ElN - repository integration at the University of Goettingen

Pilot integration of the RSpace electronic lab notebook and the Dataverse repository at the University of Goettingen

14.06.2018 Dataverse Community Meeting 1
Pilot integration of an electronic lab notebook and
an open source research data repository as part of a
modular biomedical research data platform
Harald Kusch, orcid.org/0000-0002-9895-2469
Sara Nußbeck, orcid.org/0000-0003-1223-6494
Péter Király, orcid.org/0000-0002-8749-4597
Rory Macneil
Mercè Crosas, orcid.org/0000-0003-1304-1939

14.06.2018 Dataverse Community Meeting 2
Research Data Platform
Integrative Data Management
CRC 1002
Research Data Platform
• Collection and interconnection
of research data used in
publications
• Persistent resolvable access
and long-term re-usability of
CRC 1002 data
• Data standardization for
submission to public
repositories
• Data access: Development of
Use & Access Policies

14.06.2018 Dataverse Community Meeting 3
ELN data organization
Cross-linking data in an ELN
Mouse Line
Catalogue
Antibody
Catalogue
Cell Line
Catalogue
Echo
Data
RSpace
Published Data
Registry
Research Group
Filestores
Web Resources
(Databases, Catalogues)
Research Group
Databases

14.06.2018 Dataverse Community Meeting 4
ELN data organization
Example: Cross-linking data in an ELN

14.06.2018 Dataverse Community Meeting 5
ELN data organization
Structured documentation
• Centralized protocols
• Learning tool
• Quickly shared
• Metadata recording facilitated

14.06.2018 Dataverse Community Meeting 6
ELN data organization
Sustainability
Implemented ORCID integration

14.06.2018 Dataverse Community Meeting 7
ELN data export
Sustainability
Easy additional re-usable archiving strategies:
Regular Data-Exports
Most similar to paper, partially interactive => PDF-Format
Most similar to ELN (Rspace), interactive => HMTL-Format
Interoperability, human and machine readability => XML-Format
Interfaces to repository software (e.g. Dataverse, DSPACE)

14.06.2018 Dataverse Community Meeting 8
ELN data publishing
Sustainability
Three-click action: Data export into Dataverse repository

14.06.2018 Dataverse Community Meeting 9
ELN documentation
Sustainability
Persistent identification via DOI and ORCID integration

14.06.2018 Dataverse Community Meeting 10
Summary & Outlook
• ELN facilitates digital data organization
• Metadata schema application easily configurable
and re-usable
• Existing interfaces to repository software tools
facilitate vendor-independent data sharing
• Dataverse repository enables easy publishing of
persistently identifiable datasets

14.06.2018 Dataverse Community Meeting 11
Developments Needed
❖Conceptual
➢ Recognition of the benefits of
➢Connected ELNs as data organising tools
➢Enhanced ELN  repository workflow
❖ Practical
➢ Development of Repository APIs
➢ for highly organised, heterogeneous data
➢ ingestion, query, export
Please come to our poster for further discussions!

14.06.2018 Dataverse Community Meeting 12
Dr. Sara Nußbeck
(TP INF-Leader IT)
Prof. Dr. Blanche Schwappach
(TP INF-Leader Research)
Dr. Harald Kusch
(PostDoc)
Markus Suhr
(B.Sc. Inf)
Dr. Evelina De Laurentiis
(PostDoc)
CRC 1002/1190 INF team
orcid.org/0000-0003-1223-6494 orcid.org/0000-0003-0225-6432
orcid.org/0000-0002-6469-1627 orcid.org/0000-0002-9895-2469 orcid.org/0000-0002-6307-3253
Georg Aschenbrandt
Luca Freckmann
Christian Henke
Sophia Rheinländer
Björn Hansen

14.06.2018 Dataverse Community Meeting 13
Visit http://www.eresearch.uni-goettingen.de/content/eresearch-toolbox-electronicnote-keeping for further information.
All icons used were designed using Freepik from and licensed under Creative Commons BY 3.0. www.freepik.com; www.flaticon.com

This document summarizes work by the RDA/WDS Publishing Data Interest Group to develop a conceptual and practical framework for linking data to literature. It describes the goals of linking research data and publications to increase discoverability, enable proper data reuse, and support attribution. It then outlines a proposed "multi-hub model" infrastructure as an inclusive, standards-based solution. Two key outputs are presented: 1) A prototype "Data-Literature Interlinking" service that has generated over 2 million links, and 2) The Scholix interoperability framework and guidelines for exchanging link data between sources in a standardized way. Participation by sharing link data or helping expand the Scholix standards is encouraged.

Global registries initiative frumkin omodei

The document discusses a global initiative to facilitate open access to scholarly resources and research data across boundaries by building a federation of registries. It provides use cases of how such a system could help postgraduate students, research project leaders, administrators, and ICT specialists discover and monitor globally accessible data relevant to their work. The proposed strategy is to create a "Register of Registries" that would enable consistent discovery services for finding data in collections through a standardized, interoperable model. An initial scoping meeting was held in 2007 and annual meetings since to develop the strategy.

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Vlaamse Vereniging voor Bibliotheek, Archief & Documentatie vzw (VVBAD)

Jan haspeslagh - Vlaams Instistuut voor de Zee

This document discusses open data and the process of archiving, documenting, quality checking, integrating, publishing, and redistributing data. It describes how data is archived at the Marine Data Archive and documented with metadata. Quality control ensures data is correctly interpreted and usable. Data is integrated and published through the Integrated Marine Information System with discovery metadata. A data policy advocates open data exchange and making data publicly available while recognizing the original source. The main challenges are convincing scientists to openly share data and having no mandates for participation.

Altman RDAP11 Policy-based Data Management

Smith RDAP11 NSF Data Management Plan Case Studies

The Rocky Road to Reuse

This document discusses challenges and proposed solutions for improving data sharing, integration, and reuse in research. It outlines the current research data lifecycle and issues like a lack of linking between data and publications. A proposal is made for researchers to publish data in repositories under embargo and automatically notify funders, then link the data to publications. The document also describes efforts by organizations like FORCE11, the National Data Service, and RDA to improve data search, linking, and publishing through collaboration. Key areas discussed include electronic lab notebooks, data repositories, search, linking data to publications, and citation.

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.

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Deutsche Forschungsgemeinschaft (DFG) - German Research Foundation

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Research data sharing enables validation and new analyses of results, ensures efficient use of public funds, and counters misconduct. Funding agencies can encourage open data practices by requiring long-term storage, promoting data publication, and helping make data findable through catalogs. They should work with research communities to understand infrastructure needs, partner with libraries on preservation, and consider discipline-specific approaches rather than one-size-fits-all solutions.

Comeaux RDAP11 Data Archives in Federal Agencies

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British Oceanographic Data Centre's Published Data Library

Adam Leadbetter

The document outlines the objectives, design, and current status of the Published Data Library (PDL) system. The objectives are to deliver meaningful and discoverable data collections that are fixed, usable without additional context, and assured to be available long-term. The design assigns DOIs to datasets through DataCite, with DOIs resolving to HTML landing pages containing metadata and links to usage metadata and data. Currently, descriptive pages and an 8-dataset DOI catalogue are live, along with some DOI landing pages containing human and machine-readable metadata in HTML and RDFa formats. Future work includes developing a database backend and linking to other data repositories.

Recognising data sharing

1. Metrics are being developed to track downloads and reuse of research data to understand impact and reassure researchers. A new service called IRUS for Data will provide metrics for data repositories across different platforms. 2. There is debate around what data citations mean and how they should be used and understood. Projects are working to develop best practices and encourage responsible use of citation metrics for data. 3. Ensuring research data sharing is recognized in existing systems like journal policies is challenging due to lack of standards. Initiatives are working with publishers and repositories to develop guidance and implement principles for data citation.

Who will use the open data? Mark Humphries keynote

Historic Environment Scotland

Increasing research impact: the national data registry - Alex Ball - Jisc Dig...

Jisc

Evidence shows that all forms of research output have a role in increasing the impact and value of research. Data is particularly valuable, which is why research funders are placing so much emphasis on its retention, management and discoverability. However, few universities have data collections large enough to make their data globally visible, and few have the resources to connect data held locally with data in international data centres. Jisc’s data registry service plans to cost-effectively solve this problem for universities, whilst also providing feedback for them and their researchers on how to increase the impact of their research data. This session will explain the goals and approach of the pilot, relate it to lessons from other countries and in government open data, and explain how Jisc and the community can work together to drive future developments in data discovery.

20180322 DataONE Packaging Summary

Dave Vieglais

EPSRC Policy Compliance: What researchers need to know

Introduction to the Environmental Data Initiative (EDI)

Corinna Gries

The Environmental Data Initiative enables the environmental science community to maximize knowledge development through the reusability of FAIR environmental data by providing curation services, training, and a robust and modern data repository. Please cite as: Gries, Corinna. (2018, December). Introduction to the Environmental Data Initiative (EDI) (Version 1.0). Zenodo. http://doi.org/10.5281/zenodo.4672376

Integrating repositories and eLab notebooks through an open science framework

Jisc Research data shared service overview and update - May 2016

Environmental Data Initiative

Repositories in an Open Data Ecosystem

Wolfgang Kuchinke

Data repositories are the core components of an Open Data Ecosystem. To gain a comprehensive model of the data ecosystem supporting tools and services, FAIR principles, joint storage of open data and clinical data and the integration of analysis tools should be considered. The aim was to create a data ecosystem model suitable for the sharing of open data together with sensitive data. For this purpose several tools and services were included in our data ecosystem model: Research Data Marts, I2b2 / tranSMART, CKAN, Dataverse, figshare, OSF (Open Science Framework), ... This multitude of services supports research data repositories. Different types of repositories are connected and supplement each other in the storage, release and sharing of data with different degrees of protection and data ownership. Tools to analyze, browse and visualize data are integrated in the data flow between repositories. Results of our ecosystem analysis: It doesn‘t matter where one stores data, because everything is connected for data sharing: institutional repositories with dataverses, data marts, general repositories, domain specific repositories, figshare etc. Data governance and privacy protection is integrated at the early stage of data generation.

EDI Training Module 12: Learn to Cite and Link Your Data

The document discusses citing and linking data through various discovery services. It identifies the three main search engines for discovering data as EDI Data Search, DataONE Data Search, and Google Dataset Search. It provides instructions for creating a local data catalog on a website by linking data titles and URLs. Additionally, it promotes getting an ORCID identifier to link research profiles and notes the growing number of EDI services that help with data reuse, including ingestion scripts, APIs, notifications, and provenance tracking.

Real-World Data Challenges: Moving Towards Richer Data Ecosystems

The document discusses trends in scientific data repositories and ecosystems. It notes that repositories are becoming more like virtual laboratories where scientists can conduct research. It also discusses how artificial intelligence and machine learning are being used to complement human discovery and analysis of large and complex datasets. The document raises several challenges around issues such as data ownership, rewards for data sharing and software development, and the roles of various stakeholders in research data management.

Cloud Dataverse

Merce Crosas

Presentation at the MOC Workshop, at Boston University. Cloud Dataverse will be a new service for accessing and processing public data sets in a the Massachusetts Open Cloud (MOC). It is based on Dataverse, a popular software framework for sharing, archiving, and analyzing research data. Cloud Dataverse extends Dataverse to replicate datasets from institution repositories to a cloud-based repository and store their data files in Swift, making data processing faster for in-situ application running in the cloud. Cloud Dataverse is a collaborative effort between two open source projects: Massachusetts Open Cloud (MOC) and Dataverse. The Dataversesoftware is being developed at Harvard's Institute for Quantitative Social Science (IQSS) with contributors worldwide providing 21 Dataverse installations. The Harvard Dataverse installation alone hosts more than 60,000 datasets from 300 institutions by 15,000 data authors. The MOC is a collaboration between higher education (BU, NEU, Harvard, MIT and UMass), government, and industry. Its mission is to create a self-sustaining at-scale public cloud based on the Open Cloud eXchange model.

Open Access to Research Data in H2020

OpenAIRE

This presentation provides an introduction to the Open Research Data Pilot in Horizon 2020. It explains why research data management and open data are important, what the requirements of the open research data pilot are and how OpenAIRE can help you to manage your data, open it up and comply with your funders open research data policy. - EC guidelines on open research data for H2020 project including the H2020 DMP template http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf - Online DMP tool with a template for H2020 projects https://dmponline.dcc.ac.uk/ - How to comply with the H2020 Open Research data requirements https://www.openaire.eu/how-to-comply-to-h2020-mandates-for-publications-2 - What is a data management plan and how to write one? https://www.openaire.eu/what-isa-data-management-plan-and-how-do-i-create-one - For further questions and help, contact us at: https://www.openaire.eu/support/helpdesk - For further information, check: https://www.openaire.eu/

Research Data Support at the University of Edinburgh

Robin Rice

The document summarizes the research data support services at the University of Edinburgh. It describes the university's background and information services department. It then outlines the maturity model that guides the research data management (RDM) services, the governance structure overseeing the RDM service, and the funding model that supports it. The document also summarizes the university's RDM policy and the various tools and support provided across the research data lifecycle, from creating data management plans and storing data to publishing and preserving data in the long term.

ODIN Final Event - The Care and Feeding of Scientific Data

datacite

RDA Update

This document summarizes an update on the Research Data Alliance (RDA). It discusses the growth of RDA membership and activities. Key points include: - RDA works to reduce barriers to data sharing and exchange by building social, organizational and technical infrastructure. - RDA has grown significantly since its launch in 2013, with over 2,500 members from over 90 countries working in various working groups. - Working groups focus on developing deliverables like standards, best practices and code to enable data sharing in various domains and for community needs, data stewardship, and base infrastructure. - The first deliverables have been presented, with more to come, aimed at making data sharing and discovery more trustworthy

What's hot

Research Data Shared Services

Research data spring: a consortial approach to RDM within SaS

Deutsche Forschungsgemeinschaft (DFG) - German Research Foundation

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Research data spring: extending the OPD to cover RDM

British Oceanographic Data Centre's Published Data Library

Adam Leadbetter

Recognising data sharing

Who will use the open data? Mark Humphries keynote

Historic Environment Scotland

Increasing research impact: the national data registry - Alex Ball - Jisc Dig...

Jisc

20180322 DataONE Packaging Summary

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EPSRC Policy Compliance: What researchers need to know

Introduction to the Environmental Data Initiative (EDI)

Corinna Gries

Integrating repositories and eLab notebooks through an open science framework

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Cloud Dataverse

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Research Data Support at the University of Edinburgh

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Research Data Alliance Member Statistics August 2015

This document provides an update on the Research Data Alliance (RDA). It summarizes that the RDA community focuses on building infrastructure to reduce barriers to data sharing and accelerate the development of coordinated global data infrastructure. It notes that the RDA has grown significantly since its launch in 2013 and now has over 3,000 members from over 100 countries. It also lists several outputs and deliverables that RDA working groups have produced to enable increased data sharing and interoperability.

Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...

Jack DiGiovanna

Making data and analytics FAIR has transformative potential within organizations to build on existing knowledge. FAIR resources also democratize access to information and tools in underserved communities. Global standards and analysis platforms provide strong foundational elements. However, FAIRness across time and different sectors of the biomedical workforce presents challenges. Here we summarize how platforms make data and analysis FAIR today and what we see as key areas of future focus. BioIT 2024 invited talk.

Introduction to eudat and its services

EUDAT

Are you a researcher, citizen scientist, institution or community looking for data storage and value-added services? Do you want access to tools to make your research data more FAIR (findable, accessible, interoperable, and reusable)? Interested in seeing how the future European Open Science Cloud could support research data and practically foster cross-border, cross-disciplinary collaboration? Then this webinar is for you!

Research Data Alliance Member Statistics June 2015

This document provides an update on the Research Data Alliance (RDA) from June 2015. It summarizes that the RDA community focuses on building infrastructure to reduce barriers to data sharing and accelerate the development of global data infrastructure. It notes that the RDA has grown significantly since its launch in 2013 and now has over 2,900 members from 102 countries. It also lists several outputs and deliverables produced by RDA working groups to enable improved data sharing, including standards for data citation, metadata and data type registries.

Research Data Alliance Member Statistics October 2015

This document provides an update on the Research Data Alliance (RDA). It summarizes that the RDA community focuses on building infrastructure to reduce barriers to data sharing and accelerate the development of coordinated global data infrastructure. It notes that the RDA has grown significantly since its launch in 2013 and now has over 3,300 members from 104 countries. It also lists several outputs and deliverables produced by RDA working groups, including standards for data citation, metadata directories and data type registries. Finally, it outlines RDA's organizational structure and previews upcoming plenary meetings in future years.

Research Data Alliance Member Statistics September 2015

EDINA, University of Edinburgh

User engagement in research data curation

This document discusses several studies on user engagement in research data curation. It finds that institutional repositories for data were developed without input from researchers, leading to systems that did not meet researchers' needs. Barriers to open data sharing included concerns over commercial use and maintaining ownership. Successful data curation requires understanding disciplinary differences and developing trusted relationships with researchers through dialogue early in projects.

Research Data Alliance Member Statistics July 2015

This document provides an update on the Research Data Alliance (RDA). It summarizes that the RDA community focuses on building infrastructure to reduce barriers to data sharing and accelerate the development of coordinated global data infrastructure. It notes that the RDA has grown significantly since its launch in 2013 and now has over 3,000 members from over 100 countries. It also summarizes several outputs and deliverables from RDA working groups, including standards for data citation, metadata directories and data type registries. Finally, it previews upcoming RDA plenary meetings in places like Paris, Tokyo, and the United States.

Bio Data World - The promise of FAIR data lakes - The Hyve - 20191204

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D4Science Data infrastructure: a facilitator for a FAIR data management

D4Science is a hybrid data infrastructure that integrates technologies to provide elastic access and usage of data and data management capabilities. It hosts over 50 virtual research environments for over 2500 scientists across 44 countries. D4Science aims to facilitate FAIR (Findable, Accessible, Interoperable, Re-usable) data management by assigning unique identifiers and rich metadata to resources, publishing catalogs to enable discovery, making resources available through standards, adding metadata in multiple formats, and requiring licenses and provenance to promote reuse.

D4Science Data Infrastructure - Facilitator for a FAIR Data Management

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EMBL Australian Bioinformatics Resource AHM - Data Commons

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This document discusses the development of the NIH Data Commons, which aims to create a shared framework and infrastructure for biomedical data. It notes the increasing amounts of data being generated and the need for data sharing and interoperability. The Data Commons framework treats data, tools, and publications as digital objects that are findable, accessible, interoperable and reusable. Current pilots include deploying reference datasets in the cloud, indexing data and tools, and a credits system for cloud resources. Challenges discussed include metrics, costs, standards, incentives and sustainability. The framework's relevance for supporting open data in Australia is also addressed.

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This document discusses linking together data, services, and things to support a collaborative data management facility for a wind characterization scientific study. It proposes using semantic technologies like REST, Linked Open Data, Linked Services, and concepts from the Internet of Things. The approach aims to seamlessly link the study's instruments, services, activities, and data to gain insights and make everything accessible and discoverable for researchers. It leverages existing open-source and commercial tools and illustrates how a linked knowledge environment can support search and discovery across components for both facility operations and scientists using the study results.

British Library Datasets Programme 2010

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Networked Science, And Integrating with Dataverse

African Open Science Platform

This document discusses the growing interconnectedness of research data and tools in a networked science environment. It summarizes Elsevier's current and potential future connections to the Dataverse platform, including exporting data from the Hivebench ELN to Dataverse, linking articles to datasets in Dataverse through frameworks like Scholix, indexing Dataverse through Elsevier's data search tools, and tracking metrics on Dataverse datasets through analytics platforms like PlumX. The author expresses interest in further strengthening integration between these systems to advance open sharing of research data.

Open Science Globally: Some Developments/Dr Simon Hodson

This document summarizes Simon Hodson's presentation on open science and FAIR data developments globally. Some key points: 1) There is a growing policy push for open research data, with funders and organizations adopting data sharing policies based on FAIR data principles of findability, accessibility, interoperability, and reusability. 2) Initiatives are working to build the international ecosystem of open science, including components for reporting research outputs, persistent identifiers, data standards, data repositories, and criteria for trustworthy data. 3) The African Open Science Platform aims to lay the foundations for open science in Africa through frameworks for policy, incentives, training, and technical infrastructure development. 4) International

What infrastructure is necessary for successful research data management (RDM...

heila1

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