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Slides of the lecture for VU Amsterdam about building decentralized research data infrastructure based on the principles of the Semantic Web and Linked Data. We are building Generic Common Research and Data Infrastructure which should be distributed and robust enough to be scaled up and reused for any challenging tasks like cancer research etc, where networked services built from Open Source components and data processed and published in FAIR way with keepingthe provenance information is the part of our Data Lake. Data evaluation and credibility is the top priority, we’re providing tools for the expert community for the verification of our datasets, the transparency of data and services guarantees the reproducibility of all experiments and get bring new insights in the multidisciplinary research. This infrastructure should enforce collaboration between people, bring together general public, researchers, citizen scientists, and should be distributedfree of charge with(meta)data protected and licenced.

Since 2019, the national Borealis community of institutional administrators supports researchers locally with data curation, deposit, sharing, and preservation in Borealis, the Canadian Dataverse Repository (https://borealisdata.ca). Through monthly, bilingual community meetings, special presentations, and training events, the community engages in open knowledge sharing, discussions, and practical training, to support and improve services related to areas of shared interest across all institutions using the repository. Highlights over the past year include a new joiners training session, API training, community presentations related to Re3data repository registration efforts, data preservation, discovery of research data, an upcoming survey of administrators, data licensing, and more. The motivation for strong community engagement relates to responding to community needs and is a model for community building that fosters a culture of open dialogue and collaboration. This presentation was a lightning talk for the 2023 Dataverse Community Meeting, held in person in Braga, Portugal in June 2023.

In response to the open science movement and the growth of funder and journal policies, researchers are increasingly looking for support in depositing and sharing their research data. Responding to this need by developing accessible and inclusive services and infrastructure, Borealis is a publicly accessible, multi-disciplinary, bilingual, national research data repository, based on the open-source Dataverse software, provided in partnership with regional academic library consortia and the Digital Research Alliance of Canada. The shared infrastructure supports over 65 Canadian institutions, each managing a locally-branded collection and providing local support to researchers. With support of the Borealis team and the Dataverse North Expert Group, a national-level community of Dataverse administrators is coalescing, consisting of librarians or other information specialists. This presentation will highlight the results of a community-driven initiative to survey Canadian Dataverse administrators to develop a better understanding of this community - who they are, the service models they support, their experiences using the Dataverse software, and the challenges they face supporting researchers; as well as to surface unique perceptions and perspectives of this emerging national community. Understanding both the infrastructure and the community’s collaborative approach lays important groundwork to move forward with engaging smaller institutions, such as community colleges, as well as historically marginalized populations–both as data custodians and potential depositors. The presentation will highlight the process of developing this community-informed survey, including the formation of a working group of community members and diverse stakeholders from across Canada, questionnaire development and pre-testing. The Canadian Dataverse administrator community represents a unique effort to build equitable data sharing infrastructure that is national in scope and reflective of community needs. The presenters will conclude by sharing preliminary aggregated results and discuss the importance of collaborative approaches to implementing data repository infrastructure.

The TK and BC Labels are an initiative for Indigenous communities and local organizations. Developed through sustained partnership and testing within Indigenous communities across multiple countries, the Labels allow communities to express local and specific conditions for sharing and engaging in future research and relationships in ways that are consistent with already existing community rules, governance, and protocols for using, sharing and circulating knowledge and data. ADA has an interest in establishing the means for providing suitable representation of indigenous knowledge within the Dataverse software. This includes functionality in Dataverse to: - link to and incorporate identified sources for indigenous knowledge representation, such as TKLabels and Notices - curation processes for managing the creation, reading, updating, and deleting of metadata - present curated metadata (e.g., TKLabels and TKNotices) in catalogue records - allow external aggregators to harvest this metadata (specifically the IDN Data Catalogue, but a preferably standardized model that allows for multiple external parties to harvest)

The Repository Rodeo returns for another round of questions and answers! This popular panel, featured since Open Repositories 2016 in Dublin, offers a broad overview of the main repository platforms at Open Repositories and provides an opportunity for spirited discussion amongst panelists and attendees. Join community representatives from Dataverse, DSpace, EPrints, Fedora, Invenio, Islandora, and Samvera as we briefly explain what each of our repositories actually does. We'll also talk about the directions of our respective technical and community developments and related to the conference theme of “Repositories Unlocked for Discovery and Interoperability”, we’ll discuss how our repository communities develop and implement the standards, frameworks, architectures, and methodologies for open repositories to serve as knowledge representation databases for the structured web of data. This panel will be a great opportunity for newcomers to Open Repositories to get a crash course on the major repository options and meet representatives from each of their communities. After a brief presentation from each representative, we'll open the session up for questions from the audience.

The Dataverse Project is an open source web application to share, preserve, cite, explore, and analyze research data. It facilitates making data available to others, and allows you to replicate others' work more easily. Researchers, journals, data authors, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility. With 93 installations around the world, The Dataverse software is at the forefront of research knowledge dissemination. This workshop will demonstrate best practices in depositing and curating content in a Dataverse repository.

MuseIT aims to co-design, develop, and co-evaluate a multisensory, user-centred platform for enriched engagement with cultural assets with inclusion and equal opportunity for all as core principles. Dataverse data repository will be used as shared data repository for all MuseIT working packages wheredifferent data collections will be integrated together. There are various use cases to archive cultural heritagematerials, organise and structure metadata, data, ontologies,integrate data streams from sensors and VR devices. Metadata from different modalities should be integrated without changing their ownerships and include different modalities such aspapers, news, articles, comments, images, video, audio and lyrics. MuseIT has a plan to apply AI/ML for metadata enrichment and linkage, and enabling integration of its contentwith shared controlled vocabularies in order to deliver this information inthe knowledge graph.

Presentation at the Demos session of the Dataverse Community Meeting 2023., This work received funding from the EOSC Future project as part of the RDA Open Calls Programme aimed at on strengthening the work of RDA Communities in EOSC.

Significant events like covid pandemic, Russian-Ukrainian war orpollutionhave a double dimension of diffusion in space and timeand could be documented by sharing - built or captureddigital collections in relation to science, economy, society, individuals, etc. Significant events are not known by advance. We propose an integrated approach to the preservation of information and testimonies which will allow to protect the "voices" of the public, their testimonies, experiences, losses and aspirations. We offer an interface to access those digital collections without anydelay and selection, andresearchers from the future will decide what wassignificant in the specific period of time. This talk was give at the Dataverse Community Meeting 2023 in Braga, Portugalorganized by the University of Mihno and IQSS of Harvard University.

DANS-KNAW has developed "Archive in a box" distribution which was presented for the Dataverse Community Meeting'23 in Braga, Portugal. This distributionprovidesfully automatic FAIR Dataverse data repository deployment integrated with third-partynetworked services, and connectiontoexternal controlled vocabularies required to produce Linked Data out of datasets metadata descriptions. Italso includesdata previewers and support of custom metadata schemes such as CESSDA CMM, CLARIN CMDI, ODISSEI etc. There are multiple benefits for institutions worldwideto run Common Data Infrastructure and do community based maintenance and development as costs will drop massively with a number of organizations joining the consortium. Following distributed setup, this shared infrastructure issustainable and moresuitable for the future. To make it more flexible and suitable for different communities, in CLARIAH project we have developed SEMAF semantic transformation framework and created SpaCy Machine Learning library to create semiautomatic workflow to generate FAIR metadata descriptions of datasets.

In response to the open science movement and the growth of funder and journal policies, researchers are increasingly looking for support in depositing and sharing their research data. Responding to this need by developing accessible and inclusive services and infrastructure, Borealis is a publicly accessible, multi-disciplinary, bilingual, national research data repository, based on the open-source Dataverse software, provided in partnership with regional academic library consortia and the Digital Research Alliance of Canada. The shared infrastructure supports over 65 Canadian institutions, each managing a locally-branded collection and providing local support to researchers. With support of the Borealis team and the Dataverse North Expert Group, a national-level community of Dataverse administrators is coalescing, consisting of librarians or other information specialists. This presentation will highlight the results of a community-driven initiative to survey Canadian Dataverse administrators to develop a better understanding of this community - who they are, the service models they support, their experiences using the Dataverse software, and the challenges they face supporting researchers; as well as to surface unique perceptions and perspectives of this emerging national community. Understanding both the infrastructure and the community’s collaborative approach lays important groundwork to move forward with engaging smaller institutions, such as community colleges, as well as historically marginalized populations–both as data custodians and potential depositors. The presentation will highlight the process of developing this community-informed survey, including the formation of a working group of community members and diverse stakeholders from across Canada, questionnaire development and pre-testing. The Canadian Dataverse administrator community represents a unique effort to build equitable data sharing infrastructure that is national in scope and reflective of community needs. The presenters will conclude by sharing preliminary aggregated results and discuss the importance of collaborative approaches to implementing data repository infrastructure in a way that encourages continuing adaptability to diverse community needs.

This document has been adapted from a report presented to the Ontario Council of University Libraries (OCUL) by the Odesi Nesstar Replacement Working Group. This was a working group of OCUL Data Community (ODC) members who gathered between June 2021 and February 2022 to explore options for replacing the Odesi Nesstar repository tool. The document provides a descriptive summary of the steps undertaken by the group to make a software replacement recommendation to OCUL and its stakeholders. The steps include an environmental scan of software platforms that could be used as replacements for Nesstar and a consultation process with service providers, current and previous Nesstar users at other institutions , and OCUL members. Among the group’s outputs was a preliminary list of functional requirements for migration to the new platform, which is included in this summary. As a result, Scholars Portal is moving forward with the migration of Odesi to Borealis, the Canadian Dataverse Repository. The Background section offers some context for the Working Group’s approach and decision-making process., This document has been adapted from a report presented to the Ontario Council of University Libraries (OCUL) by the Odesi Nesstar Replacement Working Group. This was a working group of OCUL Data Community (ODC) members who gathered between June 2021 and February 2022 to explore options for replacing the Odesi Nesstar repository tool.

Ce document contient les notions techniques transverses à tous les autres livrables du projet ANR BRIDGE

All the resources from the Dataverse Community Meeting 2023 held in Portugal, Braga at the University of Minho, 5-7 June 2023

Detail of the controlled vocabularies used by the Dataverse repositories of the ANR BRIDGE project members: CIRAD, INRAE and IRD at the beginning of the project.

This report presents some of the results from the Dataverse Community Survey 2022. The main goal of the survey was to help the Global Dataverse Community Consortium (GDCC; https://dataversecommunity.global/) and the Dataverse Project (https://dataverse.org/) decide on what actions to take to improve the Dataverse software and the larger ecosystem of integrated tools and services as well as better support community members. The results from the survey may also be of interest to other communities working on software and services for managing research data. The survey was designed to map out the current status as well as the roadmaps and priorities of Dataverse installations around the world. The main target group for participating in the survey were the people/teams responsible for operating Dataverse installations around the world. A secondary target group were people/teams at organizations that are planning to deploy or considering deploying a Dataverse installation. There were 34 existing and planned Dataverse installations participating in the survey.

Presentation on Decentralized Identifiers for theCLARIAH (Common Lab Research Infrastructure for the Arts and Humanities),a distributed research infrastructure for the humanities and social sciences.

The service for open research datasets Dataverse.no was established in 2017. Five years later, it holds some 1,300 datasets created by researchers at fourteen partner institutions. All submitted datasets are curated (checked) before they are published by curators at the various institutions. In addition, curators have established courses and webinars helping researchers make their datasets as FAIR as possible (FAIR = Findable, Accessible, Interoperable, Reusable). In this episode, Leif Longva and Philipp Conzett tell about how it has expanded, from a subject-specific archive called TROLLing (Tromsø Repository of Language and Linguistics) to the generic, CoreTrustSeal-certified service that we see today.

The presented Open Educational Resources help mitigate common problems that arise when scientific data is used for educational purposes: Often, finding, getting and analyzing data is a time-consuming task. To address this problem, we demonstrate how teachers and their students can use the methods to directly download data. Good analysis scripts begin with code that fetches the data from a repository. This contributes to making research reproducible and supports proper citation of research data. Two examples, one executable in Python, one in a local R installation, will show how to download datafiles from a Dataverse repository, and take first steps in analysing data.

DataverseNO (https://dataverse.no/) is a national, generic repository for open research data, owned and operated by UiT The Arctic University of Norway. The technical infrastructure of the repository is based on Dataverse, a community-driven open-source application, which is developed by an international developer and user community led by Harvard University. DataverseNO supports the FAIR Guiding Principles for scientific data management and stewardship, and is CoreTrustSeal certified (Conzett 2020). DataverseNO is based on collaboration between Norwegian research organizations. Datasets from partner institutions are published in institutional collections. Currently, 14 research organizations are partnering with DataverseNO. UiT is responsible for training and support for institutional collection managers, whereas the partner institutions are responsible for the curation of their institutional data and local user support. To ensure that data deposited into DataverseNO comply with the DataverseNO policies and guidelines they are curated by qualified research data service staff before they are published. The DataverseNO curators join forces in the DataverseNO curation network. Datasets in DataverseNO are equipped with persistent identifiers (DOIs, Digital Object Identifiers) at dataset and file level. DOIs serve as unique references to datasets and files and make them searchable in discovery services like B2FIND – EUDAT, Bielefeld Academic Search Engine (BASE), DataCite Search, Google Dataset Search, and Oria/Primo. On December 1, the last day of this year’s Munin Conference, DataverseNO will be turning 5 years!

Report describing the developed prototype of a use case of servicing metadata of social science data objects from the Lithuanian Data Archive for Humanities and Social Sciences Dataverse Repository to the Lithuanian Academic Electronic Library

Blueprint of a framework for harvesting and delivering for discovery rich metadata of social science data objects for the European Open Science Cloud (EOSC) Portal Service Catalogue.

Report on descriptors of data types in popular generic descriptors, most important distinct types of social science data objects, and most relevant metadata fields for discovering social science data objects.

Dans le cadre d'une démarche Qualité, ce guide technique documente 35 points de vérification et recommandations associées, destinés aux relecteurs ou curateurs des jeux de données (datasets) avant leur publication dans l'entrepôt DataSuds (https://dataverse.ird.fr). Entrepôt institutionnel de données scientifiques de l'IRD, DataSuds fonctionne grâce à l'application Dataverse. Le guide peut également être consulté par les déposants de données à la recherche de renseignements sur des points précis et afin d'aider à finaliser plus rapidement un jeu de données. Sous forme de tableau synthétique, le guide est divisé en 3 sections : "Métadonnées" (listées dans l'ordre du formulaire de saisie Dataverse), "Fichiers déposés" et "Conditions d’utilisation". Les principales lignes directrices sont le respect des principes FAIR, des principes Data Citation, la qualité éditoriale et les bons usages. La finalité des recommandations (comprendre le "Pourquoi") est précisée dans une colonne dédiée. Des conseils pratiques ainsi que des références vers des explications plus détaillées sont également fournis. En dernière page, une grille pratique (checklist) résume la liste des critères en une page, conçue pour être imprimée par les intervenants. Ce guide évolue au fil du temps, dans une approche d'amélioration continue. Certains conseils peuvent sembler évidents. Cependant tous reflètent nos observations, les cas réellement rencontrés durant la révision de 220 jeux de données. Ces éléments peuvent aussi être appliqués aux jeux de données destinés à être publiés dans d'autres entrepôts. Les critères de curation spécifiques à l'entrepôt DataSuds concernent principalement les types de données acceptés (cf. F1) et leur volume (F2). Contact : data@ird.fr ___________________________________________________________________________________________________________ Version 2.8 (février 2023) - Informations ajoutées (surlignées en jaune) dans les sections "Description", "Choix des fichiers", "Format des fichiers", "Attribution de licences". - Mise à disposition de la version Word du document afin de faciliter son réemploi (licence CC-BY-SA). Version 2.7 (décembre 2022) - Précisions, clarifications et reformulations. Une attention particulière est portée à la concision du guide, de sorte que le nombre de pages reste inchangé. Version 2.6 (août 2022) - Ajouts de quelques précisions. Version 2.5 (juillet 2022) - La grille (page 8) a été révisée en fonction de son expérience d'utilisation : une nouvelle colonne "Edité" aide à tracer les modifications apportées au jeu de données, afin de les rapporter ensuite au déposant ; une autre colonne est à présent destinée à répertorier les questions à poser au déposant., Licence CC-BY-SA

Met DataverseNL kunnen onderzoekers en docenten onderzoeksdata online opslaan, delen en registreren tijdens onderzoek en na afronding van het onderzoek. DataverseNL is een shared service van de deelnemende instellingen en DANS. DataverseNL gebruikt de Dataverse open source software ontwikkeld door de Universiteit van Harvard, wereldwijd gebruikt. Deze handleiding is primair bedoeld voor de DataverseNL beheerders van de aangesloten instellingen.

Presentazione nell'ambito del Workshop "Open Science e FAIR Data per le Neuroscienze, Dipartimento di Neuroscienze, Università di Torino,6-7-9-15 giugno 2022,Focus su Neuroscienze e Neuroimmagini, Computational Phenotyping ("phenomics"), Malattie Rare". La presentazione affronta le tematiche relative ad una corretta gestione e manutenzione delle strutture a supporto dei dati FAIR, elemento chiave perché il dato possa diventare linkable e machine readable, inserendosi nell’ambito delle infrastrutture già esistenti a livello Europeo (Elixir). In particolare, viene introdotta l’attività in corso presso il Dipartimento di Informatica per la realizzazione dell'infrastruttura a supporto dei Dati FAIR: infrastruttura di calcolo (HPC4AI), strumenti di supporto alla riproducibilità dei dati, sperimentazione di repository software (Dataverse)

Presentation on the flexible metadata schemes for the Dataverse Community Meeting 2022.

Interopérabilité des entrepôts •Plugin pour utiliser des listes contrôlées •Proxy sémantique •Harmonisation sémantique des vocabulaires : thématiques, Sujet, type de données&hellip

"Archive in a box" presentation for the Dataverse Community Meeting 2022, Harvard University.

Harvard Data Commons (HDC) is a university-wide initiative at Harvard University to support the lifecycle of research at Harvard. The goal of the HDC is to improve research data's integrity, provenance, and reproducibility. To accomplish this goal, the HDC team has been working on automating the flow of research data from research computing environments to management, publication, discovery, and preservation environments, leading to improved researcher experience. The project's initial phase builds a proof of concept or "Harvard Data Commons Minimum Viable Product (MVP)" to connect key systems in the research data lifecycle. In addition, the Harvard Dataverse repository provides a free platform for researchers inside and outside the Harvard community to share research data as a dataset or a dataverse collection (a collection of datasets). One of the main objectives of HDC is to improve the reproducibility of research data by supporting computational workflows on the Harvard Dataverse repository. In this lightning talk, we report our progress on enhancing the Harvard Dataverse repository to support FAIR (findability, accessibility, interoperability, and reusability) computational workflows and the challenges in this area. Considering a data-driven analysis lifecycle, researchers produce different products during the whole process. These products could be peer-reviewed journal publications, curated datasets, different kinds of plots, graphs and maps, or software. Researchers design computational workflows to compose and execute a series of analysis or data manipulation steps to produce these products. Researchers could define computational workflows using workflow-specific standards/languages such as Common Workflow Language (CWL) or defined in ad-hoc scripts and notebooks such as Python, shell script, Makefile, Jupyter Notebook, or R Notebook. We report on the challenges and progress of sharing computational workflows in the Harvard Dataverse repository from allowing workflow-specific search queries in the UI to incorporating adequate metadata and runtime environments. We also present our future plans for supporting the computational workflows beyond the MVP, which would include developments like automatic tests in Dataverse and integrations with third-party workflow tools. &nbsp

Apresenta os conceitos relacionados à certificação Core Trust Seal detalhando seus requisitos alinhados ao software Dataverse. Exemplifica como um repositório pode ser desenvolvido considerando melhores práticas de informações descritivas conforme a certificação CTS.&nbsp

We will present the Notify implementation that is currently proposed for the official adoption in DSpace. A technical introduction about the COAR Notify project [1] will be provided, showing how the use of the Linked Data Notification protocol [2], standard messages and patterns allow to integrate the repository with relevant services in a distributed, resilient and web-native architecture. The implementation has been made available as a patch for DSpace 5 and 6 in February 2022 and it is proposed for official inclusion in DSpace 7 [4, 5, 6]. This first implementation is based on the definition of a Minimum Viable Product reviewed with the COAR Notify Working Group, funded by U. Minho and developed by 4Science focused on the open peer-review scenarios. The Harvard University is currently updating their digital services and has adopted the Notify protocol to better integrate their DSpace Institution Repository with their Dataverse Data Repository. The Open Peer-review and IR – Data Repository integration scenarios will be demonstrated. [1] COAR Notify Project https://www.coar-repositories.org/notify/ [2] Linked Data Notification Protocol https://www.w3.org/TR/ldn/ [3] COAR Notify implementation website https://notify.coar-repositories.org/ [4] DSpace 5 patch, https://github.com/4Science/DSpace/tree/coar-notify-5 [5] DSpace 6 patch, https://github.com/4Science/DSpace/tree/coar-notify-6 [6] Proposal for inclusion in DSpace 7, https://github.com/DSpace/DSpace/issues/8120

24x7 talk presented at Open Repositories 2022 in Denver, Colorado (USA)

The Repository Rodeo returns for another round of questions and answers! This popular panel, featured since Open Repositories 2016 in Dublin, offers a broad overview of the main repository platforms at Open Repositories and provides an opportunity for spirited discussion amongst panelists and attendees. Join community representatives from Dataverse, DSpace, EPrints, Fedora, Haplo, Invenio, Islandora, and Samvera as we briefly explain what each of our repositories actually does. We'll also talk about the directions of our respective technical and community developments and related to the conference theme of "Building Trust Together", we’ll discuss the role of our repositories, and repository communities, in enabling trust, integration, collaboration, and sharing. This panel will be a great opportunity for newcomers to Open Repositories to get a crash course on the major repository options and meet representatives from each of their communities. After a brief presentation from each representative, we'll open the session up for questions from the audience.

International Open Access Week (OA Week) is a global event for disseminating and benefi ts of OA, sharing and gaining from experiences and motivating professionals and organizations to make OA a new norm in scholarship and research. It is the responsibility of the LIS professionals to support and strengthen the OA movement by advocacy and adoption. The present paper attempts to discuss the empirical ways and techniques through which authors, researchers, and academicians can derive the maximum benefi t of the OA literature independently and effortlessly. The tools discussed are useful and effective which may help empowering citizens foraying into a more equal knowledge society