Slides presented by Donna Kafel and Regina Raboin at the Oct. 13, 2014 meeting of the Oberlin Science Librarians at Williams College. Discusses pivotal events that have fostered the open data movement, emerging roles for librarians, resources from the NE e-Science Program, and the research data management partnerships and initiatives of Tufts University's Library Research Data Services Working Group.
This presentation was provided by Kristin Lee of Tufts University during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Building Best Practices in Research Data Management: Tisch Library’s Initiatives
Regina F. Raboin, Science Research and Instruction Librarian/ Data Management Services Group Coordinator, Tisch Library, Tufts University
Transforming liaison roles for academic librarians is critical, as universities are moving to position themselves to meet the demands of a more competitive national research environment. At La Trobe University, librarians are repackaging current research support services to streamline and incorporate these more efficiently into the researcher’s life cycle, in order to support the University’s research initiatives
Regina Raboin introduces the New England Collaborative Data Management Curric...Donna Kafel
Presentation about the New England Collaborative Data Management Curriculum by Regina Raboin of Tufts Tisch Library. This presentation was given at the 2014 ALA ALCTS meeting.
This presentation was provided by Kristin Lee of Tufts University during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Building Best Practices in Research Data Management: Tisch Library’s Initiatives
Regina F. Raboin, Science Research and Instruction Librarian/ Data Management Services Group Coordinator, Tisch Library, Tufts University
Transforming liaison roles for academic librarians is critical, as universities are moving to position themselves to meet the demands of a more competitive national research environment. At La Trobe University, librarians are repackaging current research support services to streamline and incorporate these more efficiently into the researcher’s life cycle, in order to support the University’s research initiatives
Regina Raboin introduces the New England Collaborative Data Management Curric...Donna Kafel
Presentation about the New England Collaborative Data Management Curriculum by Regina Raboin of Tufts Tisch Library. This presentation was given at the 2014 ALA ALCTS meeting.
Objectives: To explore potential collaborations between academic libraries and Clinical Translational Science Award (CTSA)-funded institutes with respect to
data management training and support.
Methods: The National Institutes of Health CTSAs have established a well-funded, crucial infrastructure supporting large-scale collaborative biomedical research. This infrastructure is also valuable for smaller, more localized research projects. While infrastructure and corresponding support is often available for large, well-funded projects, these services have generally not been extended to smaller projects. This is a missed opportunity on both accounts. Academic libraries providing data services can leverage CTSA-based resources, while CTSA-funded institutes can extend their reach beyond large biomedical projectsto serve the long tail of research data.
Results: A year-long series of conversations with the Indiana CTSI Data Management Team resulted in resource sharing, consensus building about key issues in data management, provision of expert feedback on a data management training curriculum, and several avenues for future collaborations.
Conclusions:Data management training for graduate students and early career researchers is a vital area of need that would benefit from the combined infrastructure and expertise of translational science institutes and academic libraries. Such partnerships can leverage the instructional, preservation, and access expertise in academic libraries, along with the storage, security, and analytical expertise in translational science institutes to improve the management, protection, and access of valuable research data.
Building a Community for Research Data Services: CLIR/DLF E-Research Peer Net...Inna Kouper
Panel at the Digital Library Federation forum, October 27, 2014.
Authors: Chris Kollen (U of Arizona), Sarah Williams (U of Illinois at Urbana-Champaign), Mayu Ishida (U of Manitoba), Kathleen Fear (U of Rochester), Inna Kouper (Indiana U), Kendall Roark (U of Alberta)
RDAP14: Building a data management and curation program on a shoestring budgetASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
Margaret Henderson
Director, Research Data Management
Virginia Commonwealth University
Tufts Tisch Library's Data Services GroupDonna Kafel
Presentation by Regina Raboin, Data Management Services Group Coordinator and Science Librarian at Tufts University's Tisch Library about Tisch Library's data services initiatives
NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Enabling transparency and efficiency in the research landscape
Dr. Melissa Haendel, Associate Professor, Ontology Development Group, OHSU Library, Department of Medical Informatics and Epidemiology, Oregon Health & Science University
Presentation and workshop notes from session on how to apply the Researcher Development Framework to library and information service provision for research/e support
Uses case studies of different types of researchers.
Workshop notes integrated into the presentation
University of Minnesota’s Lisa Johnston talks about five ways your library can support researchers when sharing their data. From the October 22, 2015 webinar, How to assist researchers in sharing their research data: http://libraryconnect.elsevier.com/library-connect-webinars?commid=175949
Lessons learned from developing the 3TU.Datacentrum research data facility: staffing and more - Jeroen discusses the process of setting up and the evolution of services within a research data facility run by three technical universities in the Netherlands.
This presentation was provided by Carolyn Hansen of the University of Cincinnati during the NISO Training Thursday event, Metadata and the IR, held on Thursday, February 23, 2017.
Organizational Implications of Data Science Environments in Education, Resear...Victoria Steeves
Data science (DS) poses key organizational challenges for academic institutions. DS is a multidisciplinary field that includes a range of research methodologies and fields of inquiry. DS as a domain is interested in many of the same issues as libraries: data access and curation, reproducibility, the value of ontologies, and open scholarship. At the same time, identifying opportunities to collaborate and deploy unified services can be challenging. The Data Science Environment (DSE) program, co-funded by the Gordon and Betty Moore and Alfred P. Sloan foundations, provides resources to help universities develop collaborations between researchers, develop tools in DS, and create new career paths for data scientists. Working groups within the DSE focus on reproducibility, career paths, education/training, research methods, space issues, and software/tools. This program has introduced new opportunities for libraries to explore how to engage with this community and consider how to bring the expertise in the DS community to bear on library missions and goals. In this panel, program members from each of the three partner universities, the University of Washington, New York University and the University of California, Berkeley, consider the research questions of the DSE and the organizational impact of these groups in the University as a whole and for the libraries specifically. The panel will employ a case-study presentation model framed through three lenses: the role of data sciences in information science, the
potential career paths for data scientists in libraries, and the potential
amplification of information services (e.g. data curation, institutional repositories, scholarly publishing).
CNI Program: Talk Description: https://www.cni.org/topics/digital-curation/organizational-implications-of-data-science-environments-in-education-research-and-research-management-in-libraries
Video of Talk--Vimeo: https://vimeo.com/149713097
Video of Talk--YouTube: https://www.youtube.com/watch?v=L0G9JsPMEXY
This presentation was provided by Kristi Holmes of Northwestern University during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Research Data Management in Academic Libraries: Meeting the ChallengeSpencer Keralis
TLA Program Committee sponsored Preconference talk from Texas Library Association Conference 2013.
CPE#388: SBEC 1.0; TSLAC 1.0
April 24, 2013; 4:00 -4:50 pm
Managing research data is a hot topic in academic libraries. With increased government oversight of publicly-funded research projects, librarians must strive to meet the demand for innovative solutions for managing research information and training the new eneration of librarians to address this issue.
Objectives: To explore potential collaborations between academic libraries and Clinical Translational Science Award (CTSA)-funded institutes with respect to
data management training and support.
Methods: The National Institutes of Health CTSAs have established a well-funded, crucial infrastructure supporting large-scale collaborative biomedical research. This infrastructure is also valuable for smaller, more localized research projects. While infrastructure and corresponding support is often available for large, well-funded projects, these services have generally not been extended to smaller projects. This is a missed opportunity on both accounts. Academic libraries providing data services can leverage CTSA-based resources, while CTSA-funded institutes can extend their reach beyond large biomedical projectsto serve the long tail of research data.
Results: A year-long series of conversations with the Indiana CTSI Data Management Team resulted in resource sharing, consensus building about key issues in data management, provision of expert feedback on a data management training curriculum, and several avenues for future collaborations.
Conclusions:Data management training for graduate students and early career researchers is a vital area of need that would benefit from the combined infrastructure and expertise of translational science institutes and academic libraries. Such partnerships can leverage the instructional, preservation, and access expertise in academic libraries, along with the storage, security, and analytical expertise in translational science institutes to improve the management, protection, and access of valuable research data.
Building a Community for Research Data Services: CLIR/DLF E-Research Peer Net...Inna Kouper
Panel at the Digital Library Federation forum, October 27, 2014.
Authors: Chris Kollen (U of Arizona), Sarah Williams (U of Illinois at Urbana-Champaign), Mayu Ishida (U of Manitoba), Kathleen Fear (U of Rochester), Inna Kouper (Indiana U), Kendall Roark (U of Alberta)
RDAP14: Building a data management and curation program on a shoestring budgetASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
Margaret Henderson
Director, Research Data Management
Virginia Commonwealth University
Tufts Tisch Library's Data Services GroupDonna Kafel
Presentation by Regina Raboin, Data Management Services Group Coordinator and Science Librarian at Tufts University's Tisch Library about Tisch Library's data services initiatives
NISO Virtual Conference
Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Enabling transparency and efficiency in the research landscape
Dr. Melissa Haendel, Associate Professor, Ontology Development Group, OHSU Library, Department of Medical Informatics and Epidemiology, Oregon Health & Science University
Presentation and workshop notes from session on how to apply the Researcher Development Framework to library and information service provision for research/e support
Uses case studies of different types of researchers.
Workshop notes integrated into the presentation
University of Minnesota’s Lisa Johnston talks about five ways your library can support researchers when sharing their data. From the October 22, 2015 webinar, How to assist researchers in sharing their research data: http://libraryconnect.elsevier.com/library-connect-webinars?commid=175949
Lessons learned from developing the 3TU.Datacentrum research data facility: staffing and more - Jeroen discusses the process of setting up and the evolution of services within a research data facility run by three technical universities in the Netherlands.
This presentation was provided by Carolyn Hansen of the University of Cincinnati during the NISO Training Thursday event, Metadata and the IR, held on Thursday, February 23, 2017.
Organizational Implications of Data Science Environments in Education, Resear...Victoria Steeves
Data science (DS) poses key organizational challenges for academic institutions. DS is a multidisciplinary field that includes a range of research methodologies and fields of inquiry. DS as a domain is interested in many of the same issues as libraries: data access and curation, reproducibility, the value of ontologies, and open scholarship. At the same time, identifying opportunities to collaborate and deploy unified services can be challenging. The Data Science Environment (DSE) program, co-funded by the Gordon and Betty Moore and Alfred P. Sloan foundations, provides resources to help universities develop collaborations between researchers, develop tools in DS, and create new career paths for data scientists. Working groups within the DSE focus on reproducibility, career paths, education/training, research methods, space issues, and software/tools. This program has introduced new opportunities for libraries to explore how to engage with this community and consider how to bring the expertise in the DS community to bear on library missions and goals. In this panel, program members from each of the three partner universities, the University of Washington, New York University and the University of California, Berkeley, consider the research questions of the DSE and the organizational impact of these groups in the University as a whole and for the libraries specifically. The panel will employ a case-study presentation model framed through three lenses: the role of data sciences in information science, the
potential career paths for data scientists in libraries, and the potential
amplification of information services (e.g. data curation, institutional repositories, scholarly publishing).
CNI Program: Talk Description: https://www.cni.org/topics/digital-curation/organizational-implications-of-data-science-environments-in-education-research-and-research-management-in-libraries
Video of Talk--Vimeo: https://vimeo.com/149713097
Video of Talk--YouTube: https://www.youtube.com/watch?v=L0G9JsPMEXY
This presentation was provided by Kristi Holmes of Northwestern University during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Research Data Management in Academic Libraries: Meeting the ChallengeSpencer Keralis
TLA Program Committee sponsored Preconference talk from Texas Library Association Conference 2013.
CPE#388: SBEC 1.0; TSLAC 1.0
April 24, 2013; 4:00 -4:50 pm
Managing research data is a hot topic in academic libraries. With increased government oversight of publicly-funded research projects, librarians must strive to meet the demand for innovative solutions for managing research information and training the new eneration of librarians to address this issue.
What are we doing about data? Emerging roles in data librarianship and Tales ...Donna Kafel
These slides were presented by Donna Kafel and Regina Raboin at the annual Oberlin Science Librarians meeting on Oct. 13, 2014. Topics include funding data sharing requirements, evolution of data advocacy and data sharing policies, competencies required for managing data, NE e-Science program initiatives,and the activities of Tufts Libraries' Research Data Management Working Group
Social Media & Personal Branding Tips for High School StudentsLiz Jostes
Presentation for the Memphis PREP Program, designed to teach high school juniors and seniors how to use social media and blogging to establish a positive online presence, plus activities and topics to avoid.
Social Media Etiquette for the College StudentLiz Jostes
I presented to a group of journalism students at the University of Memphis about how to use social media to your benefit when it comes to the job search post-graduation. Also, on the "dangers" of how what you post online can come back to haunt you with regards to finding a job. The goods, the bads, and the best practices of social media as it relates to networking, internships and your career.
Teaching research data managament using the NEDMC curriculum. A collaboration between the University of Massachusetts Medical School and Tufts University and other partners. Presentation given by regina Raboin Tufts University at LDAP March 2014
RDAP14: Developing an RDM Educational Service Using the New England Collabora...ASIS&T
Research Data Access and Preservation Summit, 2014
San Diego, CA
March 26-28, 2014
Regina Raboin,
Research Data Management Services Group Coordinator/Science Librarian,
Tufts University
Andrew Creamer, Project Coordinator,
University of Massachusetts Medical School
Donna Kafel, Project Coordinator,
University of Massachusetts Medical School
Elaine Martin, Library Director/NECDMC PI,
University of Massachusetts Medical School
Presentation by Stuart Lewis of the University of Edinburgh. It was presented at the LSHTM Research Data Services workshop on June 30th 2015, an event organised to mark the end of LSHTM's Wellcome Trust funded RDM project.
Presented by Robin Rice at the "IRs dealing with data" workshop at the Open Repositories 2013 Conference in Charlottetown, Prince Edward Island, Canada, on 8 July 2013.
In order to be reused, research data must be discoverable.
The EPSRC Research Data Expectations* requires research organisations to maintain a data catalogue to record metadata about research data generated by EPSRC-funded research projects.
Universities are increasingly making research data assets available through repositories or other data portals.
The requirement for a UK research data discovery service has grown as universities become more involved in RDM and capacity develops.
Going Full Circle: Research Data Management @ University of PretoriaJohann van Wyk
Presentation delivered at the eResearch Africa Conference, held 23-27 November 2014, at the University of Cape Town, Cape Town, South Africa. Various approaches to Research Data Management at Higher Education Institutions focus on an aspect or two of the research data cycle. At the University of Pretoria the approach has been to support researchers throughout the research process covering the whole research data cycle. The idea is to facilitate/capture the research data throughout the research cycle. This will give context to the data and will add provenance to the data. The University of Pretoria uses the UK Data Archive’s research data cycle model, to align its Research Data Management project-development. This model identifies the stages of a research data cycle as: creating data, processing data, analysing data, preserving data, giving access to data, and reusing data. This paper will give a short overview of the chronological development of research data management at the University of Pretoria. The overview will also highlight findings of two surveys done at the University, one in 2009 and one in 2013. This will be followed by a discussion of a number of pilot projects at the University, and how the needs of researchers involved in these projects are being addressed in a number of the stages of the research data cycle. The discussion will also give a short overview of how the University plans to support those stages not currently being addressed. The second part of the presentation will focus on the projects and technology (software and hardware) used. The University of Pretoria has adopted an Enterprise Content Management (ECM) approach to manage its Research Data. ECM is not a singular platform or system but rather a set of strategies, tools and methodologies that interoperate with each other to create a comprehensive management tool. These sets create an all-encompassing process addressing document, web, records and digital asset management. At the University of Pretoria we address all these processes with different software suites and tools to create a complete management system. Each process presented its own technical challenges. These had to be addressed, while keeping in mind the end objective of supporting researchers throughout the whole research process and data life cycle. Various platforms and standards have been adopted to meet the University of Pretoria’s criteria. To date three processes have been addressed namely, the capturing of data during the research process, the dissemination of data and the preservation of data.
Libraries and Research Data Management – What Works? Summary of a Pre-Survey.LIBER Europe
This presentation by Rob Grim was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?
Overview of the UKRDDS pilot project at Univwersity of Edinburgh employing PhD interns to validate metadata about research data created by University of Edinburgh researchers and held in local RDM services solutions. This was presented at IASSIST in June 2016, Bergen, Norway.
ESI Supplemental 1 E-research Support SlidesDuraSpace
E-Research Support at
Johns Hopkins University & Purdue University
Supplemental Webinar
Wednesday, October 17, 2012
Presented by Sayeed Choudhurry & James Mullins
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
What are we doing about data? Emerging roles in data librarianship and Tales from Tufts
1. What are we doing about data?
Emerging roles in data librarianship
and Tales from Tufts
Oberlin Science Librarians’ Meeting
Williams College
October 13, 2014
Donna Kafel
E-Science Program Coordinator
Lamar Soutter Library
Univ.of Massachusetts Medical
School
Regina Raboin
Science Research & Instruction Librarian
Research Data Management Services
Group Coordinator
Tisch Library, Tufts University
2. The Data Deluge
Somebody call a
librarian!
Image:
http://commons.wikimedia.org/wiki/File:The_Deluge_engravi
ng_by_WIlliam_Miller_after_J_Martin.jpg
3. Policies, Reports & Advocacy
2003 NIH Data
Sharing
2006 ARL Report to
NSF
2008 ARL
Reinventing Science
Librarianship forum
2011 Joint Data
Archiving Policy
2011 NSF Data
Management
Requirements
2010 Panton
Principles for Open
Data
2013 OSTP Memo
and Executive
Order
2014 Open
Government
Partnership
2015 NIH Genomic
Data Sharing Policy
4. How do we meet community needs with what we
have?
Taking the pulse of your community and library
1. Learn what research is being done
2. How is it funded?
3. Who on campus is responsible for directing research and supporting
research proposals?
4. How involved is your campus IT with research computing?
5. What is the level of student involvement in research?
6. What are researchers currently doing with data?
7. Assess the skills of your library staff
8. Does your university have archives, or an institutional repository?
9. Are there open access initiatives? Survey the OA journals in which
your faculty/researchers are publishing.
10. Do other journals in which your researchers publish require data
sharing?
5. Key Roles for Librarians
• Teaching Data Information Literacy
• Data management plan consulting
• Building data management guides
• Informationists/Embedded librarians
• Assisting researchers with metadata and statistical
analysis tools
• Planning and managing data repositories
• Assisting researchers with publication and
preservation options
6. Resources from the NE e-Science
Program
E-Science Portal for New England Librarians
http://esciencelibrary.umassmed.edu/
7. Journal of eScience Librarianship
• Advance e-Science librarianship as a discipline
• Covers range of topics including RDM services,
data curation, embedded research librarians, data
sharing and reuse
• Dissemination of research and “e-Science in
Action”
http://escholarship.umassmed.edu/jeslib/
8. Annual events
• University of Massachusetts and New England
Area e-Science Symposium
• Science Boot Camp
• Professional Development Days
10. • Established in 1852, Tufts is a private university with campuses in
Boston, Medford/Somerville & Grafton, Mass., and Talloires, France
• Total students: 10,819; Undergraduates: 5,131; Graduate and
professional: 5,284; International: 1,246
• Total libraries: 6; Total volumes, all libraries: 1,236,421
• Tisch Library: 59 staff; 20 professional, 39 library assistants
12. Research Data Management Services Group
Goals:
– Provide data management plan support and
development
– Provide updated information on evolving Federal
open data requirements & guidelines
– Educate researchers (faculty, staff, students) in
research data management, open data & open access
– Collaborate, coordinate and consult with Arts,
Science & Engineering around University-wide data
management initiatives
– Concerns: how to bring data management services
& education to a diverse academic & research
community with decentralized libraries and services?
13. Strategic University Partnerships
– Vice-provost for Research
o Office of Proposal
Development
o Office of Research
Administration
o Office of Program
Development
– Lewis-Burke Associates, LLC
– Arts and Sciences Associate
Director for Research Affairs and
Grants Administrator
– School of Engineering Research
Administrator
– Tufts Digital Collections and
Archives (Tufts Institutional
Repository and Digital Library)
– Tufts Technology Services
o Research and GIS Technical
Services
o Educational and Scholarly
Technology Services
– Tufts University Scholarly
Communications Team
– University Library Council
– Hirsch Health Sciences Library
– Webster Veterinary Library
14. Strategic Initiatives
• National Science Foundation (NSF) Informational Trip (March
2014)
o Executive summary: OVPR, Tufts Libraries, TTS, and DCA have
opportunity to evolve and build university-wide data
management services, policies and procedures.
• E-Science Duraspace Institute (November 2013 - April 2014)
o Results: Tisch Library Data Management Services Strategic Agenda
• E-Science Portal for New England Librarians (2010 - )
• Science Boot Camp (2010 - )
• Scholarly Communications Team (2012 - )
• New England Collaborative Data Management Curriculum
(NECDMC; 2011 - )
• Research and Graduate Programs Council (September 2014
presentation)
15. Accomplishments, 2009 -
• Established Tisch Library’s Data Management Services Group: Data
Management/Data Sharing Plans consultations
• Education Services: Best Practices in Research Data Management
o New England Collaborative Data Management Curriculum
(NECDMC) (ongoing)
o Savvy Researcher Series (ongoing)
o Hirsh Health Sciences Library: Tufts Medical/Dental/Sackler
School/Friedman School
o Research Data Management Software Pilot Project (June 2013 -)
Collaboration with Program Development (OVPR) and inclusion
in Tufts Innovates! Grants
o Office of Proposal Development & Institutional Review Board
o Tufts Research Day on Data Science (May 2014)
16. Group’s Future Initiatives
General
– Continue building on the National Science Foundation (NSF) Informational Trip
recommended actions
– Build on the DuraSpace Institute takeaways and continue developing strategic
agenda for Data Management Services
– Update/redesign Data Management Research Guide
– Work with Tufts Technology Services and others to develop a ‘one services
portal’ surrounding data management services at Tufts
– Sustainability for Research Data Management Services Group
Data Management Plans
– DMP Tool, Version 2 – download, customize and link from web site
– Investigate link from within Research Administration database
Education
– Tufts Graduate Schools, Research labs, Centers/Institutes (especially new
interdisciplinary centers)
– Continue building partnership with the offices of OPD & Program
Development
– NSF Research Experiences for Undergraduate Students
– Tufts Technology Services & Research Data M anagement Software:
Development of training for Tufts faculty/researchers and students (merge
with NECDMC)
17. Consulting on Data Management
Plans
How do we work with our A & S and School of Engineering faculty?
• Grants administrators contact us with lists of faculty who are
preparing NSF/NIH and other organization grant proposals
• We use an email template to contact researchers
• We ask to work with researcher in person, email, sometimes both
• We will arrange a meeting with subject specialist and metadata
librarian (when necessary)
• Our DMP template is attached to email, will provide a directorate
specific template
• We ask the researcher to provide grant summary and/or prospectus
• Within the email we provide a ‘path’ or ‘outline’ for researcher on how
to proceed
19. Data Management Practices at Tufts
• Faculty:
– utilize ad hoc data management systems
– are reliant on their students and research associates to store,
manage and retrieve their group’s data
– leverage services offered by Tisch library staff to prepare data
management plans for grant submissions
– Finding the data as mandated by the government becomes
increasingly difficult as:
– more and more data are generated
– students/associates use different data storage methods
– students/associates leave the university
– the time between data acquisition and request increases
20. Project Charter / Goal
The goal of this project is to select, implement,
manage and support a University-wide research
data management service for the Tufts research
community.
21. Exploratory Phase: 2012-2013
• May 2012 – Nov 2013
• Participants
– Chemistry Department
– Digital Collections & Archives
– Tisch Library
– Tufts Technology Services
• Stages
– Assessed ELN/LIMS market and products
– Surveyed Tufts research community
– Outreach to other institutions
22. Survey Results
• Common storage schema
but wildly different
organizational
schema
• Many researchers would
need hours to days to
retrieve data
• Majority of responders
lose track of their data
before the end of the time
period required by NIH,
NSF, and OSTP
• The majority of
researchers still share files
via email.
• Useful features of a
prospective data
management system:
– Ability to search within saved
documents
– Sharing documents with
groups of users
– Re-analyzing (not only
viewing) data
– Web-based platform
– Login-based authentication
– Electronic Laboratory
Notebook (ELN)
– Integration with MS Office
– Minimal learning curve
23. RDMS Project 2014
• Jan 10, 2014 – Kickoff meeting
• Jan 15, 2014 – Mar 15, 2014:
Pilot planning w/ project
team and vendors
• Mar 15, 2014 – May 15, 2014:
Pilot
• May 15, 2014 – June 30, 2014 :
Study of pilot results and
purchase decision
• July 2014: Contract negotiation
• August 2014: Rollout planning
• September 15, 2014: Rollout
• 2 software platforms
– ELN
– ELN + DMS
• 20 faculty and 10
researchers across all
disciplines
– Training
– Support
– Feedback
• Reference checks
24. Pilot Results
• Both programs were generally well-received
• Researchers believed that the programs would
facilitate their research and data management
processes.
• Easy-to-use vs. complicated/powerful
• Next steps: Awaiting decision by Office of Vice-
Provost for Research/Tufts Technology Services;
planning for roll-out
24
25. Research Data Management
Services Group Role
• Developed an overview of best practices in research data
management and metadata for pilot participants
• Participated in software evaluations, pilot project training and
surveying participants; gathering feedback and helping with
final assessment of products
• Collaborating with Tufts Technology Services to develop
training for Tufts faculty/researchers and students (ELN
software + NECDMC)
27. Resources
• Antle, Patrick. “DMSPT Kickoff”. Powerpoint presentation.
January 10, 2014.
• Antle, Patrick. “RDMS Simmons LIS 532 G”. Powerpoint
presentation. September 17, 2014.
• Gold, A. 2007. “Cyberinfrastructure, Data and Libraries, Part
1.” D-Lib Magazine: (13) 9/10. Accessed 10/16/2012.
http://www.dlib.org/dlib/september07/gold/09gold-pt1.
• Hey, T. and Trefelen, A. 2003. The Data Deluge: an e-Science
Perspective. The UK e-Science Core Programme.
http://eprints.soton.ac.uk/257648/1/The_Data_Deluge.pdf
28. • Raboin, Regina. “Scientific Research Data Management, Tufts
Services”. Powerpoint Presentation. September 27, 2014.
• Shorish, Y. 2012. “Data Curation is for Everyone?! The Case for
Master’s and Baccalaureate Institutional Engagement with
Data Curation.” Libraries. Paper 1.
http://commons.lib.jmu.edu/letfspubs/1
Editor's Notes
Regina Raboin, MSLISScience Research & Instruction Librarian
Research Data Management Services Group CoordinatorTisch Library, Tufts University
Donna Kafel, RN, MLIS
E-Science Program Coordinator
Lamar Soutter Library
University of Massachusetts Medical School
Over the last several decades we’ve witnessed increasingly powerful, faster network- and computer-enabled work in science and we’re now witnessing the resultant virtual continually growing tsunami of data that this work has and continues to produces . In his 2003 paper, “The Data Deluge” an e-Science perspective, Tony Hey notes, “data generated from sensors, satellites, high throughput devices, scientific images, and so on will soon dwarf all of the scientific data collected in the whole history of scientific exploration.”
At the same time, data’s value as a key component of scholarly communication is increasingly recognized. The library profession is grappling with the new issues presented by data as part of the scholarly record. This illustration is exaggerated but it shows the enormity of the deluge and how seemingly silly it would be to summon a librarian to come save everyone from a data deluge disaster.
Some may wonder how did we get to this point where data has become such a hot commodity, and how did data management become a key issue in science librarianship? These events that are depicted in this diagram have spurred an awareness of the value of research data --making it accessible, meaningful, and resuseable and they have fostered librarian involvement . It starts with NIH’s 2003 requirement that all proposals requesting $500,000 or more in direct funding include an explanation of the type of data a project will produce and how the PI plans to share or not share data. The 2006 ARL report to the National Science Foundation “Long Term Stewardship of Data in Science and Engineering” indicated a need for multiple stakeholders , including librarians, to collaborate to develop systems and practices for managing, curating and providing access to research data. The consensus from the 2008 ARL forum “Reinventing Science Librarianship” advocated that the fundamental roles of librarians needed to expand to include developing skills needed to organizing and manipulating data and data sets. In 2010, the Panton Principles were written by members of the Open Knowledge Foundation Open Science Working group—to promote adoption of practices that would make data freely accessible and reusable. The policy that has so far made the most direct impact on scientific research that has made an impact on the research world and was the mandate implemented by NSF in 2011 for all research proposals to include a 2011 data management plan.
Assisting researchers with publication may include advising them on copyright issues related to their data, assisting with identifying data repository options—disciplinary or diverse systems like Figshare,
First bullet: pre-post award
These strategic initiatives are all about building collaboration & support for the library’s initiatives and ultimately, to benefit our researchers and students.
Supported by Tisch director and Vice-provost for Research; arranged by Lewis-Burke Associates, LLC
Meetings and Discussions
NSF Head, Policy Office, Division of Institution and Award Support
Seven Division Directors
Collaboration between Tisch Library and TTS
Tufts Team: Evan Simpson, Head, Research & Instruction; Lionel Zupan, Director, Research & GIS Services, TTS; Regina Raboin
Environmental survey of Tufts E-Science, data management policies
Final bullet: latest initiative; discovered this council while reading an email
NSF, NIH, NEH (Digital Humanities) and others
Hirsh Health Sciences Library now represented
Serves A, S & E; Tufts Medical, Dental & Friedman Schools; most recently Cummings
to develop a university-wide best practices in research data management curriculum (April 2014 - )
IRB collaboration in progress
Sustainability & Scalability
Re-structuring group for growth and adaptability
Re-structuring librarian position to coordinate these strategic initiatives full time
Educating subject/liaison librarians across Tufts campuses in best practices in research data management
Continue collaboration with Scholarly Communications Team
Different template: NSF Data Management Plans (DMPs) for Engineering
Data Management Service Group offers input on data products and metadata standards and formats, as well as options for data storage, archiving, and dissemination of research results
Always stresses: “we aren’t in the business of grant writing”
Treat support for DMPs as another service for research support
DMP consulting part of a larger package to partner with SOE faculty with phases of the research cycle
At SOE instruction workshops/events addresses data management as part of the research process and documentation
How are SOE faculty different?
Based on interviews
Federal guidelines
White House Office of Science and Technology Protocol (OSTP) (Feb 2013)
NIH (Oct 2012)
NSF (Jan 2011)
All data produced during a federally-funded grant must be made available
Original data
Metadata
Software or computer code
University is at risk! What can we do to lessen it?
Not just compliance, but good practice.
No one wants to lose data.
30 commercial and open-source software platforms were investigated
Features, strengths, and weaknesses
Electronic Lab Notebook (ELN)
A computer program designed to replace paper laboratory notebooks
Data Management System (DMS)
Software for collaborating on, gathering, sharing and using data
Laboratory Information Management System (LIMS)
A software-based system that manages aspects of laboratory informatics and offers support of laboratory operations, including workflow and data tracking, especially in regulated environments
Three types of platforms, from simple to complex
Persistent storage, easy organization, retrieval, and sharing
Also flexible enough for university-wide usage. LIMS “overkill”
Goals
Understand current data management practices throughout the university
Match common and specific needs with available technological solutions that provide the necessary tools and capabilities
In-person interviews
25 faculty across Medford, Boston, and Grafton
University-wide survey
197 respondents
Two ELNs are being considered: one web-based, the other client-based.