Results of the Stakeholder Alignment Survey conducted by PI Joel Cutcher-Gershenfeld, University of Illinois, Urbana Champaign, presented by Susan Winters, University of Maryland
EarthCube Stakeholder Alignment Survey Introduction to the Data by Joel Cutch...EarthCube
Introduction to the Stakeholder Alignment Survey being conducted for EarthCube by lead institution University of Illinois, Champaign Urbana as presented by PI Joel Cutcher-Gershenfeld
THIS IS THE BEST EDUCATION SYSTEM HAS BEEN DESIGNED AND VELOPED BY DR.SRI JEEVAN EMS TO EDUCATE NAOTECHNOLOGY FOR B.TECH/M.TECH/PHD STUDENTS ON THE FOLLOWING SCHEMS.
B.E. ( NANO SYSTEM)
M.TECH.( NANO ELECRONICS SYSTEM)
PHD( NANO TECHNOLOGY MANAGEMENT)
FOR THE LECTURE OF DR.SRI JEEVAN EMS, PROFESSOR,(UNIVERSAL ENCYLOPEDIA SYSTEM)
EMAIL:sunjeevan@outlook.com
cell:bsnl:09485164931.
Culture of Quality Can Accelerate Growth and Performance in the EnterpriseASQ
A culture of quality starts with a common language that an organization uses to talk about how it meets the needs of its customers and ensures its customers or clients are satisfied.
Like all cultures, a quality culture is built around shared values and is embodied within the organizations. Those values are illustrated through the stories an organization tells about quality and the actions it takes to ensure everyone knows the importance of quality, from the governance to the measurement to the training.
When these stories, actions and value are instilled through every level of an organization, a culture of quality is created.
"Culture of Quality: Accelerating Growth and Performance in the Enterprise" explores the key components of a successful culture of quality. This first-of-its-kind global study offers actionable insight into how a quality-driven culture can accelerate business performance.
Download the free report and learn more about the research here: www.cultureofquality.org.
Culture is an integral part of an organization and Quality is one of the key focus of current business environment.Thus creating a need of changing existing traditional culture in to a quality culture.
EarthCube Stakeholder Alignment Survey Introduction to the Data by Joel Cutch...EarthCube
Introduction to the Stakeholder Alignment Survey being conducted for EarthCube by lead institution University of Illinois, Champaign Urbana as presented by PI Joel Cutcher-Gershenfeld
THIS IS THE BEST EDUCATION SYSTEM HAS BEEN DESIGNED AND VELOPED BY DR.SRI JEEVAN EMS TO EDUCATE NAOTECHNOLOGY FOR B.TECH/M.TECH/PHD STUDENTS ON THE FOLLOWING SCHEMS.
B.E. ( NANO SYSTEM)
M.TECH.( NANO ELECRONICS SYSTEM)
PHD( NANO TECHNOLOGY MANAGEMENT)
FOR THE LECTURE OF DR.SRI JEEVAN EMS, PROFESSOR,(UNIVERSAL ENCYLOPEDIA SYSTEM)
EMAIL:sunjeevan@outlook.com
cell:bsnl:09485164931.
Culture of Quality Can Accelerate Growth and Performance in the EnterpriseASQ
A culture of quality starts with a common language that an organization uses to talk about how it meets the needs of its customers and ensures its customers or clients are satisfied.
Like all cultures, a quality culture is built around shared values and is embodied within the organizations. Those values are illustrated through the stories an organization tells about quality and the actions it takes to ensure everyone knows the importance of quality, from the governance to the measurement to the training.
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"Culture of Quality: Accelerating Growth and Performance in the Enterprise" explores the key components of a successful culture of quality. This first-of-its-kind global study offers actionable insight into how a quality-driven culture can accelerate business performance.
Download the free report and learn more about the research here: www.cultureofquality.org.
Culture is an integral part of an organization and Quality is one of the key focus of current business environment.Thus creating a need of changing existing traditional culture in to a quality culture.
Disciplinary and institutional perspectives on digital curationMichael Day
Slides from a presentation jointly given by Alexander Ball and Michael Day of UKOLN in a panel session on Scientific Data Curation at the DigCCurr 2009 Conference, Chapel Hill, NC, USA, 2 April 2009
Lee Allison, PI of the EarthCube Test Enterprise Governance Project, leads the EarthCube Townhall at ESIP Summer Meeting 2014.
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Email all questions to anna.katz@azgs.az.gov.
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Paul Morin (UMN): Polar Cyberinfrastructure
Don Middleton (UCAR): Atmospheric/Climate
Kerstin Lehnert (LDEO): Domain Repositories & Physical Samples
David Schindel (CBOL, GRBio): Biological Perspective & Collections
Hank Leoscher (NEON): Observation Networks
Daniel Fuka (Virginia Tech) and Ruth Duerr (NSIDC): Brokering
Ilya Zaslavsky (UCSD): Cross-Domain Interoperability
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On Tuesday 18 September 2007, Ben Shneiderman gave a talk at the Centre for HCI Design, City University London, on the topic of information visualisation for high-dimensional spaces. Over 100 people from industry and academia attended the talk.
http://hcid.soi.cty.ac.uk/
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Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
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Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
by David H. Guston
Professor of Political Science
Director, Center for Nanotechnology in Society at ASU Co-Director, Consortium for Science, Policy & Outcomes.
Slides for meeting in Fondazione Bassetti
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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.
Conceptual Architecture for USDA and NSF Terrestrial Observation Network Inte...Brian Wee
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Meeting the NSF DMP Requirement June 13, 2012IUPUI
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EarthCube Community Webinar held Tuesday, Dec. 9th at 11:00 PST/2:00 EST for a virtual kick-off of the new 'Demonstration Phase' of EarthCube, including statements from your Leadership Council members and an update from NSF Program Officer, Eva Zanzerkia.
Disciplinary and institutional perspectives on digital curationMichael Day
Slides from a presentation jointly given by Alexander Ball and Michael Day of UKOLN in a panel session on Scientific Data Curation at the DigCCurr 2009 Conference, Chapel Hill, NC, USA, 2 April 2009
Lee Allison, PI of the EarthCube Test Enterprise Governance Project, leads the EarthCube Townhall at ESIP Summer Meeting 2014.
This presentation covers a brief introduction to EarthCube, the EarthCube journey to the All-Hands Meeting, outcomes of the All-Hands Meeting, and ways to participate in the demonstration governance.
Email all questions to anna.katz@azgs.az.gov.
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This series of presentations was given at the EarthCube Data Facilities End-User Workshop held January 15-17, 2014 in Washington, DC. This workshop provided a forum to discuss the unique requirements and challenges associated with developing the communication, collaboration, interoperability, and governance structures that will be required to build EarthCube in conjunction with existing and emerging NSF/GEO facilities.
This panel and discussion, specifically, outlined and explained several current concepts in data sharing and interoperability, featuring presentations by:
Paul Morin (UMN): Polar Cyberinfrastructure
Don Middleton (UCAR): Atmospheric/Climate
Kerstin Lehnert (LDEO): Domain Repositories & Physical Samples
David Schindel (CBOL, GRBio): Biological Perspective & Collections
Hank Leoscher (NEON): Observation Networks
Daniel Fuka (Virginia Tech) and Ruth Duerr (NSIDC): Brokering
Ilya Zaslavsky (UCSD): Cross-Domain Interoperability
Australia's Environmental Predictive CapabilityTERN Australia
Federating world-leading research, data and technical capabilities to create Australia’s National Environmental Prediction System (NEPS).
Community consultation presentation.
3-12 February 2020
Dr Michelle Barker (Facilitator)
(Presentation v5)
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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.
Relationship-based knowledge mobilization: systems-based KMb and consideratio...KBHN KT
The field of Knowledge Translation (KT) needs to consider the importance of risk perception as a key barrier for uptake of research findings. This presentation outlines several domains for risk perception identified as a result of case study/grounded theory methodology research on the restart of two nuclear generating stations in Ontario, Canada. Generalizable results for the field of KT, KMb are presented.
On Tuesday 18 September 2007, Ben Shneiderman gave a talk at the Centre for HCI Design, City University London, on the topic of information visualisation for high-dimensional spaces. Over 100 people from industry and academia attended the talk.
http://hcid.soi.cty.ac.uk/
Opening/Framing Comments: John Behrens, Vice President, Center for Digital Data, Analytics, & Adaptive Learning Pearson
Discussion of how the field of educational measurement is changing; how long held assumptions may no longer be taken for granted and that new terminology and language are coming into the.
Panel 1: Beyond the Construct: New Forms of Measurement
This panel presents new views of what assessment can be and new species of big data that push our understanding for what can be used in evidentiary arguments.
Marcia Linn, Lydia Liu from UC Berkeley and ETS discuss continuous assessment of science and new kinds of constructs that relate to collaboration and student reasoning.
John Byrnes from SRI International discusses text and other semi-structured data sources and different methods of analysis.
Kristin Dicerbo from Pearson discusses hidden assessments and the different student interactions and events that can be used in inferential processes.
Panel 2: The Test is Just the Beginning: Assessments Meet Systems Context
This panel looks at how assessments are not the end game, but often the first step in larger big-data practices at districts/state/national levels.
Gerald Tindal from the University of Oregon discusses State data systems and special education, including curriculum-based measurement across geographic settings.
Jack Buckley Commissioner of the National Center for Educational Statistics discussing national datasets where tests and other data connect.
Lindsay Page, Will Marinell from the Strategic Data Project at Harvard discussing state and district datasets used for evaluating teachers, colleges of education, and student progress.
Panel 3: Connecting the Dots: Research Agendas to Integrate Different Worlds
This panel will look at how research organizations are viewing the connections between the perspectives presented in Panels 1 and 2; what is known, what is still yet to be discovered in order to achieve the promised of big connected data in education.
Andrea Conklin Bueschel Program Director at the Spencer Foundation
Ed Dieterle Senior Program Officer at the Bill and Melinda Gates Foundation
Edith Gummer Program Manager at National Science Foundation
by David H. Guston
Professor of Political Science
Director, Center for Nanotechnology in Society at ASU Co-Director, Consortium for Science, Policy & Outcomes.
Slides for meeting in Fondazione Bassetti
This is the presentation of the Juan Cruz-Benito’s PhD “On data-driven systems analyzing, supporting and enhancing users’ interaction and experience” that was defended on September 3rd, 2018 in the Faculty of Sciences at University of Salamanca Spain. This PhD was graded with the maximum qualification “Sobresaliente Cum Laude”.
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.
Conceptual Architecture for USDA and NSF Terrestrial Observation Network Inte...Brian Wee
In light of the challenges facing agriculture over the next few decades, USDA and NEON leaders have been exchanging information on strategies for leveraging existing investments. In late 2012, the USDA launched its Long-Term Agro-Ecosystem Research (LTAR) network with an initial configuration of ten sites, three of which are co-located with NEON. Discussions have focused on the establishment of partnerships and the sharing of techniques, protocols, best practices, and physical infrastructure. This poster outlines some of those ideas.
Meeting the NSF DMP Requirement June 13, 2012IUPUI
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EarthCube Stakeholder Alignment Survey - End-Users & Professional Societies Workshop
1. EarthCube Stakeholder
Alignment: Data and
Principles
Susan Winter,
University of Maryland
Joel Cutcher-Gershenfeld,
University of Illinois, Urbana-Champaign
Support from the National Science Foundation is deeply appreciated:
NSF-VOSS EAGER 0956472, “Stakeholder Alignment in Socio-Technical Systems,”
NSF OCI RAPID 1229928, “Stakeholder Alignment for EarthCube,”
NSF GEO-SciSIP-STS-OCI-INSPIRE 1249607, “Enabling Transformation in the Social
Sciences, Geosciences, and Cyberinfrastructure,”
NSF I-CORPS 1313562 “Stakeholder Alignment for Public-Private Partnerships”
Nick Berente, University of Georgia
Burcu Bolukbasi, UIUC
Nosh Contractor, Northwestern University
Leslie DeChurch, Georgia Tech University
Courtney Flint, Utah State University
Gabriel Gershenfeld, Cleveland Indians
Michael Haberman, UIUC
John L. King, University of Michigan
Eric Knight, University of Sydney
Barbara Lawrence, UCLA
Spenser Lewis, General Dynamics
Pablo Lopez, UIUC
Ethan Masella, Brandeis University
Charles Mcelroy, Case Western
Reserve University
Barbara Mittleman, Nodality, Inc.
Mark Nolan, UIUC
Melanie Radik, Brandeis University
Namchul Shin, Pace University
Ilya Zaslavsky, UCSD
2. Unprecedented Scale and Complexity of Problems
– Some from human numbers and resource exploitation
– Failure to solve them can lead to disasters
– Require long-term commitments from diverse sectors of
society and disciplines
• simple, unidimensional solutions unlikely;
– Solutions will be iterative
– Institutions can enable more impact and 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)
3. Institutions ≠ Systems
Sources: Carolos A. Osario, ESD Doctoral Seminar, 2004, and Joel Cutcher-Gershenfeld
US Passenger Air Transportation System
http://www.xprt.net/~rolfsky/internetSite/internet.html
US Internet Backbone
Natural Disasters
US Power Grid
4. Enabling Long-term, Productive Use of Natural Resources
• Neither the state nor the market is uniformly successful
• Communities have relied on institutions to govern some
resource systems
Eleanor Ostrom, Governing the Commons:
The Evolution of Institutions for Collective Action, p. 1
5. Institutional and Systems Requirements
Creating Value
Mitigating Harm
. . . expanding the “pie” and
enabling systems transformation
. . . anticipating and mitigating
externalities and catastrophic
systems failures
7. Defining stakeholder alignment . . .
“The extent to which interdependent stakeholders
orient and connect with one another
to advance their separate and shared interests.”
A simplified
conceptual
framework . . .
Culture
Behavior
Strategy Structure
8. Preliminary Findings on Formation
• Visibility of stakeholder interests accelerates
dialogue and alignment
• Shared vision of success enables faster/more
robust forms of alignment (Strategy)
• Internal alignment within stakeholder groups
enables lateral alignment across stakeholders
(Structure)
• Alignment initially based on trust; sustaining
requires new structural arrangements (forums,
roles, incentives, etc.) (Culture/Structure)
9. Preliminary Findings on Operations. . .
• Requires leadership based on influence, more than
authority (Behavior)
• “Over specified” or “under specified” forums are
ineffective – minimum critical specifications
(Structure)
• Primary lever for change is “middle-out” (protocols
and standards) not top-down or bottom-up
(Strategy/Structure)
• Failure to deliver on individual/collective interests
erodes alignment and systems success (Overall)
10. Minimum critical specification:
No more and no less!
Council of Data Facilities
Charter
I. Preamble
II. Vision
III. Mission and goals
IV. Definition
V. Membership
VI. Roles and responsibilities
VII. Operations
VIII.Coordination with
EarthCube
IX. Signatures
Assembly of EarthCube
Funded Projects Guidelines
I. Introduction and overview
II. Guiding principles
III. Operations
IV. Roles and responsibilities
V. Assembly coordinating
committee
VI. Coordination with
EarthCube
VII. Signatures
11. The vision. . .
“Over the next decade, the geosciences
community commits to developing a
framework to understand and predict
responses of the Earth as a system—from
the space-atmosphere boundary to the
core, including the influences of humans
and ecosystems.”
– GEO Vision Report of NSF Geoscience
Directorate Advisory Committee, 2009
12. Potential failure modes. . .
• Unrealistic or misaligned expectations
• “Build it and they will come”
• Not valuing current cyber/geo efforts and
initiatives
• Not advancing the frontier – just automating
current state
• Not engaging the 200,000+ geoscience and cyber
stakeholders not yet involved in EarthCube
• Not anticipating the needs of the next generation
(students, post docs)
• Unknown unknowns (transformational changes in
technology, policy, etc.)
13. Stakeholder alignment data by End User Workshop
(n=1,544)
EarthCube Website (n=164)
Data Centers (n=578)
Early Career (n=37) Oct. 17-18, 2012
Structure and Tectonics (n=24) Nov. 19-20, 2012
EarthScope (n=22) Nov. 29-30, 2012
Experimental Stratigraphy (n=21) Dec. 11-12, 2012
Atmospheric Modeling / Data Assimilation and
Ensemble Prediction (n=29) Dec. 19, 2012
OGC (n=14) Jan. 13, 2013
Critical Zone (n=39) Jan. 21-23, 2013
Hydrology / Envisioning a Digital Crust (n=23) Jan. 29-31, 2013
Paleogeoscience (n=40) Feb. 3-5, 2013
Education & Workforce Training (n=33) Mar. 3-5, 2013
Petrology & Geochemistry (n=59) Mar. 6-7, 2013
Sedimentary Geology (n=50) Mar. 25-27, 2013
Community Geodynamic Modeling (n=45) Apr. 22-24, 2013
Integrating Inland Waters, Geochemistry, Biogeochem
and Fluvial Sedimentology Communities (n=46) Apr. 24-26, 2013
Deep Sea Floor Processes and Dynamics (n=29) June 5-6, 2013
Real-Time Data (n=25) June 17-18, 2013
Ocean ‘Omics (n=42) Aug. 21-23, 2013
Coral Reef Systems (n=44) Sept. 18-19/Oct. 23-24, 2013
Geochronology (n=66) Oct. 1-3, 2013
Ocean Ecosystem Dynamics (n=36) Oct. 7-8, 2013
Clouds and Aerosols (n=39) Oct. 21-22, 2013
Rock Deformation and Mineral Physics (n=35) Nov. 12-14, 2013
14. Stakeholder Alignment data by Fields and
disciplines (n=1,544)
Primary Secondary
Atmospheric n=175 (11.3%) n=74 (4.8%)
Biologist/Ecosystems n=127 (8.2%) n=101 (6.5%)
Climate Scientists n=78 (5.1%) n=86 (5.6%)
Critical zone n=31 (2%) n=44 (2.8%)
Geographers n=32 (2.1%) n=34 (2.2%)
Geologists n=358 (23.2%) n=112 (7.3%)
Geophysicists n=148 (9.6%) n=73 (4.7%)
Hydrologists n=82 (5.3%) n=61 (4.0%)
Oceanographers n=171 (11.3%) n=94 (6.1%)
Computer/Cyber n=82 (5.3%) n=91 (5.9%)
Data managers n=53 (3.4%) n=86 (5.6%)
Software engineers n=24 (1.6%) n=50 (3.2%)
Note: additional categories included in the survey, but these are the focus here.
15. Sample specific areas of expertise
• Air Sea Interaction
• Atmospheric Radiation
• Basalt geochemistry
• Biodiversity Information
Networks
• Carbonate Stratigraphy
• Chemical Oceanography
• Coastal Geomorphology
• Computational Geodynamics
• Cryosphere-Climate Interaction
• Disaster Assessment
• Ensemble data assimilation
• Geochronology
• Geoinformatics
• Geomicrobiology
• Glaciology
• Heliophysics
• Isotope Geochemistry
• “It’s complicated”
• Magnetospheric Physics
• Mesoscale Meteorology
• Multibeam Bathymetric Data
• Nearshore Coastal Modeling
• Paleoceanography
• Paleomagnetism
• Permafrost Geophysics
• Planetology
• Riverine carbon and nutrient
biogeochemistry
• Satellite gravity and altimetry
data processing
• Tectonophysics
• Thermospheric Physics
• Watershed Management
16. Accessing data, models, and software within
fields/disciplines: Importance and ease
How IMPORTANT is it for you to find, access, and/or integrate multiple datasets, models, and/or software
(e.g. visualization tools, middleware, etc.) in your field or discipline? (v58)
How EASY is it for you to find, access, and/or integrate multiple datasets, models, and/or software (e.g.
visualization tools, middleware, etc.) in your field or discipline? (v59)
untitled - ec- 08- indomain.pdf
17. Importance and ease within fields/disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
IMPORTANT
data, tools,
models in your
field
EASE data,
tools, models
in your field
18. Accessing data, models, and software across
fields/disciplines: Importance and ease
How IMPORTANT is it for you to find, access, and/or integrate multiple datasets, models, and/or software
(e.g. visualization tools, middleware, etc.) that span different fields or disciplines? (v60)
How EASY is it for you to find, access, and/or integrate multiple datasets, models, and/or software (e.g.
visualization tools, middleware, etc.) that span different fields or disciplines? (v61)
untitled - ec- 09- spandomain.pdf
19. Importance and ease across fields/disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
IMPORTANT
data, tools,
models across
fields
EASE data,
tools, models,
across fields
20. Cooperation/sharing among geoscientists
Cooperation/sharing among cyber-developers
There is currently a high degree of sharing of data, models, and software among geoscientists. (v69)
There is currently a high degree of sharing of software, middleware and hardware among those developing
and supporting cyberinfrastructure for the geosciences. (v70)
3/ 4/untitled - ec- 12- current- coop.pdf
21. Cooperation/sharing among geoscientists
and among cyber-developers by fields and disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
cooperation among geoscientists
Cooperation among cyber-developers
22. Collaboration between geo and cyber
Sufficient end user training
There is currently sufficient communication and collaboration between geoscientists and those who
develop cyberinfrastructure tools and approaches to advance the geosciences. (v72)
There is currently sufficient geoscience end-user knowledge and training so they can effectively use the
present suite of cyberinfrastructure tools and train their students/colleagues in its use. (v73)
untitled - ec- 13- current- collob.pdf
23. Collaboration between geo and cyber and sufficient
end user training by fields and disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Collaboration between geo and cyber
Sufficient end-user training
24. End user views on sharing data, tools, models,
and software
Overall, I believe that sharing data, tools, models, and software that I generated will advance my career in
the next 3-5 years? (v82)
I trust that the data, tools, models, and software shared by other colleagues will be well-documented and
reliable. (v83)
untitled - ec- 15- adv- career.pdf
25. End user views on sharing data, tools, models,
and software by fields and disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Sharing will advance my career
I turst data will be well-documented and reliable
26. Support for sharing from employer and colleagues
My employer/organization will most likely value and reward any efforts I make in the shaping and
development of EarthCube (v120).
Any contributions I might make to the shaping and development of EarthCube will likely be recognized and
valued by colleagues in my field/discipline (v122).
untitled - ec- 27- efforts.pdf
27. Support for sharing from employer and
colleagues by fields and disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Employer will value EC efforts
Colleagues will value EC efforts
28. End user views on commercial products and
applications
The EarthCube incorporate commercial products or applications to reduce cost or speed development.
(v105)
The EarthCube process should generate tools and approaches that benefit commercial products or
applications. (v106)
untitled - ec- 22- commercial.pdf
29. End user views on commercial products and
applications by fields and disciplines
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Incorporate commercial
Benefit commercial
30. Motivation for engagement with EarthCube
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Advancing
my research
Advancing
my teaching
Networking
opportunities
Developing
successful
grant
proposals
Leading to
new scientific
advances
Making
geoscience
data /
findings
available to
the general
public
Informing
resource
managers
and policy
makers
Serving my
field /
profession
31. Support for EarthCube specifying guidelines
Support for guidelines using international standards
EC should specify guidelines
m(s) = 0.79 (0.19)[n=353, 18]
EC should use formal int. standards
m(s) = 0.84 (0.18)[n=342, 29]
The EarthCube initiative should specify guidelines so there is more interoperability and uniformity in
discovering, accessing, sharing, and disseminating geoscience data. (v99)
Where such standards exist, EarthCube should use formal, internationally approved, geoscience-wide data
access/sharing standards and protocols (e.g. ISO, OGC). (v100)
32. Support for collaboration among US govt. orgs.
Support for collaboration between US and Intl. orgs.
EarthCube should play an active role in enabling collaboration and coordination of geoscience cyber-
infrastructure activities among US government organizations (NSF, NOAA, NASA, Army Corp, etc.). (v116)
EarthCube should play an active role in enabling collaboration and coordination between US and
international geoscience cyberinfrastructure initiatives and organizations. (v117)
untitled - ec- 26- enable.pdf
33. Elements of Success (from Early Career workshop)
Access/Uploading:
• Google earth style interface
• Accessible data submission interface
• Standardized meta data (data type, context, provenance, etc.) for field
scientists (with & w/o internet access)
• Data security
• Public accessibility; empower non-specialists
Utilization/Operations:
• Community mechanisms to build tools
• Large data manipulation, visualization, and animation
• Searchable access by space, time, and context
• Voice to pull up data and analyze
• Open source workflow management for data processing and user-
contributed algorithms (facilitate reproducibility)
• Cross-system comparisons; ontology crosswalks for vocabs in diff
disciplines
• Easy integration of analytic tools (R, Matlab, etc.)
• NSF support for data management
34. Elements of Success (from Early Career workshop)
Output/Impact:
• Mechanisms for credit for work done (data, models, software, etc.);
ease of citation; quantify impact
• Promote new connections between data producers and consumers
• Interactive publications from text to data
• Recommendations system (like Amazon) for data, literature, etc.;
Flickr for data (collaborative tagging)
• Educational tutorials for key geoscience topics (plate tectonics, ice
ages, population history, etc.)
• Gaming scenarios for planet management
• EarthCube app store; ecosystem of apps
35. Most important challenges of the
21st Century, as identified by NAE
• Make solar energy
economical
• Provide energy from fusion
• Develop carbon
sequestration methods
• Manage the nitrogen cycle
• Provide access to clean water
• Restore and improve urban
infrastructure
• Advance health informatics
• Engineer better medicines
• Reverse-engineer the
brain
• Prevent nuclear terror
• Secure cyberspace
• Enhance virtual reality
• Advance personalized
learning
• Engineer the tools of
scientific discovery
Source: http://www.engineeringchallenges.org/
37. The complete survey (1544 respondents) is available for
exploratory analysis via a new online interface:
The URL is http://maxim.ucsd.edu/ecsurvey1544
This version requires Silverlight plugin. As before, it will take a few
minutes to load it the first time (because of the size of the survey
data file).
There are also two additional versions
http://maxim.ucsd.edu/openlinkpivot/survey1544.html
http://maxim.ucsd.edu/lobsterpot/0.9.32/survey1544.html
These do not require a plugin, but these are experimental, and less
robust than the first one.