire, A. L. (2015). Implementing a Graduate-Level Research Data Management Course: Approach, Outcomes, and Lessons Learned. Journal of Librarianship and Scholarly Communication, 3(2), eP1246. http://dx.doi.org/10.7710/2162-3309.1246.

Implementing a Graduate-Level Research Data Management Course: Approach, Outcomes, and Lessons Learned

INTRODUCTION: As data-driven research becomes the norm, practical knowledge in data stewardship is critical for researchers. Despite its growing importance, formal education in research data management (RDM) is rare at the university level. Academic librarians are now playing a leadership role in developing and providing RDM training and support to faculty and graduate students. This case study describes the development and implementation of a new, credit-bearing course in RDM for graduate students from all disciplines. DESCRIPTION OF PROGRAM: The purpose of the course was to enable students to acquire foundational knowledge and skills in RDM that would support long-term habits in the planning, management, preservation, and sharing of research data. The pedagogical approach for the course combined outcomes-centered course design with active learning techniques. Periodic course assessment was performed through anonymous student surveys, with the objective of gauging course efficacy and quality, and to obtain suggested modifications or improvements. These assessment results indicated that the course content and scope were appropriate and that the active learning approach was effective. Assessments of student learning demonstrated that all major learning objectives were achieved. NEXT STEPS: Information derived from the student surveys was used to determine how the course could be modified to improve student experience and the overall quality of the course and the instruction

Implementing a graduate-level data information literacy curriculum at Oregon State University: approach, outcomes and lessons learned

This poster describes the development and implementation of a new course in data information literacy for graduate students. Curricular materials were drawn from the New England Collaborative Data Management Curriculum (NECDMC), the DataONE Education Modules, and the MANTRA online course materials. The pedagogical approach for the course combined outcomes-centered course design with active learning techniques. The approach was predicated on the idea that getting the students actively engaged with the content and techniques of data management would be more effective than lecture alone. This approach was also driven by the practical reality that while the course content was necessarily discipline agnostic, successful learning outcomes depended on the students’ ability to apply the material to discipline specific standards of practice (e.g. metadata and data documentation, data sharing formats and methods, etc.). The goal was that after taking the course, the students would successfully incorporate data management best practices into their daily workflow. Such behavioral change takes self-reflection ("How does this material relate to me?") and practice, both of which I strove to offer during class meetings. The 2-credit class met twice per week for 50 minutes. For each meeting a lesson plan was created that included anticipated timing, learning outcomes, lecture content, teaching strategies, student products, the DIL core competency addressed and assessment approach, if any. Lesson plans also included the associated readings and homework assignment, if any. Not every specific learning outcome had an assessment component, but closely related outcomes were assessed together. Periodic course assessment was also performed through anonymous student surveys, with the objective of gauging course efficacy and quality, and to obtain suggested modifications or improvements. The midterm assignment for the course was a scaled back Data Curation Profile, and the final exam assignment was to create a data management plan for their research project. The inaugural course had an official enrollment of 11 students, including one faculty member enrolled for credit and two as non-credit auditors. I also had an additional faculty member “sitting in” on lectures who did not complete any of the outside assignments. The disciplinary range of the students was broad: six students from the College of Public Health and Human Sciences, two from the College of Forestry, and one each from the Colleges of Veterinary Medicine, Science, and Agriculture. Aside from the faculty members, student degree paths ranged from non-thesis master’s to Ph.D., with some of the students having a very well defined research project already planned and others much less so. With all of the variability in student disciplinary background and experience, in-class learning activities and the homework, midterm and final exam assignments were relied upon to facilitate application of the generalized course content to their individual, discipline-specific circumstances. The content and quality of the students’ assignments demonstrated that this approach was successful.This entry includes the conference poster and supplementary materials including: course syllabus, lesson plans, assessment survey, and survey responses.Keywords: curriculum, data management, instruction, pedagogy, evaluation, active learning, data information literac

Thoughts on “eResearch”: a Scientist’s Perspective

In response to the burgeoning practice of collaborative, networked, data-intensive research (known as eScience), university and research libraries are devoting significant consideration, effort and resources toward expanding their responsibilities to include research data services. The jargon that the librarianship community uses to discuss data-driven research is inconsistent and confusing, especially to non-librarians. This is problematic because when we attempt to engage research scientists in an effort to provide services, we risk alienating our potential stakeholders by using language that they don’t understand. As a recent transplant to the library community, the difference between librarian and research scientist perceptions of data-driven research, and the vocabulary surrounding it, have been surprising. This paper summarizes the problem of “eResearch,” spoken from the perspective of a recent scientist-turned-data librarian. The main conclusions reached are that “eResearch” is a meaningless term that should be avoided, and that data support services needn’t be couched as an eScience issue.Keywords: eScience, Jargon, data management, research data services, eResearchKeywords: eScience, Jargon, data management, research data services, eResearc

The spectral backscattering properties of marine particles

The inherent and apparent optical properties of different ocean regimes are the basis for all optical remote sensing of the ocean. Ecological information derived from remote sensors therefore relies on having a detailed understanding of how particulate backscattering and absorption contribute to the bulk optical signal. The absorption characteristics of oceanic particles, e.g. phytoplankton and marine bacteria, organic detritus, and minerogenic particles, have been well characterized, and there are several ways to determine their contribution to bulk signals. In contrast, the backscattering properties of marine particles are not well understood, and indeed there is still some uncertainty regarding the dominant sources of backscattering in the ocean. Recent advances in optical instrumentation now permit laboratory and in situ examination of the spectral backscattering properties of marine particles, and we use these new tools to improve the characterization of backscattering in the ocean. We first investigated the ratio of backscattering to total scattering across a wide range of oceanic environments and particle types. The spectral dependency of the particulate backscattering ratio (backscattering/scattering in all directions) is relevant in the fields of ocean color inversion, light field modeling, and inferring particle properties from optical measurements. Aside from theoretical predictions for spherical, homogeneous particles, we have had very limited data showing the actual in situ spectral variability of the particulate backscattering ratio. Our analysis of five data sets from different ocean regimes revealed no spectral dependence of the particulate backscattering ratio within our measurement certainty. We did find however, that different particle populations demonstrated qualitative differences in the backscattering ratio. In an effort to better understand the variability that we observed in in situ backscattering, we investigated the spectral backscattering properties of thirteen species of marine phytoplankton using laboratory cultures. Theoretical analysis has shown that the backscattering coefficient and backscattering ratio may be influenced by particle size, shape, composition, and internal structure. We found species-specific relationships between backscattering and photosynthetic pigment concentration, and distinct differences between species in the backscattering ratio. These differences were related to cell size and were likely influenced by internal cell structure and composition. Of particular importance is our finding that backscattering by phytoplankton cells is higher than predicted by model studies. Finally, we used the backscattering coefficient and the backscattering ratio to aid in the discrimination of non-algal particle populations and major phytoplankton taxonomic groups in a complex coastal environment. We combined information from multiple in situ measurements, including chlorophyll concentration, hyperspectral absorption and attenuation, as well as backscattering, to discriminate and track phytoplankton groups and colored detrital matter in an optically complex, nearshore environment. We applied these approaches to interpret a time-series of hyperspectral optical observations from a coastal mooring

Digital Asset Management System Assessment: Use Cases for Digital Infrastructure Re-design

Academic libraries that offer digital asset management systems (DAMS) and services such as an institutional repository, data curation services, and digitization of historic documents face the need to assess and refine services. This need can be most apparent when considering changes to DAMS infrastructure. The proposed panel presents the experiences of OSU Libraries and Press as we move to a new DAMS system for ScholarsArchive@OSU. Before considering DAMS platforms, we conducted an in-depth requirements analysis with our stakeholders, both within our organization as well as with stakeholders outside of the organization. The panelists will include OSU faculty and administrators selected for requirements interviews who present unique use cases for the DAMS, including those for whom the current iteration of the DAMS does not provide adequate service. Audience members will learn about using requirements analysis to design new digital infrastructures and will learn about popular digital library technologies (e.g. Hydra, DSpace)

Building professional development opportunities in data services for academic librarians

Research data management represents a significant professional development area for academic librarians –significant for its growing importance to the profession, since researchers are increasingly expected to comply with research data management requirements, and for the extent of competence needed by librarians to support researchers in research data management practices and plans. This article recounts how the Association of College and Research Libraries is fostering professional development opportunities in research data management. The authors describe two key endeavors: (1) the development and deployment of a needs assessment survey, which allowed insight into the types of librarians expressing the most need; and (2) planning and implementation of a pre-conference workshop for ACRL 2015, intended to prototype a future professional development offering. The article concludes by discussing additional assessment that was done following the workshop and how the pre-conference laid the foundation for proposing a ‘‘roadshow’’ for research data management, similar to what the Association of College and Research Libraries sponsors for scholarly communication