All of society’s grand challenges -- be it addressing rapid climate change, curing cancer and other disease, providing food and water for more than seven billion people, understanding the origins of the universe or the mind -- all of them require diverse and sometimes very large data to to be shared and integrated across cultures, scales, and technologies. This requires a new form and new conception of infrastructure. The Research Data Alliance (RDA) is creating and implementing this new data infrastructure. It is building the connections that make data work across social and technical barriers. RDA launched in March 2013 as a international alliance of researchers, data scientists, and organizations to build these connections and infrastructure to accelerate data-driven innovation. RDA facilitates research data sharing, use, re-use, discoverability, and standards harmonization through the development and adoption of technologies, policy, practice, standards, and other deliverables. We do this through focussed Working Groups, exploratory Interest Groups, and a broad, committed membership of individuals and organizations dedicated to improving data exchange. I also discuss some early ideas on building community and connecting like minded organizations at different scales.

1. Unless otherwise noted, the slides in this presentation are licensed by Mark A. Parsons under a Creative Commons Attribution-Share Alike 3.0 License
The Research Data Alliance:
Creating the culture and technology for an international data infrastructure
Mark A. Parsons
Rensselaer Polytechnic Institute
Boulder Earth and Space Science Informatics Group
21 August 2013

2. All of society’s grand challenges require diverse
(often large) data to to be shared and integrated
across cultures, scales, and technologies.

3. Research Data Alliance
Vision
Researchers around the world sharing and using research data
without barriers.
Purpose
to accelerate international
data-driven innovation and discovery
by facilitating research data
sharing and exchange,
use and re-use,
standards harmonization, and
discoverability.
through the development and adoption of infrastructure, policy,
practice, standards, and other deliverables.

4. We need to start thinking about software in a
way more like how we think about building
bridges, dams, and sewers
– Dan Bricklin, Software That Lasts 200 Years
http://www.bricklin.com/200yearsoftware.htm

9. Dynamics of Infrastructure
Edwards, et al. 2007 Understanding Infrastructure: Dynamics,
Tensions, and Design.
• Infrastructures become “ubiquitous, accessible, reliable, and transparent” as
they mature.
• Staged evolution
• “system-building, characterized by the deliberate and successful design of
technology-based services.”
• “technology transfer across domains and locations results in variations on
the original design, as well as the emergence of competing systems.”
• Finally, “a process of consolidation characterized by gateways that allow
dissimilar systems to be linked into networks.”

10. Ecology of Infrastructure
Figure derived from F. Millerand
based on S. L. Star & K. Ruhleder
(1996)

11. When is infrastructure?

12. When is infrastructure?
Who is infrastructure?

13. Deliverables that make data work
“Create - Adopt - Use”
• Adopted code, policy, infrastructure, standards, or best practices that enable
data sharing
• “Harvestable” efforts for which 12-18 months of work can eliminate a
roadblock
• Efforts that have substantive applicability to groups
within the data community, but may not apply to all
• Efforts for which working scientists and researchers
can start today
RDA Principles
Openness
Consensus
Balance
Harmonization
Community Driven
Non-profit

14. RDA Organizational Framework

15. Positive deviance says that if you want to create change, you must
scale it down to the lowest level of granularity and look for people
within the social system who are already manifesting the desired
future state. Take only the arrows that are already pointing toward
the way you want to go, and ignore the others. Identify and
differentiate those people who are headed in the right direction. Give
them visibility and resources. Bring them together. Aggregate them.
Barbara Waugh
Leadership Model: Positive Deviance
Slide courtesy Ted Habermann, NOAA

16. RDA Members are
from 51 Countries
15 July 2013
Academia
58%
Private
8%
Public Admin.
11%
Other
23%

17. • Data Type Registries
• PID Information Types
• Standardization of data categories and codes, working specifically with the
ISO 639 (human languages)
• Data Foundation and Terminology
• Practical Policy (pending)
• Community Capability Model (in review)
• Data Citation: Making Data Citable (in review)
• Metadata Standards (in review)
Working Groups

18. • Metadata
• Preservation e-Infrastructure
• The Engagement Group
• Data in Context
• Publishing Data
• UPC Code for Data
• The Long Tail of Research Data
• Agricultural Data Interoperability
• Certification of Digital Repositories
• Structural Biology
• Big Data Analytics
• Defining Urban Data Exchange
• Marine Data Harmonization
• Digital Practices in History and
Ethnography
• Toxicogenomics Interoperability
• Brokering
• Legal Interoperability
Interest Groups

19. Going Glocal
Beginning of the inchoate part of
the talk

20. Themes from B. Caron on Community
(with a nod to J. Bacon & G. Graen)
• Network Effect (esp. networks of subnetworks)
• Sub-communities enhance belonging
• Connections breed connections
• Requisite Variety
• Ashby’s law: “variety absorbs variety”
• Surface-level diversity (race, age, gender) vs deep-level (values, conceptual
metaphors, personality).
• Adjacent Possible—the importance of local
• Need for a common cause, a “collaboration-driven ethos”,
an “axiom of unity,” a dream.

21. Themes from A. Tsing on Collaboration
Friction—An ethnography of global connection
• “Actually existing universalisms are
hybrid, transient, and involved in
constant reformulation through
dialogue.” They work out through
friction.
• “There is no reason to think
collaborators have common goals.”
• Unity and diversity cover each
other up. Need to remember the
local.

22. Themes from Parsons on Relationships
(I’m an introvert)
• The central challenge is diversity. We address it through (deep-
level) diversity, more specifically through friction. Friction is
manifested in relationships.
• Fostering relationships is central to community and data
science.
• they build social capital—success through giving
• they uncover tacit knowledge
• they inform methods

23. Methods
• User-driven design is not just end user. Engage providers and funders too.
• Case studies not just use cases.
• Ethnography—study relationships because data are often at the center of that
interaction—a boundary object.
• Agile is not just for software.
• Individuals and interactions over processes and tools
• Working software (working volunteers) over comprehensive documentation
• Customer collaboration (member collaboration) over contract negotiation
• Responding to change over following a plan.

24. Relationships grow through personal, unscripted
interaction around common interest—shared
stories.
Figure courtesy webbirdmedia.com

25. Get involved!
• Join RDA as an individual member supporting our principles at
http://rd-alliance.org
• Join as an Organizational Member (nominal fee) or an Organizational
Affiliate (jointly sponsored efforts)
• Initiate or join an Interest Group
• Propose or join a Working Group
• Attend the RDA Plenaries
• Nominate yourself or someone else for the Technical Advisory Board (TAB)
Coming together is a beginning;
keeping together is progress;
working together is success.
—Henry Ford

26. Next Plenary:
16-18 September 2013
National Academy of Sciences
Washington DC
Hashtag: #RDAPlenary
RDA Plenary 3 in
Dublin Ireland,
March 26-28 2014,
hosted by Australia
and Ireland

27. Questions and comments to:
enquiries@rd-alliance.org or parsom3@rpi.edu
Twitter: @resdatall