This document discusses the concept of a shared research data management service. It outlines the need for interoperability between data storage, management plans, repositories, and other systems. Various institutional scenarios are presented, from those just starting research data management to those with some existing infrastructure. The vision is for a Jisc-provided shared cloud storage service integrated with publication and archiving functionality to help researchers easily manage the full data lifecycle. Potential technical solutions already exist that could be integrated to develop such a service. Stages of development, benefits, and timelines are proposed.
Open data in ubi systems research data management plan (part 4)Heli Väätäjä
This slideset motivates to creating a data management plan and gives initial advice. Slides are from the seminar on Open Data in Ubiquitous Systems Research aimed for doctoral students in HCI and CS.
Open data in ubi systems research data management plan (part 4)Heli Väätäjä
This slideset motivates to creating a data management plan and gives initial advice. Slides are from the seminar on Open Data in Ubiquitous Systems Research aimed for doctoral students in HCI and CS.
National data services lightening talk at the RDAJisc RDM
Our slides for the lightening talk at the annual RDA in Tokyo. All about the national shared services to support research data infrastructure. March 2016.
UK Research Data Discovery Service metadata schemaJisc RDM
An overview of the metadata schema being developed for the UK research data discovery service. Dom Fripp at the Research Data Network event at Cardiff University, May 2016.
Building data networks: exploring trust and interoperability between authoris...Repository Fringe
Building data networks: exploring trust and interoperability between authoris, repositories and journals. Varsha Khodiyar , Scientific Data; Neil Chue Hong, Journal of Open Research Software; Rachael Kotarski, DataCite, Peter McQuilton, BioSharing; Reza Salek, Metabolights. At Repository Fringe 2015
OAIS and It's Applicability for Libraries, Archives, and Digital Repositories...faflrt
ALA/FAFLRT Workshop on Open Archival Information Service (OAIS). Presented by Robin Dale, RLG. Sponsored by ALA Federal and Armed Forces Libraries Roundtable (FAFLRT). Presented on June 16, 2001 at the ALA Annual Conference.
'Making the case for a research data shared service' in the Measuring Success and Changing Culture session Presented during the National RDM Strategies session of the Göttingen-CODATA RDM Symposium 2018
Trusted Digital Repositories: OAIS and Certification - Robin Dale (2002)faflrt
Open Archival Information Service (OAIS) workshop. Presented by Robin Dale of RLG. Sponsored by ALA Federal and Armed Forces Libraries Roundtable (FAFLRT). Presented on June 15, 2002 at ALA Annual Conference.
National data services lightening talk at the RDAJisc RDM
Our slides for the lightening talk at the annual RDA in Tokyo. All about the national shared services to support research data infrastructure. March 2016.
UK Research Data Discovery Service metadata schemaJisc RDM
An overview of the metadata schema being developed for the UK research data discovery service. Dom Fripp at the Research Data Network event at Cardiff University, May 2016.
Building data networks: exploring trust and interoperability between authoris...Repository Fringe
Building data networks: exploring trust and interoperability between authoris, repositories and journals. Varsha Khodiyar , Scientific Data; Neil Chue Hong, Journal of Open Research Software; Rachael Kotarski, DataCite, Peter McQuilton, BioSharing; Reza Salek, Metabolights. At Repository Fringe 2015
OAIS and It's Applicability for Libraries, Archives, and Digital Repositories...faflrt
ALA/FAFLRT Workshop on Open Archival Information Service (OAIS). Presented by Robin Dale, RLG. Sponsored by ALA Federal and Armed Forces Libraries Roundtable (FAFLRT). Presented on June 16, 2001 at the ALA Annual Conference.
'Making the case for a research data shared service' in the Measuring Success and Changing Culture session Presented during the National RDM Strategies session of the Göttingen-CODATA RDM Symposium 2018
Trusted Digital Repositories: OAIS and Certification - Robin Dale (2002)faflrt
Open Archival Information Service (OAIS) workshop. Presented by Robin Dale of RLG. Sponsored by ALA Federal and Armed Forces Libraries Roundtable (FAFLRT). Presented on June 15, 2002 at ALA Annual Conference.
Entrepreneurship and solopreneurship requires some specific skills, called the Outer Game, in order to become profitable. This presentation walks you through the various steps you will need to master in order to make a profitable and rewarding business.
User privacy and data trustworthiness in mobile crowd sensingLeMeniz Infotech
User privacy and data trustworthiness in mobile crowd sensing
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Web : http://www.lemenizinfotech.com
Web : http://www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Blog : http://ieeeprojectspondicherry.weebly.com
Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/
Youtube:https://www.youtube.com/watch?v=eesBNUnKvws
Jenny Mitcham from the University of York and Chris Awre from the University of Hull share lessons learned from their project to explore the potential of the digital preservation solution Archivematica to help manage research data that academics within the University produce. The project 'Filling the Digital Preservation Gap' has been carried out with funding from Jisc as part of their Research Data Spring program and was a collaboration of the University of York and the University of Hull. The project did not only explore Archivematica as a possible solution but also how it could integrate with the repositories and other systems for the management of research data.
The Series is jointly sponsored by ANDS and CAUL.
Open Data management is still not trivial nor sustainable - COMSODE results are here to bring automation to publication and management of Open Data in public institutions and companies. Presentation includes Open Data Ready standard proposal, three use cases and invitation for Horizon 2020 projects 2016.
Figshare is a research data management platform that offers out-of-the-box compliance with the EPSRC mandate on open access to research data. Not only does figshare satisfy open data mandates but it also provides a world class research data dissemination platform. With private sharing and collaboration functionality, figshare for institutions provides a flexible and comprehensive end-to-end data management platform. This session will focus on how the University of Sheffield and the University of Salford have implemented figshare for institutions.
Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...Denodo
Watch full webinar here: https://bit.ly/3fBpO2M
Data Fabric has been a hot topic in town and Gartner has termed it as one of the top strategic technology trends for 2022. Noticeably, many mid-to-large organizations are also starting to adopt this logical data fabric architecture while others are still curious about how it works.
With a better understanding of data fabric, you will be able to architect a logical data fabric to enable agile data solutions that honor enterprise governance and security, support operations with automated recommendations, and ultimately, reduce the cost of maintaining hybrid environments.
In this on-demand session, you will learn:
- What is a data fabric?
- How is a physical data fabric different from a logical data fabric?
- Which one should you use and when?
- What’s the underlying technology that makes up the data fabric?
- Which companies are successfully using it and for what use case?
- How can I get started and what are the best practices to avoid pitfalls?
Unlock Your Data for ML & AI using Data VirtualizationDenodo
How Denodo Complement’s Logical Data Lake in Cloud
● Denodo does not substitute data warehouses, data lakes,
ETLs...
● Denodo enables the use of all together plus other data
sources
○ In a logical data warehouse
○ In a logical data lake
○ They are very similar, the only difference is in the main
objective
● There are also use cases where Denodo can be used as data
source in a ETL flow
A brief overview of the development and current workflows for Research Data Management at Imperial College London, presented to colleagues at the University of Copenhagen and Roskilde University in Denmark.
Researchers require infrastructures that ensure a maximum of accessibility, stability and reliability to facilitate working with and sharing of research data. Such infrastructures are being increasingly summarised under the term Research Data Repositories (RDR). The project re3data.org – Registry of Research Data Repositories – began to index research data repositories in 2012 and offers researchers, funding organisations, libraries and publishers an overview of the heterogeneous research data repository landscape. In December 2014 re3data.org listed more than 1,030 research data repositories, which are described in detail using the re3data.org schema (http://dx.doi.org/10.2312/re3.003). Information icons help researchers to identify easily an adequate repository for the storage and reuse of their data. This talk describes the heterogeneous RDR landscape and presents a typology of institutional, disciplinary, multidisciplinary and project-specific RDR. Further, it outlines the features of re3data. org and it shows current developments for integration into data management planning tools and other services.
By the end of 2015 re3data.org and Databib (Purdue University, USA) will merge their services, which will then be managed under the auspices of DataCite. The aim of this merger is to reduce duplication of effort and to serve the research community better with a single, sustainable registry of research data repositories. The talk will present this organisational development as a best practice example for the development of international research information services.
Belgium & Luxembourg dedicated online Data Virtualization discovery workshopDenodo
Watch full webinar here: https://bit.ly/33yYuQm
Data virtualization has become an essential part of enterprise data architectures, bridging the gap between IT and business users and delivering significant cost and time savings. This technology revolutionizes the way data is accessed, delivered, consumed and governed regardless of its format and location.
This 1.5 hour discovery session will show help you identify the benefits of this modern and agile data integration and management technology for your organisation.
Recent national and international mandates and reports seek to promote an open research infrastructure which facilitates easy access to knowledge and information for all. For example, The UK Open Research Data Task Force report, released in February 2019, recommends user-friendly services for research data management and infrastructure to maximise interoperability and discoverability.
Jisc has built the Open Research Hub (JORH), which integrates a repository, preservation, reporting and storage platform. This cloud-based service is a community governed, multi-tenant solution for universities and other research institutions to manage, store, preserve and share their published research data. Based on existing open standards, the service’s open and extensive data model incorporates best practice from across the sector, including DataCite, CrossRef, CERIF, Dublin Core and PREMIS.
While the Hub was built to address the needs of research data curation, its adoption of open, best practice standards means it has the potential to allow the service to handle a much wider range of digital research objects, including Open Access articles, theses and software. The data model, rich messaging layer and an open API facilitate interoperability with other institutional and scholarly communications systems. This provides the potential for the Hub to underpin infrastructure capable of meeting the requirements of an ever-evolving open research agenda.
This talk will introduce some of the key initiatives seeking to shape open research infrastructure and discuss how the Hub’s current and future development is directed towards facilitating open research best practice. Consideration will be given to how the Hub either meets or can meet recent recommendations such as FAIR, Plan S, ORDTF and the COAR’s Next Generation Repositories.
Jisc Research Data Shared Service - a Samvera case studyJisc RDM
As part of its Research Data Shared Service (RDSS), Jisc has been developing a repository component as part of its core architecture . Through making an integrated research data management platform available to UK Universities, there is a growing demand from small to medium HEIs for the RDSS to provide a single repository solution that fits their needs for publications and data with workflows for Open Access and REF submissions. To achieve this, the repository must be integrated with other Jisc Open Access services such as Sherpa, Jisc Monitor and Publications router, along with those provided by external stakeholders such as ORCID, Crossref, DataCite and OpenAIRE.
This presentation is a case study in evaluating Samvera for this role, and its suitability as a multi-tenanted, sustainable hybrid repository that is both attractive to researchers and universities and aligns with the broader international objectives of the community, the FAIR agenda and open science.
Stories from the Field: Data are Messy and that's (kind of) okJisc RDM
Jude Towers and David Ellis on research data at Lancaster Unviversity and within their own disciplines. At the Research Data Champions Day 26 March 2018.
Title: Monitoring institutional compliance with RDM policy
database that is used by the team to monitor compliance.
Research Data Network
University of Strathclyde
**Researcher engagement resources: a demonstration**
*Rosie Higman, University of Cambridge/Manchester, Hardy Schwamm, Lancaster University*
Research Data Network
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
2. Overview
Shared Services For Research Data Management July 2015 2
• RDM systems Architecture
• Institutional Scenarios
• Vision for shared service
• Concept for Jisc procured/provided shared service
• Benefits
• Timescales
3. 3
Top Level RDM Architecture
Shows need for interoperability and
transfers of data and metadata
between a number of systems and
services
• Data Storage (Active and Archive
• DMPs
• CRIS systems
• Repositories
• Data catalogues and registries
• External data centres
• National and International
aggregation and identifier
services
Credit for Architecture concepts: John Lewis
(Sheffield) & Stuart Lewis (Edinburgh)
http://dx.doi.org/10.6084/m9.figshare.120223
0
Shared Services For Research Data Management July 2015
4. Institutional Scenarios
• Scenarios range from Greenfield (no RDM
infrastructure in place) to various brownfield scenarios
• Brownfield scenarios based on gaps within
architecture. Examples include:
• Institutions who may have established central active
data storage, but are lacking a publication platform,
data registry and archive storage.
• Institutions with a data repository, who may be
lacking active data storage options for researchers
Shared Services For Research Data Management July 2015 4
Scenarios and requirements derived from architecture
5. Vision for Jisc provided shared service
Jisc could facilitate researchers cloud storage space
which can sync with their personal machines and
common workflows to store active research data and
allow sharing and collaboration between peers
Within this space allow easy functionality to publish and
archive research outputs fulfilling policy requirements
throughout the RDM lifecycle
Shared Services For Research Data Management July 2015 5
Researchers shouldn’t need to think (too much!) about
Research Data Management
6. What a researcher should see
Shared Services For Research Data Management July 2015 6
Familiar user friendly UI that links with workflows
7. What a researcher should see
Shared Services For Research Data Management July 2015 7
Ingest to publication repository or archive – Minimal metadata
8. What a researcher should see
UK Research Data Store June 2015 8
Publication Page for ResearchObject (with DOI/Metrics etc)
9. What we need
Shared Services For Research Data Management July 2015 9
Modules that seamlessly integrate with each other
10. Technology already exists
Active Data Storage and File syncing and sharing (OneDrive, Sharepoint
DropBox, Box, Owncloud, Institutional Storage etc.) Services that researchers
are used to as the base interface to store active data and use as access points
to publication/archival services
Publication/Archival Ingest UI (Figshare, Eprints, Zenodo other? In house?)
Repository Front End (Figshare, Eprints, UKRDDS etc.)
Archival Management / Long term Storage (Arkivum/Others)
Metadata Schema (From Research at Risk Metadata WP)
EEA based storage (AWS,Azure etc.)
Network (JANET)
LongTerm Preservation (Metadata and tools need specifying for RDM)
Shared Services For Research Data Management July 2015 10
Don’t re-invent the wheel, join up technology that
already exists
11. Benefits
Meets policy requirements An easy way to meet funder’s requirements with little
effort from the institution
Network connecting with Janet means that data egress costs will be reduced or
negligible
Storage shared storage could be procured at cheaper rates
User Friendly many researchers are already familiar with the types of UI’s mentioned
Discoverability and Access Allows easy open access to research outputs if required
Aggregation allows for easy aggregation of UK research outputs to share globally
LongTerm Storage archived research objects are safely stored with multiple copies
Integration These systems already exist and are starting to integrate
LocalView System could be institutionally branded
Research Data Problem Eases RDM issues for the institutions where there isn’t the
capacity or desire to implement their own system
Shared Services For Research Data Management July 2015 11
12. Timeline 2015-16
Jan
15
Mar
15
May
15
Jul 15
Sep
15
Nov
15
Jan
16
Mar
16
May
16
Jul 16
Sep
16
Nov
16
USAGE STATISTICS FOR
RESEARCH DATA
RESEARCH DATA
MANAGEMENT SHARED
SERVICE
SHARED SERVICES IN THE
PRESERVATION &
CURATION GAP
Shared Services & Infrastructure
Medium priorityHigh priority
Early consultation ProcurementSurvey
Requirements refinement workshop
Outline RDM architecture Early adopters engaged
Beta Business case
Shared service
Early intelligence gathering Requirements defined
Scope
Prototype with IRUS software Service design Business case
BetaConsultative group established
Input to COUNTER
Service
Shared Services For Research Data Management July 2015
13. Proposed Stages?
1st Stage: fully Jisc provided/procured/hosted system
2nd Stage: Jisc offer modules or national agreements to fill
architecture gaps in existing systems
• Jisc require feedback from the community and will consult
before and after an October event with preceeding
publication of shared services concepts
• If there is community agreement Jisc will begin
procurement/development
• To take these concepts forward volunteer pilot institutions
to work up detailed requirements and develop/test the
service in partnership will be needed.
Shared Services For Research Data Management July 2015 13
14. Find out more…
Thank you!
Email: rachel.bruce@jisc.ac.uk
John.kaye@jisc.ac.uk
Twitter:rachelbruce
Except where otherwise noted, this
work is licensed under CC-BY-NC-ND
Editor's Notes
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----- Meeting Notes (23/06/15 11:23) -----
security and governance. encryption
dropbox other devs
UCL ask under the hood arkivum (appliance)
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----- Meeting Notes (24/06/15 13:13) -----
data transfer costs
reduce egress costs
See ca
role.
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----- Meeting Notes (24/06/15 13:13) -----
data transfer costs
reduce egress costs
See ca
role.