What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
ISI 2024: Application Form (Extended), Exam Date (Out), EligibilitySciAstra
The Indian Statistical Institute (ISI) has extended its application deadline for 2024 admissions to April 2. Known for its excellence in statistics and related fields, ISI offers a range of programs from Bachelor's to Junior Research Fellowships. The admission test is scheduled for May 12, 2024. Eligibility varies by program, generally requiring a background in Mathematics and English for undergraduate courses and specific degrees for postgraduate and research positions. Application fees are ₹1500 for male general category applicants and ₹1000 for females. Applications are open to Indian and OCI candidates.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
2. 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.
THE RESEARCH DATA ALLIANCE
www.rd-alliance.org
building the social and technical bridges that enable open
sharing of data
32 FLAGSHIP OUTPUTS
including 4 ICT
Technical Specifications
75 ADOPTION CASES
across multiple
disciplines,
organisations &
countries
84 GROUPS WORKING ON GLOBAL DATA
INTEROPERABILITY CHALLENGES
28 Working Groups
56 Interest Groups
9,403 INDIVIDUAL MEMBERS FROM 137
COUNTRIES
68% Academia & Research
14% Public Administration
13% Enterprise & Industry
49 ORGANISATIONAL MEMBERS
9 AFFILIATE MEMBERS
21/01/2020 rd-alliance.org @resdatall | @rda_europe | @RDA_US
3. What is RDA?
21/01/2020 3
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 9,400 members globally representing 137 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 @resdatall | @rda_europe | @RDA_US
4. What does RDA do?
Reproducibility
Data preservation
Best practices for domain repositories
Legal interoperability
Data citation
Data type registries
Metadata
and so many more!
21/01/2020 4
Members come together through self-formed, volunteer and focused Working Groups and
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:
rd-alliance.org @resdatall | @rda_europe | @RDA_US
5. Who Can Join RDA?
Any individual or organisation, regardless of profession or discipline,
with an interest in reducing the barriers to the sharing and re-use of
data and who agrees to RDA’s guiding principles of:
Openness
Consensus
Balance
Harmonization
Community-driven
Non-profit and technology-neutral
Individual Membership is free at https://www.rd-alliance.org/user/register
21/01/2020 5rd-alliance.org @resdatall | @rda_europe | @RDA_US
6. Why Join RDA as an Individual Member?
21/01/2020 6
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
Individual RDA Members 9,403
rd-alliance.org @resdatall | @rda_europe | @RDA_US
7. Who is RDA – Worldwide Growth
21/01/2020 7rd-alliance.org @resdatall | @rda_europe | @RDA_US
8. Who is RDA – Organisation type
21/01/2020 8rd-alliance.org @resdatall | @rda_europe | @RDA_US
9. Who is RDA – Professional Title
21/01/2020 9rd-alliance.org @resdatall | @rda_europe | @RDA_US
10. Who is RDA – Geographical Distribution
21/01/2020 10rd-alliance.org @resdatall | @rda_europe | @RDA_US
9,403 RDA members from 137 different countries
11. Why Join RDA as an Organisational Member?
21/01/2020 11
Organisational Member Benefits
◦ Provide an organisational 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 Organisational Forums
◦ Receive regular updates on the work of the RDA
◦ Attend Organisational Assembly meetings and vote on proposed policies for consideration by the RDA
Council and for members of the Organisational Advisory Board
◦ Provide advice to RDA Council through the Organisational Advisory Board
◦ Be recognized on the RDA Website and at RDA Meetings as a supporter of data interoperability
◦ Communicate open job positions in your organisation to entire RDA community (Exclusive to
Organisational Members)
◦ Reduced RDA Plenary meeting registration fee (Exclusive to Organisational Members)
49 Organisational & 9 Affiliate Members
rd-alliance.org @resdatall | @rda_europe | @RDA_US
12. RDA Organisational Members
AARNet Pty Ltd (APL), Australia
American Geophysical Union (AGU), USA
American University Library, USA
Australian Research Data Commons, Australia
Battelle - National Ecological Observatory Network
(NEON), USA
Blackfynn Inc., USA
California Institute of Technology, USA
CANARIE, Canada
CAP Digital, France
Carnegie Mellon University, USA
Consortium of European Social Science Data Archives
(CESSDA)
Columbia University Libraries/Information Services, USA
Corporation for National Research Initiatives (CNRI)
Danish e-Infrastructure Cooperation
DANS, Data Archiving and Networked Services, The
Netherlands
Data Observation Network for Earth - DataONE
Digital Curation Centre (DCC), UK
Digital Repository of Ireland (DRI), Ireland
EGI Foundation
ELSEVIER, The Netherlands
European Parliamentary Research Service (EPRS)
European Data Infrastructure (EUDAT project)
German Data Forum, Germany
Global Biosocial Complexity Initiative, Arizona State
University, USA
Helmholtz Association, Germany
IASSIST - International Association for Social Science
Information Services
and Technology
Indiana University Pervasive Technology Institute, USA
Information Technology Research Insititute (ITRI)- National
Institute of
Advanced Industrial Science and Technology (AIST), Japan
Interdisciplinary Centre for Mathematical and
Computational Modelling
(ICM), University of Warsaw, Poland
International Association of STM Publishers
International Federation of Data Organizations for Social
Sciences
KAUST - King Abdullah University of Science and
Technology
LIBER - Association of European Research Libraries
Max Planck Computing and Data Facility (MPCDF),
Germany
Massachusetts Institute of Technology Libraries (MIT
Libraries), USA
National Center for Supercomputing Applications,
University of Illinois at
Urbana-Champaign, USA
National Library of Ireland, Ireland
Netherlands e-Science Center
NSD - Norwegian Centre for Research Data
NZ eScience Infrastructure, New Zealand
Purdue University Libraries, USA
Research Data Canada, Canada
Scholarly Publishing and Academic Resources Coalition
(SPARC), USA
Science & Technology Facilities Council (STFC), UK
The Alan Turing institute, UK
TMF – Technology, Methods, and Infrastructure for
Networked Medical
Research, Germany
Washington University in St. Louis Libraries, USA
Web Science Trust, UK
John Wiley & Sons Ltd., UK
21/01/2020 12rd-alliance.org @resdatall | @rda_europe | @RDA_US
13. RDA Affiliate Members
The Consortia Advancing Standards
in Research Administration
Information -
CASRAI
Confederation of Open Access
Repositories (COAR)
Committee on Data for Science and
Technology (CODATA)
DataCite
Group on Earth Observations (GEO)
Global Open Data for Agriculture &
Nutrition (GODAN)
International Council for Scientific
and Technical Information (ICSTI)
Connecting Research and
Researchers (ORCID)
World Data System (WDS)
21/01/2020 13rd-alliance.org @resdatall | @rda_europe | @RDA_US
14. RDA active Interest Groups (IG) & Working Groups (WG):
Discipline-focused and Partnerships
21/01/2020 14
Discipline focus
Working Groups
Agrisemantics WG
FAIRSharing Registry WG
Capacity Development for Agriculture Data WG
Rice Data Interoperability WG
Wheat Data Interoperability WG
Reproducible Health Data Services WG
Preserving Scientific Annotation WG
Blockchain Applications in Health WG
InteroperAble Descriptions of Observable Property Terminology WG (I-ADOPT WG)
Interest Groups
Agricultural Data IG (IGAD)
Biodiversity Data Integration IG
Chemistry Research Data IG
Digital Practices in History and Ethnography I
Earth Science Information Partners (ESIP)/RDA Earth, Space, and Environmental Sciences IG
Geospatial IG
Global Water Information IG
Health Data IG
Linguistics Data 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
Social Sciences & Humanities Research Data IG
Research Data Management in Engineering IG
RDA for the Sustainable Development Goals IG
Total 84 groups:
28 Working Groups & 56 Interest Groups
Partnerships
Working Groups
RDA/TDWG Metadata Standards for attribution of physical and digital collections stewardship WG
RDA/World Data System (WDS) Scholarly Link Exchange WG
RDA/World Data System (WDS) Publishing Data Workflows WG
Interest Groups
ELIXIR Bridging Force IG
RDA/National Information Standards Organization (NISO) Privacy Implications of Research Data Sets
IG
rd-alliance.org @resdatall | @rda_europe | @RDA_US
15. 21/01/2020 15
Total 84 groups:
28 Working Groups & 56 Interest Groups
Reference and Sharing
Working Groups
Data Citation WG
Data Description Registry Interoperability WG
International Materials Resource Registries WG
Research Data Collections WG
Research Data Repository Interoperability WG
Data Usage Metrics WG
Interest Groups
Data Discovery Paradigms IG
National Data Services IG
RDA/CODATA Legal Interoperability IG
Reproducibility IG
Sharing Rewards and Credit (SHARC) IG
Community Needs
Working Groups
RDA/CODATA Summer Schools in Data Science and Cloud Computing in the Developing World
WG
Interest Groups
CODATA/RDA Research Data Science Schools for Low and Middle Income Countries
Archives & Records Professionals for Research Data IG Data for Development IG
Early Career and Engagement IG
Education and Training on handling of research data IG
Ethics and Social Aspects of Data IG
International Indigenous Data Sovereignty IG
Open Questionnaire for Research Data Sharing Survey IG
Data for Development IG
Research Funders & Stakeholders on Open Research and Data Management Policies and
Practices IG
Coordinating the Global Open Science Commons IG
RDA active Interest Groups (IG) & Working Groups (WG):
Focus on Reference/Sharing and Community Needs
rd-alliance.org @resdatall | @rda_europe | @RDA_US
16. 21/01/2020 16
Base Infrastructure
Working Groups
Data Type Registries WG
Metadata Standards Catalog WG
PID Kernel Information WG
Software Source Code ID WG
Research Metadata Schemas WG
Interest Groups
Data Fabric IG
Data Foundations and Terminology IG
Disciplinary Interoperability Framework IG
Big Data IG
Metadata IG
PID IG
Software Source Code IG
Vocabulary Services IG
Federated Identity Management IG
Data Economics IG
Data Stewardship and Services
Working Groups
Brokering Framework WG
World Data System (WDS)/RDA Assessment of Data Fitness for Use WG
Data Versioning WG
FAIR Data Maturity Model WG
Interest Groups
Active Data Management Plans IG
Data in Context IG
Data Rescue IG
Domain Repositories IG
Virtual Research Environments IG
Libraries for Research Data IG
Physical Samples and Collections in the Research Data Ecosystem IG
Preservation Tools, Techniques, and Policies IG
RDA/World Data System (WDS) Certification of Digital Repositories IG
Repository Platforms for Research Data IG
Research Data Architectures in Research Institutions IG
Data policy standardisation and implementation IG
GO FAIR IG
Open Science Graphs IG
Total 84 groups:
28 Working Groups & 56 Interest Groups
RDA active Interest Groups (IG) & Working Groups (WG):
Focus on Data Stewardship and Infrastructures
rd-alliance.org @resdatall | @rda_europe | @RDA_US
17. Retired Working and Interest Groups
(Groups that have completed their work and currently inactive within RDA)
21/01/2020 17
Historical Groups
Brokering Governance WG
Metadata Standards Directory WG
PID Information Types WG
Practical Policy WG
RDA/World Data System (WDS) Publishing Data Bibliometrics WG
RDA/World Data System (WDS) Publishing Data Services WG
Repository Audit and Certification DSA–WDS Partnership WG
Data Foundations and Terminology WG
Provenance Patterns WG
DMP Common Standards WG
Empirical Humanities Metadata WG
Exposing Data Management Plans WG
On-Farm Data Sharing (OFDS) WG
Persistent Identification of Instruments WG
Mapping the Landscape IG
Preservation e-Infrastructure IG
Quality of Urban Life IG
Development of Cloud Computing Capacity and Education in Developing
World Research IG
Weather, Climate and Air quality IG
Structural Biology IG
RDA/World Data System (WDS) Publishing Data Cost Recovery for Data Centres
IG
Marine Data Harmonization IG
RDA/World Data System (WDS) Publishing Data IG
Brokering IG
Research Data Provenance IG
Long tail of research data IG
rd-alliance.org @resdatall | @rda_europe | @RDA_US
18. RDA Recommendations that Make Data Work
21/01/2020 18
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
“Create - Adopt - Use”
32 flagship Recommendations & Outputs
More than 75 cases of Adoption in Different Domains, Organisations and Countries
rd-alliance.org @resdatall | @rda_europe | @RDA_US
19. RDA Recommendations & Outputs
21/01/2020 19
CATEGORIES OF RECOMMENDATIONS & OUTPUTS
Recommendations: RDA’s flagship outputs and the equivalent of “specifications” or
“standards” that other organisations create and endorse.
Supporting Outputs: RDA outputs that originate from the work of RDA groups, but not
always adoptable by other organisations. “Upon request” by RDA groups, these outputs
are reviewed by the RDA member community and if no major objections or gaps are
identified, they are approved to use the RDA Brand.
Other Outputs: These are workshop reports, published articles, survey results, etc.
produced by RDA groups. Upon request by the groups, these outputs are posted on the
RDA websitebut have no level of endorsement.
rd-alliance.org @resdatall | @rda_europe | @RDA_US
20. RDA Recommendations
21/01/2020 20
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
Data Foundation & Terminology Model: produced by the Data Foundation &
Terminology WG which ensures researchers use a common terminology when referring
to data.
PID Information Types API: persistent Identifier Type Registry produced by the PID
Information Types WG, a conceptual model for structuring typed information to better
identify PIDs, common interface for access to this information.
The Data Type Registries Model: published by the Data Type Registries WG providing
machine-readable and researcher-accessible registries of data types that support the
accurate use of data
Practical Policies Recommendations: defining best practices of how to deal with data
automatically and in a documented way with computer actionable policy.
rd-alliance.org @resdatall | @rda_europe | @RDA_US
21. RDA Recommendations
21/01/2020 21
Dynamic-data Citation Methodology: Supports efficient processing of data and linking
from publications.
Data Description Registry Interoperability Model: Interoperability model addressing
the problem of cross platform discovery by connecting datasets together.
Metadata Standards Directory Recommendations: Community curated standards
catalogue for metadata interoperability
Research Data Collections Recommendations:
A comprehensive model for actionable collections and a technical interface
specification to enable client-server interaction.
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
rd-alliance.org @resdatall | @rda_europe | @RDA_US
22. RDA Recommendations
21/01/2020 22
Wheat Data Interoperability Recommendations: impacting the discoverability, reusability
and interoperability of wheat data by building a common framework for describing,
representing linking and publishing wheat data
Brokering Governance Recommendations: Sustainable Business Models for Brokering
Middleware to support Research Interoperability
RDA/CODATA Summer Schools in Data Science and Cloud Computing in the Developing
World Recommendations: A framework to run a series of Summer Schools in Data Science
and data sharing in low and middle income countries (LMICs)
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
rd-alliance.org @resdatall | @rda_europe | @RDA_US
23. RDA Recommendations
21/01/2020 23
RDA/WDS Repository Audit and Certification Catalogues:
Creates harmonized Common Procedures for certification of repositories at the basic level,
drawing from the procedures already put in place by the Data Seal of Approval (DSA) and the
ICSU World Data System (ICSU-WDS).
RDA/WDS Workflows for Research Data Publishing Model:
A data-publishing reference model assisting research communities in understanding options
for data publishing workflows and increases awareness of emerging standards and best
practices.
Research Data Interoperability WG Final Recommendations: Provides recommendations with
respect to an interoperable packaging and exchange format for digital content.
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
rd-alliance.org @resdatall | @rda_europe | @RDA_US
24. RDA Recommendations
21/01/2020 24
RDA/WDS Publishing Data Services: An open, universal literature-data cross-linking service
to improve data visibility, discoverability, re-use and reproducibility.
FAIRsharing: Standards, Databases, Repositories and Policies - Final Recommendation:
Guide for citation and its implementation in a registry of standards, databases and data policies
RDA/TDWG Attribution Metadata Working Group: Final Recommendations: Supports
standardized metadata for attributing work and tracking provenance in the curation and
maintenance of research collections.
PID Kernel Information Working Group: A set of guiding principles, architectural
considerations, use cases and a fundamental metadata schema to manage information in
Persistent Identifier records for scalable middleware infrastructure and automated
processes.
rd-alliance.org/recommendations-and-outputs/all-recommendations-and-outputs
rd-alliance.org @resdatall | @rda_europe | @RDA_US
26. RDA Supporting Outputs
21/01/2020 26
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.
A survey of current practices in data search services:
Survey results based on an examination of practices that data repositories employ in helping users search as well as common
data discovery issues, such as relevancy.
Addressing the Gaps: Recommendations for Supporting the Long Tail of Research Data:
Seven recommendations applicable to various stakeholders - including governments, funders, research institutions and
researchers - to help improve the current approach to managing long tail data.
Data Discovery Paradigms: User Requirements and Recommendations for Data Repositories:
Output helps data repositories improve search and discovery of data.
Eleven Quick Tips for Finding Research Data:
Educates and trains research students and early career researchers, and helps researchers more effectively and precisely
discover data that meets specific needs.
rd-alliance.org @resdatall | @rda_europe | @RDA_US
27. RDA Supporting Outputs
21/01/2020 27
Income Streams for Data Repositories:
Output provides insight for Data Centre managers and Research Infrastructures into alternative options for cost recovery,
substantiated by the results from a survey of over twenty data centres around the globe, and in different domains.
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 who are engaged in activities that involve access to and reuse of research data from diverse sources.
Matrix of use cases and functional requirements for research data repository platforms:
Based on use cases, matrix describes forty-four functional requirements identified for research data repository platforms and
provides a score identifying relative importance.
Research Data Repository Interoperability Primer:
Set of use cases and an overview of standards, technologies and tools that could be components of an adoptable approach to
facilitating interoperability between different research data repository platforms.
rd-alliance.org @resdatall | @rda_europe | @RDA_US
28. RDA Supporting Outputs
21/01/2020 28
Persistent identifiers: Consolidated assertions:
Set of assertions about the nature, creation and usage of Persistent Identifiers (PIDs). It is not meant to produce
another comprehensive document on PIDs, but to identify agreements across documents that have been
suggested to be included by experts.
Summary of Virtual Layer Recommendations:
Provides a high-level conceptual framework to support Digital Object management and service development.
Federated Identity Management for Research Collaborations:
Common requirements of Research Communities seeking to leverage Identity Federation for Authentication and
Authorisation.
Results of an Analysis of Existing FAIR Assessment Tools:
First result of the FAIR Data Maturity Model WG, based on the analysis of existing approaches related to FAIR self-
assessment tools. Questions and options stemming from theses different approaches were classified according to the
FAIR principles/facets.
rd-alliance.org @resdatall | @rda_europe | @RDA_US
29. The RDA CoreTrustSeal Adoption Story:
21/01/2020 29
Discover more
The Chinese Astronomical Data Center (CAsDC) hasbeen
providingdata servicesto usersfor over 30 years,and hasgreat
influence in the Chinese astronomical community. Over the years
however, we did not attach much importance to thestandardization
of data management,resulting in repetitive work and omissions. As
a mandatory standard for WDS, CoreTrustSeal providesuswith a
comprehensive checklist for all aspectsof our work in data
management. By introducing the CoreTrustSeal system, we realized
that we identified areaswhere we could make improvements,and
acted accordingly. In the future, we will continue to make
improvementson data management proceduresbased on CoreTrustSeal, and we recommend other datacentersto
adopt thisstandard.
CoreTrustSeal offers to any interested data repository a core level certification based on the DSA–WDS Core Trustworthy Data
Repositories Requirements catalogue and procedures.
The Chinese Astronomical Data Center (CAsDC)
rd-alliance.org @resdatall | @rda_europe | @RDA_US
30. Call for Supporting and Other RDA Outputs
21/01/2020 30
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.
Become one of the next RDA adopters!
If you are interested in any of the RDA’s recommendations or would like to
share your group's results with our international community, please fill the
contact form at https://www.rd-alliance.org/interest-rda-recommendations or
write to enquiries@rd-alliance.org. RDA Adoption & Implementation
Stories - Tell us yours!
rd-alliance.org @resdatall | @rda_europe | @RDA_US
31. What are Plenary Meetings?
21/01/2020 31
• 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.
rd-alliance.org @resdatall | @rda_europe | @RDA_US
32. Plenary Meetings: Benefits of Attending
21/01/2020 32
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
rd-alliance.org @resdatall | @rda_europe | @RDA_US
33. 21/01/2020 33
61 breakout meetings
• 13 Birds of a Feather Sessions
• 13 Working Groups Meetings
• 27 Interest groups Meetings
• 8 Joint Group Meetings (to cross fertilise among groups with a
common interest or activity)
RDA Plenary 13
Attendees at P14
Continent Countries Total Delegates Total Delegates
Europe 24 429
75,13%
North America 3 89
15,59%
Asia 6 27
4,73%
Oceania 2 16
2,80%
Africa 3 7
1,23%
South America 1 3
0,53%
Held on 23-25 October 2019
Helsinki|Espoo, FITotal Participants: 571
rd-alliance.org @resdatall | @rda_europe | @RDA_US
Organised by:
34. 34
61 breakout meetings
• 13 Birds of a Feather Sessions
• 13 Working Groups Meetings
• 27 Interest groups Meetings
• 8 Joint Group Meetings (to cross fertilise among groups with a
common interest or activity)
RDA Plenary 13
Attendees at P14
Continent Countries Total Delegates Total Delegates
Europe 24 429
75,13%
North America 3 89
15,59%
Asia 6 27
4,73%
Oceania 2 16
2,80%
Africa 3 7
1,23%
South America 1 3
0,53%
Held on 23-25 October 2019
Helsinki|Espoo, FITotal Participants: 571
rd-alliance.org @resdatall | @rda_europe | @RDA_US
Organised by:
35. 21/01/2020 35
Next RDA Plenary Meeting:
Plenary 15 - Melbourne, Australia
rd-alliance.org @resdatall | @rda_europe | @RDA_US
→ https://www.rd-alliance.org/plenaries/rda-15th-plenary-meeting-australia
36. 21/01/2020 36
RDA in 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
rd-alliance.org @resdatall | @rda_europe | @RDA_US