This paper will discuss a supplement received in support of a grant from the National Institute of Dental and Craniofacial Research (PI: Brian Schmidt) on the role of proteases and peptides in cancer pain. A number of barriers were preventing the research team from maximizing the efficiency and effectiveness of their work. A critical component of the research was to identify which proteins, from among hundreds identified in collected samples, to include in preclinical testing. This selection involved laborious and prohibitively time-consuming manual searching of the literature on protein function. Additionally, the research team encompassed ten investigators working in two different cities, which led to issues around the sharing and tracking of both data and citations.

The supplement outlined three areas in which the informationists would assist the researchers in overcoming these barriers: 1) creating an automated literature searching system for protein function discovery, 2) introducing tools and associated workflows for sharing citations, and 3) introducing tools and workflows for sharing data and specimens.

For 18 months, the informationist is serving as a member of the research team on the grant, “Promoting Breast Cancer Screening in Non-Adherent Women” (R01 CA-132935, National Cancer Institute, National Institutes of Health), working to develop data management tools, providing an in-depth literature review and report on the issues facing researchers and internet technology professionals when building and implementing research tools, assisting with a systematic review on the effectiveness of telephone intervention protocols for preventive screenings, and instructing the members of the team in advanced searching techniques and bibliographic management.

This role serves as a new model of embedded librarianship for the LSL. It also provides opportunities for new services from the Library in the role of data and information management. Further, the acceptance of an informationist into a well-funded research team demonstrates a level of commitment by researchers to receiving research support from the Library that it has not experienced to date. This brief paper describes the study and the accomplishments to date.

Targeted radionuclide therapy is an emerging modality for cancer therapy that involves the delivery of radioactive atoms using carriers that preferentially bind to tumor cells. Such treatment is best implemented with patient-specific dosimetry calculations. This mutually beneficial partnership brings the specialized skill set, knowledge base and expertise of an informationist to the biomedical research team to assist in accomplishing the broader work of improving RPT delivery in metastatic cancer patients.

The informationist will carry out multiple tasks to produce an effective and efficient workflow that facilitates the dissemination of the information to a globally dispersed research team. This collaboration will be evaluated both quantitatively and qualitatively, and the important role of the informationist in the success of this project will demonstrate the value of including an informationist in the research team. This demonstrated value will assist Welch Library in continuing to promote the embedded informationist program to other interested researchers throughout the institution.

Methods: We used directed qualitative content analysis to assess and categorize data and metadata errors identified by peer reviewers of data papers published in the Ecological Society of America’s (ESA) Ecological Archives. Descriptive statistics provided the relative frequency of the errors identified during the peer review process.

Results: There were seven overarching error categories: Collection & Organization, Assure, Description, Preserve, Discover, Integrate, and Analyze/Visualize. These categories represent errors researchers regularly make at each stage of the Data Life Cycle. Collection & Organization and Description errors were some of the most common errors, both of which occurred in over 90% of the papers.

Conclusions: Publishing data for sharing and reuse is error prone, and each stage of the Data Life Cycle presents opportunities for mistakes. The most common errors occurred when the researcher did not provide adequate metadata to enable others to interpret and potentially re-use the data. Fortunately, there are ways to minimize these mistakes through carefully recording all details about study context, data collection, QA/ QC, and analytical procedures from the beginning of a research project and then including this descriptive information in the metadata.

SETTING: This project examined experimental data files from instruments in a teaching laboratory at Brandeis University.

METHODOLOGY: Experimental data files and associated metadata on instrument hard drives were captured and analyzed using Xplorer2 software. Formats were categorized as proprietary or open, and characteristics such as file naming conventions were noted. Discussions with the faculty member and lab staff guided the project scope and informed the findings.

RESULTS: Files in both proprietary and open formats were found on the instrument hard drives. 62% of the experimental data files were in proprietary formats. Image files in various formats accounted for the most prevalent types of data found. Instrument users varied widely in their approaches to data management tasks such as file naming conventions.

CONCLUSIONS: This study found inconsistent approaches to managing data on laboratory instruments. Prevalence of proprietary file formats is a concern with this type of data. Students express frustration in working with these data, and files in these proprietary formats could pose curation and preservation challenges in the future. Teaching labs afford an opportunity for librarians interested in learning more about primary research data and data management practices.

Overview: This paper is based on the Librarian Panel Discussion during the 4th Annual University of Massachusetts and New England Region e-Science Symposium. Librarians representing large public and private research universities presented an overview of service models developed at their respective organizations to bring support for data management and eScience to their communities. The approaches described include two library-based, integrated service models and one collaboratively-staffed, center-based service model.

Results: Three institutions describe their experiences in creating the organizational capacity for research data management support services. Although each institutional approach is unique, common challenges include garnering administrative support, managing the integration of services with new or existing staff structures, and continuing to meet researchers needs as they evolve.

Conclusions: There is no one way to provide research data management services, but any staff position, committee, or formalized center reflects an overarching organizational commitment to data management support.

Design and Setting: Each of eight students was matched with a Cornell Librarian mentor. Other components of the program included program-specific activities and events, virtual communication, and an open invitation to students to participate in Cornell University Library events.

Methods: We conducted an exit survey of both students and mentors at the conclusion of the program. The survey was administered online, with seven of eight students and all mentors completing the survey.

Results and Conclusions: The program was successful in attaining professional acculturation outcomes and professional development outcomes. Results for employment outcomes were mixed (though it was too early to expect most students to have successfully obtained a job), and also mixed for outcomes related to opportunities such as internships and projects. We offer some suggestions for improvement in these areas. Overall, students and mentors had a very positive experience with the program.