The iSamples (Internet of Samples in the Earth Sciences) Research Coordination Network is part of EarthCube and focuses on the integration of physical samples and collections into digital data infrastructure in the Earth sciences. This presentation summarizes the activities of the iSamples RCN and presents results from a major community survey about sharing and management of physical samples that was conducted as part of the RCN.
Slides from presentation at CHI2015:
Paper Title: Designing for Citizen Data Analysis: A Cross-Sectional Case Study of a Multi-Domain Citizen Science Platform
Abstract:
Designing an effective and sustainable citizen science (CS) project requires consideration of a great number of factors. This makes the overall process unpredictable, even when a sound, user-centred design approach is followed by an experienced team of UX designers. Moreover, when such systems are deployed, the complexity of the resulting interactions challenges any attempt to generalisation from retrospective analysis. In this paper, we present a case study of the largest single platform of citizen driven data analysis projects to date, the Zooniverse. By eliciting, through structured reflection, experiences of core members of its design team, our grounded analysis yielded four sets of themes, focusing on Task Specificity, Community Development, Task Design and Public Relations and Engagement. For each, we propose a set of design claims (DCs), drawing comparisons to the literature on crowdsourcing and online communities to contextualise our findings.
Dissertation proposal defense for a comparative case study of virtual citizen science projects, focusing on the concepts of virtuality, technology, organizing, participation, and outcomes.
Successfully defended with no revisions on 5 May, 2010.
Slides from presentation at CHI2015:
Paper Title: Designing for Citizen Data Analysis: A Cross-Sectional Case Study of a Multi-Domain Citizen Science Platform
Abstract:
Designing an effective and sustainable citizen science (CS) project requires consideration of a great number of factors. This makes the overall process unpredictable, even when a sound, user-centred design approach is followed by an experienced team of UX designers. Moreover, when such systems are deployed, the complexity of the resulting interactions challenges any attempt to generalisation from retrospective analysis. In this paper, we present a case study of the largest single platform of citizen driven data analysis projects to date, the Zooniverse. By eliciting, through structured reflection, experiences of core members of its design team, our grounded analysis yielded four sets of themes, focusing on Task Specificity, Community Development, Task Design and Public Relations and Engagement. For each, we propose a set of design claims (DCs), drawing comparisons to the literature on crowdsourcing and online communities to contextualise our findings.
Dissertation proposal defense for a comparative case study of virtual citizen science projects, focusing on the concepts of virtuality, technology, organizing, participation, and outcomes.
Successfully defended with no revisions on 5 May, 2010.
Disciplinary and institutional perspectives on digital curationMichael Day
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California Ocean Science Trust " Building a Sustainable Knowledge Base for ...Tom Moritz
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Sediment Experimentalist Network (SEN): Sharing and reusing methods and data ...hsuleslie
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Supplementary presentation slides from a lecture on digital preservation given at the University of the West of England (UWE) as part of the MSc in Library and Library Management, University of the West of England, Frenchay Campus, Bristol, March 10, 2010
Australia's Environmental Predictive CapabilityTERN Australia
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A VIVO VIEW OF CANCER RESEARCH: Dream, Vision and RealityPaul Courtney
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Trust and Accountability: experiences from the FAIRDOM Commons Initiative.Carole Goble
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The FAIRDOM Initiative (FAIR Data Models Operations, http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards and sensitivity to asset sharing and credit anxiety. Our aim is a FAIR Research Commons that blends together the doing of research with the communication of research. The Platform has been installed by over 30 labs/projects and our public, centrally hosted FAIRDOMHub [2] supports the outcomes of 90+ projects. We are proud to support projects in Norway’s Digital Life programme.
2018 is our 10th anniversary. Over the past decade we learned a lot about trust between researchers, between researchers and platform developers and curators and between both these groups and funders. We have experienced the Tragedy of the Commons but also seen shifts in attitudes.
In this talk we will use our experiences in FAIRDOM to explore the political, economic, social and technical, social practicalities of Trust.
[1] Wilkinson et al (2016) The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18
[2] Wolstencroft, et al (2016) FAIRDOMHub: a repository and collaboration environment for sharing systems biology research Nucleic Acids Research, 45(D1): D404-D407. DOI: 10.1093/nar/gkw1032
The Knowledge Exchange is a partnership of six national
organisations within Europe. As part of its ambition to make
Open Scholarship work, the Knowledge Exchange has developed
a Framework for Open Scholarship. This sets out the different
phases in the research life cycle against a variety of perspectives
that present barriers/challenges for Science/Scholarship to
be open, at the same time acknowledging that there are many
levels of stakeholders, reaching from individual researchers to
institutions to national governments. In this talk the presenters
will explain the partnership and share their recent report and
current work around Open Scholarship.
Chris Keene, Jisc
Bas Cordewener, Jisc/Knowledge Exchange
Notes from attending FORCE2019 conference in Edinburgh (October 15-18), covering a range of topics around Research Communications, e-Scholarship, Open Science and Open Access. Links on last slide for full conference programme and presented materials available online.
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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.
3. iSamplES Objective
advance the use of innovative cyberinfrastructure to connect
physical samples and sample collections across the Earth
Sciences with digital data infrastructures as par of EarthCube
to improve the discovery, access, sharing, analysis, and curation of physical
samples and the data generated by their study as needed by the science
community
iSamplES: The Internet of Samples in the Earth Sciences
3
The Internet of Samples
in the Earth Sciences
4. iSamplES Goals
develop a shared vision for an Internet of Samples in
the Earth Sciences.
converge on and eventually build consensus for best
practices and standards for sample registration,
identification, citation, and metadata that can be
adopted across the diverse stakeholder community.
enhance broad awareness of and access to existing
resources that will advance preservation, access, and
management of samples
iSamplES: The Internet of Samples in the Earth Sciences
4
5. iSamplES Stakeholders
iSamplES: The Internet of Samples in the Earth Sciences
5
Domain Scientists
working with samples in the
field, lab, or in data systems
Large-scale science programs,
observatories, and sampling
campaigns (IODP, ICDP, CZO, etc.)
Data Facilities
handling sample-based data
Computer and CI
Scientists
Curators
- core repositories
- museums
- sample repositories &
collections
- academic departments
Publishers and
Professional Societies
EarthCube Projects
Agencies
Software Engineers
6. iSamplES Activities
iSamplES: The Internet of Samples in the Earth Sciences
6
Stakeholder Alignment
(lead: Joel Cutcher-
Gershenfeld)
• questionnaires & surveys
• workshops & outreach events
• ongoing working groups
isamplES Knowledge
Hub, semantic WiKi
(lead: Yolanda Gil)
CINERGI Catalog of Earth
Science Collections (lead:
Ilya Zaslavsky)
Transformation of Sample and
Data Practices by Early Career
Scientists (lead: Benjamin
Hallett)
7. Transformation of Sample and Data Practices by
Early Career Scientists
7
iSamples Early Career Workshop
• lunch meeting at AGU FM 2014
• 60 participants (students, postdocs, junior faculty)
• recruit ECS for development of teaching modules
• 5 participants at iSamples Kickoff workshop
10. iSamples Kick-off Workshop
UT Austin: Jan 28-30, 2015
53 participants
domain sciences (igneous, metam.,
& soil geochem; geochron;
tectonics; paleoclimate;
paleontology; geophysics)
computer science
library science
data facilities
sample facilities (core and sample
repositories, museums/Smithsonian,
NASA astromaterials)
publishing
petroleum industry
1/3 early career scientists!!
iSamplES: The Internet of Samples in the Earth Sciences
10
16. Other Perspectives
the scientists
senior level: Steve Goldstein (LDEO)
early career: Michael Tuite (JPL), Jon Stelling (LeHigh), Amanda
Waite (U Florida), Emily Hernandez Goldstein (UT Austin)
the curators: Ann Molineux (UT Austin), Betty Adrian
(USGS)
related efforts
scientific collections: Eileen Graham (SciColl, Smithsonian
Institution)
bioinformatics: Ramona Walls (iPLant Collaborative)
digital archiving: Chris Jordan (Digital Preservation Network, UT
Austin)
16
18. Workshop Discussions
Identified commonalities
“People are all facing similar problems.”
“We are all in the same boat together.”
Revealed consensus
Focus on minimum critical solutions
“simple is actually better than a Cadillac of software”
“Encouraged that the sample information that is needed can be
relatively small”
“Stop the bleeding first” (problem of legacy on back burner)
Need for culture change
“old mentality that this is my rock”
need for education so that scientists document samples better
18
19. Today’s most troubling and daunting problems have
common features: some of them arise from human
numbers and resource exploitation; they require
long-term commitments from separate sectors of
society and diverse disciplines to solve; simple,
unidimensional solutions are unlikely; and failure to
solve them can lead to disasters.
In some ways, the scales and complexities of our
current and future problems are unprecedented,
and it is likely that solutions will have to be iterative .
. .
Institutions can enable the ideas and energies of
individuals to have more impact and to sustain
efforts in ways that individuals cannot.
From “Science to Sustain Society,” by Ralph J. Cicerone, President,
National Academy of Sciences, 149th Annual Meeting of the Academy (2012)
21. iSamples Governance
Steering committee provides guidance to the PI and co-
PI, who then serves as the leadership for operations.
SC is responsible for defining the vision and statement of
principles, with an invitation for individuals and organizations to
serve as signatories.
Working groups focus on identified tasks.
Specify goal, scope, deliverables, and periodic two-way input to
steering committee (with chairs or co-chairs added to steering
committee).
Potential to be allied with or serving as working groups in ESIP,
RDA or others
Plan additional workshop for early 2016 and assess need
for more structure at that time
21
22. Working group topics
Metadata standards
Metadata standards for physical samples within and across disciplines / Sample-based
interoperability standards: unique identifiers, controlled vocabularies, RDF schemas, etc.
Physical infrastructure
Physical infrastructure for sample curation (preservation & access) and standards (attributes) for
repositories and collections
Workflow support
Workflow support (software) for investigators (field, lab, publication, grant proposals) /
Architecture of shared cyberinfrastructure for collection management and shared
interoperability tools
“Use Cases”
“Use cases” on the reuse of physical samples and policies for sample sharing / End user
perspectives / Sample collection scenarios / Work flow documentation / Research process
modeling / Scientific requirements
Digital collections
Digitization and cataloguing of collections, including image handling / Data and sample rescue
Dynamic citation
Dynamic citation of samples: Guidance to publishers and authors to link samples, data, and
publications
Communication/education
Communication, education, training, mentorship, ambassadors, engagement
Consolidate
23. Working Groups
WG1: Identifiers & Metadata
WG2: User stories & scientific requirements
incl. policies for sample sharing
WG3: Communication, Education, Training
WG4: Architecture & Workflows
WG5: Physical Infrastructure
incl. digitization of collections, sample rescue
23
24. WG1: Identifiers & Metadata
Problem: Lack of standards for sample discovery & identification across
domains
Goal: Define minimum metadata profiles required to facilitate
functional/meaningful discovery and interoperability across domains
Try not to make metadata burdensome, but promote use and still make it rich
Examine scope & integration of unique identifier types (IGSN, LSID, BCID, RRID, etc.)
Build consensus for leading practices to make recommendations to community
Co-chairs: David Arctur (UT Austin), Reyna Jenkyns (Ocean Networks Canada)
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25. WG1: Next Steps
compile use cases for
metadata needs (work with
WG2, WG4)
gather & evaluate existing
resources (metadata,
vocabularies, UIDs) – don’t
reinvent the wheel
session at ESIP Summer Meeting
identify key contacts
EarthCube TAC
CODATA Task Group, ESIP, RDA IG,
etc.
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26. WG2: User Stories & Science Requirements
Problem:
We do not have a full picture of how
people interact with samples.
We don’t have good life cycle based
policies, don’t know when/where
different actors are needed (curators,
investigators, etc.)
Goals:
Collect user stories
Articulate different life cycle practices
for different users
Identify curatorial points of intervention,
develop policies/recommendations
Co-chairs: Andrea Thomer (UIUC), Sarah
Ramdeen (UNC Chapel Hill)
26
27. WG2: Next Steps
generate flowcharts for research
processes
establish protocol for further
interviews with people from
different roles and domains
encourage RCN participants to
post institutional policies
use EarthCube End-user
workshops
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28. WG3: Communication, Training, Education
Problem: Insufficient
appreciation of benefits of digital
sample management
Goal: Develop communication
plan to promulgate best practices
specific for a variety of audiences
(students/ECS, late career scientists)
identify ambassadors
prepare training modules
Co-chairs: Ben Hallett (U Wisconsin
Oshkosh), Ashlee Dere (U Nebraska
Omaha)
28
29. WG3: Next Steps
work toward communication
plan: create 3 slides about
iSamples as talking points
build skeleton of list of
registries, listservs, etc.
reach out to EarthCube
Engagement Team
work closely with other WGs to
contribute materials
29
30. WG4: Architecture & Workflows
(incl. citation of samples)
Problem: Barriers to adoption of leading
practices such as IGSN assignment,
standard sample documentation, sample
citation in the literature
Goals: Identify barriers and develop
solutions with maximum efficiency, e.g.
for integrating IGSNs into workflows
from collection to publishing
gather data from people in the field and who work
with collections
design of app to support metadata capture in the
field (with EC3?)
recommend protocols for citation of samples to
NSF
Co-Chairs: Unmil Karadkar (iSchool, UT Austin),
Emily Hernandez Goldstein (Jackson School, UT
Austin)
30
31. WG4: Next Steps
Evaluate IGSN registration process and tools and identify steps
to improve usability
integrate SESAR user feedback
talk with the use case group about what feedback they get
31
Propose solutions
Software applications
(design & test applications
for digital data entry in the
field) (iSchool class project)
Incentives
Requirement of agencies
DMPs to have IGSNs - reach out
to make reviewers require it
Work with EarthCube RCNs EC3, C4P
32. WG5: Physical Infrastructure, Digitizing,
Cataloguing, & Sample Rescue
Problem: Loss of physical samples
and the information
(data/metadata) about them
Goals:
Produce a vision for national archive
system for physical samples
Produce proposal for funding streams
for a national archive system and
systematic digitization of samples (like
iDigBio?)
Co-chairs: Leslie Hale (Smithsonian
Institution), Ramona Walls (iPlant)
32
33. WG5: Next Steps
use the DESC & iSamples survey
to develop a set of criteria by which samples should be
preserved;
to develop a set of criteria for which collections should
be digitized first;
to develop leading practices for digital archiving of
sample data/metadata.
represent WG at Marine Curators meeting in
April at College Station, TX
33
34. iSamples: Next Steps
Set up workspaces, forums, and listservs for WGs
Complete development of iSamples semantic wiki as
prototype for community feedback
iSamples session at EarthCube All-Hands Meeting
isamples session at ESIP Summer Meeting
Ensure that WGs move forward
Development of educational modules
34
35. Participate!
Join the iSamples group
go to http://earthcube.org/group/isamples
Join a Working Group
send email to mcarter@ldeo.columbia.edu
To get alerts about upcoming webinar
Join the iSamples group or check the EarthCube calendar
For any questions
contact mcarter@ldeo.columbia.edu or
lehnert@ldeo.columbia.edu
35
Editor's Notes
uncover and understand the interests that are guiding your venture
enable iSamplES to be responsive to its stakeholders’ shared and separate interests