This document provides an update on the Research Data Alliance (RDA) from June 2015. It summarizes that the RDA community focuses on building infrastructure to reduce barriers to data sharing and accelerate the development of global data infrastructure. It notes that the RDA has grown significantly since its launch in 2013 and now has over 2,900 members from 102 countries. It also lists several outputs and deliverables produced by RDA working groups to enable improved data sharing, including standards for data citation, metadata and data type registries.
Research engagement in EUDAT| www.eudat.eu | EUDAT
| www.eudat.eu | EUDAT’s vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, that combine community-specific data repositories with the permanence and persistence of some of Europe’s largest scientific data centres. EUDAT services are community driven solutions. This presentation describes the different ways EUDAT engages with the research communities
Closing address by John Wood on the role of the Research Data Alliance given at the Now and Future of Data Publishing Symposium, 22 May 2013, Oxford, UK
Sarah Jones - National approaches to data managementdri_ireland
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
Hilary Hanahoe - The Research Data Alliance in a nutshelldri_ireland
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
RDA Presentation by Hilary Hanahoe at Open Science 2020 event, Pisa 8th April - Sharing data across technologies, disciplines and countries, what is it, how does it work, how and why you should get involved
LIBER Webinar: Are the FAIR Data Principles really fair?LIBER Europe
The FAIR Data Principles are a hot topic in research data managment. Their adoption within the H2020 funding programme means researchers now have to pay much more attention to how their share, publish and archive their data.
In this light, how can libraries help their research communities implement the FAIR principles? And write better data management plans?
This questions were addressed in a LIBER webinar containing some guidance and reflections on the principles themselves. Presented by Alastair Dunning, Head Research Data Services at the TU Delft (hosts of the 4TU.Centre for Research Data), it is based on a study of 37 data repositories (from subject specific repositories, to generic data archives, to national infrastructures), seeing how far they comply with each of the individual facets of the Data principles.
An overview on FAIR Data and FAIR Data stewardship, and the roadmap for FAIR Data solutions coordinated by the Dutch Techcentre for Life Sciences. This presentation was given at the Netherlands eScience Center's "Essential skills in data-intensive research" course week.
FAIR data: what it means, how we achieve it, and the role of RDASarah Jones
Presentation on FAIR data, the FAIR Data Action Plan developed by the European Commission Expert Group and the role of the Research Data Alliance on implementing FAIR. The presentation was given at the RDAFinland workshop held on 6th June - https://www.csc.fi/web/training/-/rda_and_fair_supporting_finnish_researchers
Find out how to partner with us for the RDA 6th Plenary in Paris, 23- 25 September 2015! Join us for an international event gathering industry and academic experts, world leaders involved in the data ecosystem !
Research engagement in EUDAT| www.eudat.eu | EUDAT
| www.eudat.eu | EUDAT’s vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, that combine community-specific data repositories with the permanence and persistence of some of Europe’s largest scientific data centres. EUDAT services are community driven solutions. This presentation describes the different ways EUDAT engages with the research communities
Closing address by John Wood on the role of the Research Data Alliance given at the Now and Future of Data Publishing Symposium, 22 May 2013, Oxford, UK
Sarah Jones - National approaches to data managementdri_ireland
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
Hilary Hanahoe - The Research Data Alliance in a nutshelldri_ireland
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
RDA Presentation by Hilary Hanahoe at Open Science 2020 event, Pisa 8th April - Sharing data across technologies, disciplines and countries, what is it, how does it work, how and why you should get involved
LIBER Webinar: Are the FAIR Data Principles really fair?LIBER Europe
The FAIR Data Principles are a hot topic in research data managment. Their adoption within the H2020 funding programme means researchers now have to pay much more attention to how their share, publish and archive their data.
In this light, how can libraries help their research communities implement the FAIR principles? And write better data management plans?
This questions were addressed in a LIBER webinar containing some guidance and reflections on the principles themselves. Presented by Alastair Dunning, Head Research Data Services at the TU Delft (hosts of the 4TU.Centre for Research Data), it is based on a study of 37 data repositories (from subject specific repositories, to generic data archives, to national infrastructures), seeing how far they comply with each of the individual facets of the Data principles.
An overview on FAIR Data and FAIR Data stewardship, and the roadmap for FAIR Data solutions coordinated by the Dutch Techcentre for Life Sciences. This presentation was given at the Netherlands eScience Center's "Essential skills in data-intensive research" course week.
FAIR data: what it means, how we achieve it, and the role of RDASarah Jones
Presentation on FAIR data, the FAIR Data Action Plan developed by the European Commission Expert Group and the role of the Research Data Alliance on implementing FAIR. The presentation was given at the RDAFinland workshop held on 6th June - https://www.csc.fi/web/training/-/rda_and_fair_supporting_finnish_researchers
Find out how to partner with us for the RDA 6th Plenary in Paris, 23- 25 September 2015! Join us for an international event gathering industry and academic experts, world leaders involved in the data ecosystem !
In recent years governments and research institutions have emphasized the need for open data as a fundamental component of open science. But we need much more than the data themselves for them to be reusable and useful. We need descriptive and machine-readable metadata, of course, but we also need the software and the algorithms necessary to fully understand the data. We need the standards and protocols that allow us to easily read and analyze the data with the tools of our choice. We need to be able to trust the source and derivation of the data. In short, we need an interoperable data infrastructure, but it must be a flexible infrastructure able to work across myriad cultures, scales, and technologies. This talk will present a concept of infrastructure as a body of human, organisational, and machine relationships built around data. It will illustrate how a new organization, the Research Data Alliance, is working to build those relationships to enable functional data sharing and reuse.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Adjusting primitives for graph : SHORT REPORT / NOTES
Research Data Alliance Member Statistics June 2015
1. Update on the Research Data Alliance
June 2015
Updated: 8th
June 2015
2. 2
RDA community focuses on
building social, organizational
and technical infrastructure to
reduce barriers to data sharing
and exchange
accelerate the development of
coordinated global data
infrastructure
CREATE ADOPT USE
RDA Working Group Infrastructure
Deliverables are:
Focused pieces of adopted code, policy,
infrastructure, standards, or best practices that
enable data to be shared and exchanged
“Harvestable” efforts for which 12-18 months of
work can eliminate a roadblock for a substantial
community
Efforts that have substantive applicability to
“chunks” of the data community, but may not apply to
everyone
Efforts forwhich working scientists and
researchers can start today while more long-term or
far-reaching solutions are appropriately discussed in
other venues
Research Data Alliance created to Accelerate Development of
Research Data Sharing Infrastructure Worldwide
Plenary 2
Washington, DC
3. 3
Precipitous Growth
RDA Launch /First
Plenary
March2013
RDA Second
Plenary
September2014
RDA Third
Plenary
March2014
RDA Fourth
Plenary
September2014
RDA Fifth
Plenary
March2015
Amsterdam,
Netherlands
Washington,
DC, USA
Dublin, Ireland
Gothenburg,
Sweden
240 participants
First Working Groups
and Interest Groups
380 participants from22
countries
First “neutral space”
community meeting (Data
Citation Summit)
First Organizational Partner
Meet-up
First BOFs
497 Participants from32
countries
First Organizational
Assembly
6 co-located events
14 BOF,
12 Working Groups, 22
Interest Groups
San Diego,
CA, USA
550 Participants
from40 countries
1st
RDA Deliverables
presented
Organizational
Assembly and first
OAB/Council
meeting
10 co-located events
11 BOF,
14 Working Groups,
36 Interest Groups
383 Participants from30
countries
2nd
RDA Deliverables
presented
Organizational Assembly /
Council meetings
1st
Adoption Day & Large
scale data projects meeting
10 BOF, 10 Working Groups,
20 Interest Groups;
10 joint Sessions;
4 thematic Plenary Sessions
4. 4
The Research Data Alliance Community Today
Total RDA Community Members: 2936
from 102 countries
5. 5
RDA Organizational Structure Complete
RDA Funders Forum
Stakeholder Group
RDA Council
Responsible for overarching mission, vision, impact of RDA
Technical Advisory
Board
Responsible for Technical
roadmap and interactions
Secretary-General and
Secretariat
Responsible for
administration and
operations
Organizational Advisory
Board and
Organizational
Assembly
Responsible for organizational
adoption and strategic advice
Working Groups 16 (June 2015)
Self formed & responsible for impactful, outcome-oriented efforts
Interest Groups 42 (June 2015)
Self formed & responsible for defining and refining common issues
RDAMembership
8. 8
Data Foundation & Terminology: a model for data in the
registered domain.
PID Information Types: a common protocol for providers
and users of persistent ID services worldwide.
Data Type Registries: allowing humans and machines to act
on unknown, but registered, data types.
Practical Policy: defining best practices of how to deal with
data automatically and in a documented way with computer
actionable policy.
https://rd-alliance.org/rda-outputs.html
Outputs
9. 9
Metadata standards directory: Community curated
standards catalogue for metadata interoperability
Data Citation: defining mechanisms to reliably cite dynamic
data
Data Description Registry Interoperability solutions
enabling cross platform discovery based on existing open
protocols and standards
Wheat Data Interoperability impacting the discoverability,
reusability and interoperability of wheat data by building a
common framework for describing, representing linking and
publishing wheat data
https://rd-alliance.org/rda-outputs.html
Outputs
10. 10
Organisations & initiatives seen as pioneers in
realizing full value from research data
exercise considerable influence in the
development of standards for data exchange
and will provide valuable insights to the entire
range of RDA activity
regularly briefed on developments in data
interoperability with equally regular opportunity
to provide feedbackon activity and suggestions
on next steps
Organisation & Affiliate Members
14. 14
RDA Plenary 3 (Dublin)
March 26-28, 2014
Theme : “Playing YOUR part”
500 attendees from 35 countries
Hosted by Ireland and Australia
Co-located events:
EUDAT Training
MUMIA Meeting on Verifiable Results in Multi-
lingual/Multi-faceted Search: Challenges in
Sharing Data, Tools and Results Workshop
SIM4RDM: Building Collaborations to address
research data management workshop
APARSEN-EUDAT-SCIDIP-ES Workshop on
Data Preservation and Re-use
Focus on emerging professionals :
RDA/EU sponsored 22 European Early Career
Researchers and Scientists
RDA/US sponsored 8 Student Interns
15. 15
September 22-24, 2014
Theme : “Reaping the Fruits”
550 attendees from 40+ countries
Co-hosted by Netherlands
Co-located conferences:
EUDAT Conference
Crowd Computing 2014
Data Seal of Approval Conference 2014, etc.
1st RDA deliverables presented:
Data Type Registries
PID Information Types
Practical Policy
Data Foundation and Terminology
Focus on emerging professionals :
RDA/EU sponsored 14 European Early
Career Researchers and Scientists
RDA/US sponsored 8 Student Interns and
5 Early Career and Student Fellows
RDA Plenary 4 (Amsterdam)
16. 16
March 8-11, 2015
Theme : “Adopt-a-Deliverable”
383 attendees from 30 countries
Supported by the San Diego Super
Computing Center
1st
Adoption Day & Large scale data
projects meeting
2nd
Set of RDA deliverables presented:
Data Citation: Making Data Citable
Data Description Registry Interoperability
Metadata Standards Directory
Wheat Data Interoperability
Focus on emerging professionals :
RDA/EU sponsored 5 European Early Career
Researchers and Scientists
RDA/US sponsored 5 Fellowship winners
RDA Plenary 5 (San Diego, CA)
17. 17
RDA Plenary 6 (Paris)
When?
23-25 September 2015
Where?
CNAM, Paris, France
What?
Enterprise Engagement
with a focus on Research
Data for Climate Change
https://rd-alliance.org/plenary-meetings/rda-sixth-plenary-meeting.html
19. 19
Next Steps forRDA
Continuing pipeline of infrastructure deliverables
adopted and used to accelerate data sharing
Increasing coordination of infrastructure
Increasing cross-boundary collaborations
between domains, sectors, organizations
International and regional programs focusing on
workforce, outreach, expansion of infrastructure
impact
New partners in the Organizational Assembly
Focused strategy to support development of
industry infrastructure for data sharing
More Infrastructure
Partnership with
Industry
Synergistic Programs
Effective Community