The Research Data Alliance (RDA) is an international organization with over 4,900 members from 118 countries that works to reduce barriers to data sharing and exchange. RDA develops infrastructure and holds working groups to develop recommendations and standards to facilitate open data sharing across technologies and disciplines. Key activities of RDA include developing recommendations for data citation, metadata standards, and repository platforms. RDA outputs include specifications, code, policies and practices to enable greater data interoperability, discoverability, and reuse globally.
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.
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.
An introduction to the FAIR principles and a discussion of key issues that must be addressed to ensure data is findable, accessible, interoperable and re-usable. The session explored the role of the CDISC and DDI standards for addressing these issues.
Presented by Gareth Knight at the ADMIT Network conference, organised by the Association for Data Management in the Tropics, in Antwerp, Belgium on December 1st 2015.
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.
Toward Semantic Representation of Science in Electronic Laboratory Notebooks ...Stuart Chalk
An electronic laboratory Notebook (ELN) can be characterized as a system that allows scientists to capture the data and resources used in performing scientific experiments. This allows users to easily organize and find their data however, little information about the scientific process is recorded.
In this paper we highlight the current status of progress toward semantic representation of science in ELNs.
An introduction to the FAIR principles and a discussion of key issues that must be addressed to ensure data is findable, accessible, interoperable and re-usable. The session explored the role of the CDISC and DDI standards for addressing these issues.
Presented by Gareth Knight at the ADMIT Network conference, organised by the Association for Data Management in the Tropics, in Antwerp, Belgium on December 1st 2015.
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.
Toward Semantic Representation of Science in Electronic Laboratory Notebooks ...Stuart Chalk
An electronic laboratory Notebook (ELN) can be characterized as a system that allows scientists to capture the data and resources used in performing scientific experiments. This allows users to easily organize and find their data however, little information about the scientific process is recorded.
In this paper we highlight the current status of progress toward semantic representation of science in ELNs.
The Open Research Agenda (Milton Keynes)Robert Farrow
Slides presented at the CALRG Annual Conference 2016
(http://cloudworks.ac.uk/cloudscape/view/2975). The Open Research Agenda is an international consultation exercise on research priorities in open education.
Polar research is inherently interdisciplinary and is becoming more so. Correspondingly, polar data managers have been working to meet very diverse communities and needs, especially after the progress of the International Polar Year 2007-8 (IPY). But is it enough? Despite their best efforts, the polar data and research communities can be rather insular. The unique challenges of polar research and data management may sometimes blind us to relevant developments in other parts of the world. At the same time, global initiatives and research in the lower latitudes often underplay, or even ignore, data needs and solutions in the polar regions. This conference emphasizes the need to extend polar issues more globally, yet the polar voice is still not loud enough in global conversations about data infrastructure.
Infrastructure, by its nature, must work across all scales. It requires a “glocal” perspective that simultaneously embraces both universalizing and particularizing tendencies. In this presentation I will discuss how there needs to be a constant interplay between local implementation and global design of data infrastructure. I will describe where the polar regions have had success in this area and where key challenges remain. I will describe a path forward for the polar data community to be better represented on the global stage through initiatives like the Research Data Alliance while also amplifying their effectiveness at the regional and local level. A goal is to improve the global understanding of polar issues while also improving the practice of polar data practitioners.
"Infrastructure, relationships, trust, and RDA" presentation given by Mark Parsons, RDA Secretary General at the eInfrastructures & RDA for Data Intensive Science Workshop - held prior to the RDA 6th Plenary, Paris, 22 September 2015.
Infrastructure is often thought of as a complex physical construct usually designed to transport information or things (e.g. electricity, water, cars, money, sound, data…). The Research Data Alliance (RDA) takes a more holistic view and considers infrastructure as a complex body of relationships between people, machines, and organisations.
This paper will describe how this more ecological perspective leads RDA to define and govern an agile virtual organization. We seek to harness the power of the volunteer, through an open problem solving approach that focusses on the problems of our individual members and their organisations. We focus on implementing solutions that make data sharing work better without defining a priori what is necessary. We do not judge the fitness of a solution, per se, but instead assess how broadly the solution is adopted, recognizing that adoption is often the social challenge of technical problem.
We seek to encourage a bottoms up approach with light guidance on principles from the top. The goal is to develop community solutions that solve real problems today yet are adaptive to changing technologies and needs.
Slides presented at Open Education 2016. The Open Research Agenda is an international consultation exercise on research priorities in open education which combines online surveys and focus group interactions. This presentation summarises thematic analysis of the data set and indicates future directions for research in the field of open education.
Libraries Enabling Open Science: LIBER Strategy & AdvocacyLIBER Europe
Presentation by Susan Reilly at the LAI/CILIP Ireland join annual conference 2016: https://libraryassociation.ie/events/laicilip-ireland-annual-joint-conference-2016
EUDAT Webinar "Organise, retrieve and aggregate data using annotations with B...EUDAT
| www.eudat.eu | Annotate your research data with B2NOTE:
A note in the margins of a book or a scientific paper, a comment on a manuscript: we are all using annotations to add information to existing physical documents. To offer a similar experience with digital content within the EUDAT Collaborative Data Infrastructure (CDI), we developed a service that allows associating additional information to a file, in a computer-readable format, without changing the file or the data record itself. These digital annotations can thus be searched to organize, retrieve and aggregate files, datasets and documents.
Although B2NOTE is a standalone service, it has been designed to be integrated with the existing EUDAT services. In the first pilot version, B2NOTE allows to annotate files located in B2SHARE. The service is called as a “widget” within the B2SHARE User Interface. B2NOTE allows you to easily and intuitively create three types of annotations: a semantic tag coming from identified ontology repositories (only Bioportal at the moment but we are working toward integrating more vocabularies), a free-text keyword that can be used when you do not find a semantic term in particular and a free-text comment.
This presentation uses a long-term case study to explore the socio-scientific aspects influencing what data products are created and made available for use. We examine two major satellite remote-sensing product collections from the National Snow and Ice Data Center—one on sea ice extent and another on Greenland ice sheet melt. We examine how the products and their curation have evolved over time in response to environmental events and increasing scientific and public demand over several decades. The products have evolved in conjunction with the needs of a changing and expanding designated user community. These changes in the user community were driven by increased interest in the Arctic partly because of the rapid change in the Arctic as characterized in these data, but also because of the increasing awareness (and controversy) around climate change and its impact.
We find that a data product development cycle supported by a data product team with multiple perspectives is key to mobilizing scientific knowledge to multiple stakeholders. Furthermore, the expertise and approaches to making data open and truly useful must continually adapt to new perceptions, needs, and events. Effective data access is an ongoing process, not a one-time event.
References
Baker K S; Duerr, R E; and Parsons, M A 2016 Scientific knowledge mobilization: Co-evolution of data products and designated communities. International Journal of Digital Curation 10 (2): 110-135. http://dx.doi.org/doi:10.2218/ijdc.v10i2.346
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.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
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.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
1. RDA in a nutshell
February 2017
WWW.RD-ALLIANCE.ORG - @RESDATALL
CC BY-SA 4.0
2. Vision
Researchers and innovators openly
share data across technologies,
disciplines, and countries to address
the grand challenges of society.
Mission
RDA builds the social and technical
bridges that enable open sharing of
data.
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
3. What is RDA?
RDA is an international member based organization focused on the
development of infrastructure and community activities that reduce
barriers to data sharing and exchange, and the acceleration of data
driven innovation worldwide.
With more than 4,900 members globally representing 118 countries,
RDA includes researchers, scientists and data science professionals
working in multiple disciplines, domains and thematic fields and from
different types of organisations across the globe.
RDA is building the social and technical bridges that enable open sharing of
data to achieve its vision of researchers and innovators openly sharing data
across technologies, disciplines, and countries to address the grand challenges
of society.
rd-alliance.org/about-rda
WWW.RD-ALLIANCE.ORG
@RESDATALL
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4. What does RDA do?
Members come together through self-formed, volunteer, focussed Working
Groups, exploratory Interest Groups to exchange knowledge, share
discoveries, discuss barriers and potential solutions, explore and define
policies and test as well as harmonise standards to enhance and facilitate
global data sharing & re-use.
RDA members collaborate together across the globe to tackle numerous
infrastructure & data sharing challenges related to:
Reproducibility
Data preservation
Best practices for domain
repositories
Legal interoperability
Data citation
Data type registries
Metadata
and so many more!
rd-alliance.org/about-rda
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5. Who Can Join RDA?
Any individual or organization, regardless of profession or discipline,
with an interest in reducing the barriers to data sharing and re-use and
who agrees to RDA’s guiding principles of:
◦ Openness
◦ Consensus
◦ Balance
◦ Harmonization
◦ Community-driven
◦ Non-profit and technology-neutral
Individual Membership is free @
https://www.rd-alliance.org/user/register
rd-alliance.org/get-involved.html
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@RESDATALL
CC BY-SA 4.0
6. Why Join RDA as an Individual
Member?
Individual Member Benefits
◦ Contribute to acceleration of data infrastructure development
◦ Work and share experiences with collaborators throughout the
world
◦ Access to extraordinary network of colleagues with various levels
of experience, perspectives and practices
◦ Gain greater expertise in data science regardless of whether one is
a student, early or seasoned career professional
◦ Enhance the quality and effectiveness of personal work and
activities
◦ Improve one’s competitive advantage professionally and
positioning oneself for leadership within the broader research
community
rd-alliance.org/get-involved/individual-membership.html
Individual RDA Members 4908
WWW.RD-ALLIANCE.ORG
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9. Why Join RDA as an
Organisational Member?
Organisational Member Benefits
◦ Provide an organizational perspective on the work of RDA and ability to
influence RDA’s direction
◦ Assist in implementation & adoption of RDA Recommendations &
Outputs
◦ Participate in all RDA Organizational Forums
◦ Receive regular updates on the work of the RDA
◦ Attend Organizational Assembly meetings and vote on proposed policies
for consideration by the RDA Council and for members of the
Organizational Advisory Board
◦ Provide advice to RDA Council through the Organizational Advisory Board
◦ Be recognized on the RDA Website and at RDA Meetings as a supporter of
data interoperability
rd-alliance.org/get-involved/organisational-membership
46 Organisational & 6 Affiliate Members
WWW.RD-ALLIANCE.ORG
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10. Organisational & Affiliate Members
rd-alliance.org/get-involved/organisational-membership
CC BY-SA 4.0
WWW.RD-ALLIANCE.ORG
@RESDATALL
43 Organisational
Members
8 Affiliate
Members
11. Domain Science - focused
Agrisemantics WG
BioSharing Registry WG
Fisheries Data Interoperability WG
On-Farm Data Sharing (OFDS) WG
Rice Data Interoperability WG
Wheat Data Interoperability WG
Agriculture Data IG (IGAD)
Biodiversity Data Integration IG
Chemistry Research Data IG
Digital Practices in History and Ethnography IG
Geospatial IG
Global Water Information IG
Linguistics Data Interest Group
Health Data IG
Mapping the Landscape IG
Marine Data Harmonization IG
Quality of Urban Life IG
RDA/CODATA Materials Data, Infrastructure & Interoperability IG
Research data needs of the Photon and Neutron Science
community IG
Small Unmanned Aircraft Systems’ Data IG
Structural Biology IG
Weather, Climate and air quality IG
RDA Interest (IG) & Working Groups (WG) by
Focus (1)
rd-alliance.org/groups
Community Needs - focused
Data Science and data-related education and training
certification and accreditation schemes WG
RDA/CODATA Summer Schools in Data Science and Cloud
Computing in the Developing World WG
Teaching TDM on Education and Skill Development WG
Archives & Records Professionals for Research Data IG
Data for Development IG
Development of Cloud Computing Capacity and Education in
Developing World Research IG
Education and Training on handling of research data IG
Ethics and Social Aspects of Data IG
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
Total 85 groups:
35 Working Groups & 50 Interest Groups
12. Reference and Sharing - focused
Data Citation WG
Data Description Registry Interoperability WG
Data Security and Trust WG
Empirical Humanities Metadata WG
RDA / WDS Publishing Data Bibliometrics WG
Research Data Collections WG
QoS-DataLC Definitions WG
International Materials Resource Registries WG
National Data Services IG
RDA/CODATA Legal Interoperability IG
Reproducibility IG
Data Discovery Paradigms IG
Repository Core Description WG
Research Data Repository Interoperability WG
Partnership Groups
RDA / TDWG Metadata Standards for attribution of
physical and digital collections stewardship WG
RDA/NISO Privacy Implications of Research Data Sets IG
RDA/WDS Scholarly Link Exchange Working Group
Repository Audit and Certification DSA–WDS Partnership
WG
RDA/WDS Publishing Data IG
ELIXIR Bridging Force IG
rd-alliance.org/groups
RDA Interest (IG) & Working Groups (WG) by
Focus (2)
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
Total 85 groups:
35 Working Groups & 50 Interest Groups
13. Data Stewardship and Services – focused
Brokering Framework WG
Brokering Governance WG
WDS/RDA Assessment of Data Fitness for Use WG
RDA / WDS Publishing Data Services WG
RDA / WDS Publishing Data Workflows WG
Active Data Management Plans IG
Data in Context IG
Data Rescue IG
Data Versioning IG
Domain Repositories IG
Libraries for Research Data IG
Long tail of research data IG
Preservation e-Infrastructure IG
Preservation Tools, Techniques, and Policies IG
RDA/WDS Certification of Digital Repositories IG
RDA/WDS Publishing Data Cost Recovery for Data Centres IG
Repository Platforms for Research Data IG
Research Data Provenance IG
Virtual Research Environments IG
Base Infrastructure – focused
Array Database Assessment WG
Data Foundation and Terminology WG
Data Type Registries WG
Metadata Standards Catalog WG
Metadata Standards Directory WG
PID Information Types WG
PID Kernel Information WG
Practical Policy WG
Data Fabric IG
Data Foundations and Terminology IG
Big Data IG
Brokering IG
Federated Identity Management IG
Metadata IG
PID IG
Vocabulary Services IG
rd-alliance.org/groups
RDA Interest (IG) & Working Groups (WG) by
Focus (3)
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@RESDATALL
CC BY-SA 4.0
Total 85 groups:
35 Working Groups & 50 Interest Groups
14. RDA Recommendations that
make data work
rd-alliance.org/recommendations-outputs
Adopted code, policy, specifications, standards, or 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 that can start today
WWW.RD-ALLIANCE.ORG
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“Create - Adopt - Use”
17 flagship recommendations & outputs with over
75 cases of adoption in different domains, organisations and countries
15. THE RDA OUTCOMES LEGEND
Recommendations: are the flagship outputs of RDA. They are
RDA’s equivalent of the “specifications” or “standards” that
other organisations create and endorse. The process for
creating and endorsing these is already defined.
Supporting Outputs: are the outputs of RDA WGs and IGs that
are fruit of RDA work, but are not necessarily adoptable
bridges. “Upon request”, these sort of outputs go through a
community comment period and if no major objections or gaps
are identified they get the RDA Brand.
Other Outputs: include workshop reports, published articles,
survey results, etc. Anything a WG or IG wants to register and
report. Upon request, these are published and discoverable on
the RDA website but have no level of endorsement.
RDA Recommendations & Outputs
rd-alliance.org/recommendations-and-outputs/all-recommendations-
and-outputs
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16. 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.
Metadata standards directory: Community curated
standards catalogue for metadata interoperability
RDA Recommendations & Outputs
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
17. 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
Brokering Governance WG: Sustainable Business Models for
Brokering Middleware to support Research Interoperability
RDA/CODATA Summer Schools in Data Science and Cloud
Computing in the Developing World WG: A framework to run a
series of Summer Schools in Data Science and data sharing in low
and middle income countries (LMICs)
RDA Recommendations & Outputs
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
18. Repository Audit and Certification DSA–WDS: A convergent DSA-WDS
certification standard to help eliminate duplication of effort, increase
certification procedure coherence and compatibility thus benefitting
researchers, data managers, librarians and scientific communities.
RDA/WDS Publishing Data Bibliometrics: improved research data metrics and
corresponding services, with the final goal of increasing the overall availability
and quality of citations and research data itself.
RDA/WDS Publishing Data Workflows: enhance the possibilities for greater
discoverability and a more efficient and reliable reuse of research data
benefitting other stakeholders like publishers, libraries and data centres.
RDA/WDS Publishing Data Services: A universal interlinking service between
data and the scientific literature. The Scholix initiative a high level
interoperability framework for exchanging information about the links
between scholarly literature and data. It aims to build an open information
ecosystem to understand systematically what data underpins literature and
what literature references data.
RDA Recommendations & Outputs
rd-alliance.org/recommendations-and-outputs/all-recommendations-
and-outputs
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
19. 23 Things: Libraries For Research Data An overview of practical, free,
online resources and tools that users can immediately take advantage
of to incorporate research data management into the practice of
librarianship.
RDA Recommendations & Outputs
rd-alliance.org/recommendations-and-outputs/all-recommendations-
and-outputs
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
Legal Interoperability of Research Data Principles and Implementation
Guidelines: a set of principles and practical implementation guidelines
offered as high-level guidance to all members of the research
community —the funders, managers of data centers, librarians,
archivists, publishers, policymakers, university administrators, individual
researchers, and their legal counsel.
Matrix of use cases and functional requirements for research data
repository platform Based on use cases, the matrix describes forty-
four functional requirements identified for research data repository
platforms and provides a score identifying relative importance.
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
20. Adoption & Implementation
“Solving the problem must include adopters in the process, to ensure
that real problems are addressed. Open problem solving is the key.”
RDA Recommendations and Outputs take the form of technical
specifications, code, policies or practices, harmonized standards or
reference models. In the widest sense these aim for:
Greater data sharing, exchange, interoperability, usability and re-usability;
Greater discoverability of research data sets;
Better management, stewardship, and preservation of research data;
New data standards or harmonization of existing standards.
RDA Adoption Stories - Tell us yours!
75 Adoption Cases
https://www.rd-alliance.org/recommendations-
outputs/adoption-recommendations
Find out how you can become an Adopter
https://www.rd-alliance.org/recommendations-and-outcomes/become-rda-adopter
Addressing data challenges
https://www.rd-alliance.org/recommendations-and-
outputs/all-recommendations-and-outputs
rd-alliance.org/recommendations-and-outputs/all-
recommendations-and-outputs
WWW.RD-ALLIANCE.ORG
@RESDATALL CC BY-SA 4.0
21. Call for Supporting and Other
RDA Outputs
https://rd-alliance.org/call-supporting-and-other-rda-outputs
If your group has produced something that you
would like to share with the broader community,
please send it to enquiries@rd-alliance.org and
indicate whether you would like it to be considered
as a ‘Supporting’ or ‘Other’ output.
rd-alliance.org/call-supporting-and-other-rda-outputs
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22. What are Plenary Meetings?
Organised around the world every 6 months
exciting & productive events bringing together a
unique community of data science professionals, from
multiple disciplines and domains;
help move the community forward in creating
tangible deliverables that improve data sharing across
disciplines, technologies, and countries;
heart of the plenaries are working meetings of RDA
Working & Interest groups and new potential groups
through Birds of a Feather meetings
presentation of new Outputs and Adoption cases
CC BY-SA 4.0
WWW.RD-ALLIANCE.ORG
@RESDATALLrd-alliance.org/plenaries
23. RDA Plenary Meetings: benefits of attending
Exchange knowledge, share discoveries, discuss
barriers and potential solutions
Expand your network and meet new
committed and passionate data science
professionals, working in multiple disciplines
Contribute to acceleration of data
infrastructure development
Learn about new trends, strategies, research
developments, directions and policies
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
rd-alliance.org/plenaries
24. RDA deliverables presented:
RDA/CODATA Summer Schools in Data Science and Cloud Computing in the Developing World WG
Brokering Governance WG
Metadata Standards Catalog WG Recommendations
Biosharing Registry WG Recommendations
Scholix Franmework
+ 6 Adoption cases
69 Breakout session meetings:
12 BoF Meetings
31 Interest group meetings
10 Working group meetings
16 Joint group meetings
69 Breakout sessions
Newcomers Session, 2 RDA organisational members meeting, TAB and Chairs session
RDA/EU sponsored 8 European Early Career Researchers and Scientists & RDA/US sponsored 8 Fellowship
42 posters on display
549 participants from 33 countries
rd-alliance.org/plenaries/rda-eighth-plenary-meeting-
denver-co
WWW.RD-ALLIANCE.ORG
@RESDATALL
CC BY-SA 4.0
25. rd-alliance.org/plenaries/rda-ninth-plenary-meeting-
barcelona CC BY-SA 4.0
https://www.rd-alliance.org/plenaries/rda-ninth-plenary-meeting-barcelona
WWW.RD-ALLIANCE.ORG
@RESDATALL
Looking forward to seeing you all in Barcelona!
Register now:
https://www.rd-alliance.org/plenaries/rda-ninth-plenary-meeting-barcelona/rda-9th-
plenary-registration
Early Bird Registration until 27th February 2017 midnight CET
26. rd-alliance.org/plenaries/rda-ninth-plenary-meeting-
barcelona CC BY-SA 4.0
WWW.RD-ALLIANCE.ORG
@RESDATALL
Call for Poster Session
https://www.rd-alliance.org/plenaries/rda-ninth-plenary-meeting-barcelona/rda-9th-
plenary-poster-session
APPLICATIONS are due: 12th March 2017 at 23:00 UTC
27. rd-alliance.org/plenaries/rda-tenth-plenary-meeting-
montreal-canada CC BY-SA 4.0
WWW.RD-ALLIANCE.ORG
@RESDATALL
https://www.rd-alliance.org/plenaries/rda-tenth-plenary-meeting-montreal-canada
The 10th RDA Plenary Meeting will take place from 19 to 21 September 2017
in Montreal, Canada. The meeting is co-organised by RDA, the University of
Montreal and Research Data Canada, Canada.
29. RDAin a Nutshell
WWW.RD-ALLIANCE.ORG/
@RESDATALL
RDA Global
Email - enquiries@rd-alliance.org
Web - www.rd-alliance.org
Twitter - @resdatall
LinkedIn -
www.linkedin.com/in/ResearchDataAlliance
Slideshare -
http://www.slideshare.net/ResearchDataAlliance
RDA Europe
Email - info@europe.rd-alliance.org
Twitter - @RDA_Europe
RDA US
Twitter - @RDA_US
Editor's Notes
Guiding Principles:
Openness
Consensus
Balance
Harmonization
Community-driven
Non-profit and technology-neutral
Guiding Principles:
Openness
Consensus
Balance
Harmonization
Community-driven
Non-profit and technology-neutral
Guiding Principles:
Openness
Consensus
Balance
Harmonization
Community-driven
Non-profit and technology-neutral
Expand your network and meet new data science professionals, working in multiple disciplines, including but not limited to academia, library sciences, earth science, astronomy and meteorology