Swedish National Data Service

Research e-infrastructures, digital archives, and data services have become important pillars of scientific enterprise that in recent decades have become ever more collaborative, distributed, and data intensive. The archaeological research community has been an early adopter of digital tools for data acquisition, organization, analysis, and presentation of research results of individual projects. However, the provision of e-infrastructure and services for data sharing, discovery, access, and (re)use have lagged behind. This situation is being addressed by ARIADNE, the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This EU-funded network has developed an e-infrastructure that enables data providers to register and provide access to their resources (datasets, collections) through the ARIADNE data portal, facilitating discovery, access, and other services across the integrated resources. This article describes the current landscape of data repositories and services for archaeologists in Europe, and the issues that make interoperability between them difficult to realize. The results of the ARIADNE surveys on users’ expectations and requirements are also presented. The main section of the article describes the architecture of the e-infrastructure, core services (data registration, discovery, and access), and various other extant or experimental services. The ongoing evaluation of the data integration and services is also discussed. Finally, the article summarizes lessons learned and outlines the prospects for the wider engagement of the archaeological research community in the sharing of data through ARIADNE.

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

The articles in this special issue demonstrate significant differences in digital archiving capacity in different countries. In part these reflect differences in the history of archaeology in each country, its relationship to the state, whether it is centralised or decentralised, state-led or commercially driven. They also reflect some of the different attitudes to archaeology across the world, most recently explored in a survey conducted under the auspices of the NEARCH project. They reflect a snapshot in time, but our aim is to record the current state-of-the-art in each country, to inform knowledge, stimulate discussion, and to provoke change.

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.

The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for clinicians, researchers, policy- and decision-makers, funders, publishers, public health experts, disaster preparedness and response experts, infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations), and other potential users. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.

The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.

In the past, data from archaeological investigations, as well as research projects led by universities have not been archived or made publicly accessible. Synthetic publications such as papers, reports and articles have been available, but not the underlying data files containing the original data to be reused or combined with new/other datasets for further research. Archaeological investigations are regulated within Sweden, but it has only recently been possible for that data to be preserved and disseminated in a more streamlined way. The mandatory requirement to archive research data at universities is often not enforced, resulting in a loss of data that is very problematic. This is now slowly changing owing to requirements from both governmental bodies and funding agencies, and therefore the future of archaeological data in Sweden looks a bit brighter.

This document is a deliverable (D16.4) of the ARIADNE project (“Advanced Research Infrastructure for Archaeological Dataset Networking in Europe”), which is funded under the European Community's Seventh Framework Programme. It presents the final results of the work carried out in Tasks 16.2 “Natural Language Processing (NLP)”. NLP is an interdisciplinary field of computer science, linguistics and artificial intelligence that uses many different techniques to explore the interaction between human (natural) and computer languages. The partners continued to focus on one of the most important, but traditionally difficult to access resources in archaeology; the largely unpublished reports generated by commercial or “rescue” archaeology, commonly known as “grey literature”, exploring both rule-based and machine learning NLP methods, the use of archaeological thesauri in NLP, and various Information Extraction (IE) methods in their own language. USW extended their English language rule based methods using the GATE toolkit for NER (Named Entity Recognition) to Dutch and Swedish language grey literature reports, in collaboration with LU and DANS (Dutch reports) and SND (Swedish reports). This made use of glossaries and thesauri from the partners, including the Dutch Rijksdienst Cultureel Erfgoed (RCE) Thesauri. The process of importing the thesauri resources into a specific framework (GATE), and the suitability and performance of the selected resources when used for the purposes of Named Entity Recognition (NER) were analysed. The NER techniques were focused on the general archaeological entities of Archaeological Context, Material, Physical Object (Finds), Monument, Place, and Temporal (Time Appellation). The methods proved capable of extracting CIDOC CRM element and in some case studies Getty Art and Architecture Thesaurus concepts, in addition to the native vocabularies. General archaeological NLP (GATE) pipelines for English, Dutch and Swedish have been developed. In addition experimental pipelines were developed for two exploratory thematic case studies on data integration, where the output is expressed as RDF Linked Data via a CRM based data model. An English language pipeline is available for a numismatic case study. English, Dutch and Swedish pipeline are available for a case study of item level data/NLP integration on a loose theme based around archaeological interest in wooden objects and their dating, as expressed in different kinds of datasets and reports. Both case studies have resulted in interactive demonstrators operating over the ARIADNE Linked Data Cloud. All 7 pipelines are freely available as open source ARIADNE outcomes. The Archaeology Data Service (ADS) at the University of York continued developing a machine learning-based NLP technique which has now been integrated it into a new metadata extraction web API, which takes previously unseen English language text as input, and identifies and classifies named entities within the text. The outputs can then be used to enrich resource discovery metadata for existing and future resources. This API can be incorporated into existing interfaces and used by archaeological practitioners to automatically generate metadata related to text-based content uploaded on a per-file basis, or by using batch creation of metadata for multiple files. This report presents the final results of the work carried out to date, and presents the issues to be addressed during the remainder of the ARIADNE Project

Formell publicering av forskningsdata är en central del i utvecklingen mot öppen vetenskap, oavsett om det gäller öppna data eller data med åtkomstbegränsningar. Samtidigt ska Sverige ha ställt om till öppna vetenskapspraktiker senast 2026. Sedan 2022 finns även lagkrav på svenska myndigheter att förteckna och offentliggöra information om alla data som publiceras. I vilken utsträckning forskningsdata faktiskt publiceras i Sverige är dock svårt att svara på – bland annat då det saknas effektiva metoder för att spåra och följa upp sådana publiceringar. Uppföljningen försvåras bland annat av brister i angivna metadata för organisationsaffilieringar och klassificering av material. Den kompliceras också av skillnader i rutiner för hur forskning redovisas lokalt och nationellt. För att uppnå bättre spårbarhet hos forskningsdatapubliceringar krävs förbättringar av såväl nationell samordning och teknisk infrastruktur som incitamentsstrukturer. Vi identifierar här några av de viktigaste hindren och pekar ut möjliga vägar framåt.

This deliverable describes the activities carried out within Work Package 15 (WP15) of theARIADNEplus project by the different partners and describes the results achieved. The work package consists of several individual tasks and subtasks with the overall goal to develop and provide useful services to archaeologists. This means the work package is by nature heterogeneous with stand-alone tasks and services. Efforts have been made to facilitate collaboration between the individual tasks through joint work package meetings. This has resulted in new cross-task contacts being made, and some sharing of expertise to improve services has been done. A service design template aligning the ARIADNEplus services with the requirements from European Open Science Cloud (EOSC) has been created. In connection with this, the ARIADNEplus AO-CAT ontology has been adapted to the requirements from EOSC Resource Data Model (Task 15.1). The Visual Media Service (Task 15.2.1) has had a new format added, allowing for 2D visualisation of LIDAR data in DEM format. In addition, three other standards have been added: gITF, ThreeJS and IIIF, supporting various functionality in the service. The service has also been adapted to support integration with the ARIADNEplus infrastructure in D4Science. A visual wizard has been defined to guide Visual Media Service users to add hotspots to a 3D scene easily and quickly. This extension, initially implemented in 3DHOP will allow archaeologists to create interactive links from the digital 3D model to the related documentation without writing any source code (Task 15.2.2). Task 15.2.3 reworked the Online 3D Database System for Endangered architectural and archaeological Heritage in the south Eastern MEditerRAnea area (EpHEMERA). EpHEMERA is a service provided by the Cyprus Institute to visualize in 3D archaeological excavations, ancient buildings, and their related documentation. In EpHEMERA, it is possible to visualise, online and through standard web browsers, 3D architectural and archaeological models (classified according to a specific type of risk), query the database system and retrieve metadata attached to each digital object, and extract geometric and morphological information about the Cultural Heritage asset. The visualisation and annotation tool of the TSS project have been ported to the OpenLime library and integrated into the Visual Media Service (Task 15.2.1). An additional layer of SVG annotations have been developed and added to the service. The Annotation service have been used and improved in three different pilot projects. (Task 15.3.2). Various strands of work have been done improving services for text mining and Natural Language Processing (Task 15.4). One of these efforts has been building upon the outcomes of the preceding ARIADNE project. A set of archaeological Named Entity Recognition NLP pipelines were reconfigured and deployed for easier use on the General Architecture for Text Engineering (GATE) cloud. Another effort has been on extracting temporal archaeological information using two different parallel approaches, normalisation and named entity recognition. A Python development platform has been used to unify the various services. A Vocabulary Annotation Tool (Task 15.3.1) was developed using the same platform, as part of Task 15.4. The tool facilitates the locating and tagging of vocabulary terms within free text and outputs suggested subject annotations in a range of formats. The GeoPortal service (Task 15.5) is a new REST service designed to manage complex spatio-temporal documents defined by metadata profiles. It was released as a component of the gCube framework. A prototype using the service was deployed and operated to manage archaeological excavation projects (Task 15.7). Two services for querying the RDF AO-Cat metadata records aggregated by the ARIADNEplus Infrastructure was established (Task 15.6): a full-text index service and a SPARQL endpoint. The full text index service is based on OpenSearch and supports the needed query functionality of the ARIADNEplus portal. The SPARQL endpoint allows performance of semantic queries on the RDF records within the ARIADNEplus data and knowledge cloud.

This deliverable describes the final results of Tasks 12.1, 12.2, 12.3 and 12.4 of the ARIADNEplus project. The tasks developed, delivered, and maintained the components of the ARIADNEplus infrastructure that support the integration and interoperability of the data provided by the members of the consortium and associate partners. The catalogue data integrated by the ADI (the Aggregative Data Infrastructure developed in T12.2) are transformed into RDF records compliant with the CRM-based ARIADNEplus Ontology (AO-Cat) and are made publicly available in the ARIADNEplus Knowledge Base (T12.1), where they are enriched and linked to the Getty AAT thesaurus and the PeriodO gazetteer of time periods. The knowledge base exposes a SPARQL endpoint and its content is indexed on an OpenSearch index that serves the ARIADNEplus portal (T12.3). The domains of mortuary archaeology, numismatics and epigraphies were chosen for deeper integration of item level data (T12.4) compliant with specific Application Profiles developed in WP4. A searching interface, built on the ResearchSpace platform provides support for research questions that require information richer than what is available in AO-Cat. The design, development and deployment activities have been guided by the requirements of all the members of the consortium, especially those involved in WP4, WP5 and the working group on portal requirements. The ARIADNEplus ADI features the following main components for data collection, transformation, and harmonisation: (i) the 3M Editor developed and maintained by FORTH, operated by CNR; (ii) the Vocabulary Matching Tool developed and maintained by USW, operated by CNR; and (iii) the ARIADNEplus aggregator developed, maintained, and operated by CNR. The knowledge base is implemented with GraphDB (free edition) and one Springboot application that acts as mediator for the interactions among the aggregator, GraphDB, and OpenSearch. As of October 2022, the KB contains 175M RDF triples describing 3M resources from 60K collections and 25 providers. Numbers are expected to increase by December 2022 with the aggregation of additional resources as planned in WP5. OpenSearch provides a full-text index of the content available in the knowledge base, to be used by the ARIADNEplus portal. The ARIADNEplus portal is developed using PHP, Vue.js, Javascript, Vuex, Tailwind, and Font Awesome. The portal provides standard free-text and faceted search options, but also advanced features based on the concepts of temporal, spatial, and topical coverage. In order to test the new functionality of the portal and enable data curators to check the quality of data before it is made available on the public portal, WP12 set up a staging environment accessible only to members of the consortium, where the collected data is aggregated, added to a staging knowledge base and indexed on a staging portal. Upon confirmation of data experts, data is then pushed to the production environment.

Rapporten är en sammanställning av arbetet i KAFFE-projektet 2025 (Kartläggning av förmågor inom forskningens e-infrastruktursystem), som bedrivits inom ramen för SND-nätverket i form av ett samarbete mellan SND-kontoret och nätverksmedlemmarna. Rapporten ger en strukturell jämförelse mellan hur utredningar och rapporter beskriver forskningsdatahantering som process och hur forskarna själva ser på arbetet med forskningsdata, och belyser diskrepansen mellan de två planen, vad gäller förväntningar men också i form av vilka begrepp som används. I anslutning till projektrapporten har SND:s styrgrupp tagit fram ett antal rekommendationer för det hur det fortsatta arbetet med forskningsdata kan organiseras, som läggs med som bilaga. The report presents a summary of the work in the 2025 KAFFE project (Sw. Kartläggning av förmågor inom forskningens e-infrastruktursystem, trans. Survey of capabilities within the research e-infrastructure system), a project run within the context of the Swedish National Data Service (SND) network. The report presents a structural comparison between how different public enquiries describe research data management as a process and how researchers view the work with research data, and highlights discrepancies between the two levels, in terms of expectations as well as concepts and terminology. In connection to the report the SND steering group has composed a number of recommendations for how the work with the research data can be organised going forward, here included as an appendix.

Rapporten är en sammanställning av arbetet i KAFFE-projektet 2025 (Kartläggning av förmågor inom forskningens e-infrastruktursystem), som bedrivits inom ramen för SND-nätverket i form av ett samarbete mellan SND-kontoret och nätverksmedlemmarna. Rapporten ger en strukturell jämförelse mellan hur utredningar och rapporter beskriver forskningsdatahantering som process och hur forskarna själva ser på arbetet med forskningsdata, och belyser diskrepansen mellan de två planen, vad gäller förväntningar men också i form av vilka begrepp som används. I anslutning till projektrapporten har SND:s styrgrupp tagit fram ett antal rekommendationer för det hur det fortsatta arbetet med forskningsdata kan organiseras, som läggs med som bilaga. The report presents a summary of the work in the 2025 KAFFE project (Sw. Kartläggning av förmågor inom forskningens e-infrastruktursystem, trans. Survey of capabilities within the research e-infrastructure system), a project run within the context of the Swedish National Data Service (SND) network. The report presents a structural comparison between how different public enquiries describe research data management as a process and how researchers view the work with research data, and highlights discrepancies between the two levels, in terms of expectations as well as concepts and terminology. In connection to the report the SND steering group has composed a number of recommendations for how the work with the research data can be organised going forward, here included as an appendix.

Detta är en beskrivning av Svensk nationell datatjänst (SND). Vad SND är, vad SND gör och inte gör. Det är ett levande dokument som uppdateras kontinuerligt allt eftersom SND utvecklas och utifrån de synpunkter som framkommer om vad som saknas eller bör förtydligas i dokumentet.Dokumentet ingår i SND:s dokumentsamling för DAU. Description of SND This is a description of The Swedish National Data Service (SND). What SND is and what SND does and does not do. It is a living document that is continuously updated as the SND develops, based on the views of what is missing or requires clarification within the document.This document is part of SND's collection of documents for DAU.

The SND Annual Report 2025 presents activities within the SND consortium and network, including national and international collaborations, training, communications, governance, and internal projects. It highlights the development of Researchdata.se, the KAFFE project, the ART<3DATA project, Openscience.se, flagship initiatives, and provides statistics and financial results for the year.

The SND Annual Report 2025 presents activities within the SND consortium and network, including national and international collaborations, training, communications, governance, and internal projects. It highlights the development of Researchdata.se, the KAFFE project, the ART<3DATA project, Openscience.se, flagship initiatives, and provides statistics and financial results for the year.

Overview In 2026, Swedish National Data Service was proud co-host of the course "Open Science in the Swedish Context 2026" in Gothenburg! This release contains an archived version of the course website. The course website contains links to view or download editable, re-useable versions of the presentations and other course materials. Background Helping researchers and research support staff to develop Open Science skills is at the heart of the work of SND and our co-hosts SciLifeLab and NBIS – National Bioinformatics Infrastructure Sweden. As national infrastructures, we share responsibility for ensuring that the Swedish research community has the knowledge and tools to work transparently, collaboratively, and in accordance with FAIR principles. The course brought together participants spanning all career stages and disciplines from across Sweden for four days of training covering the full Open Science landscape: from policy, principles and ideology, to data management, intellectual property, open publishing, open educational resources, citizen science, and science communication. SND is proud to promote a research culture where openness is not an afterthought, but a natural part of how science is done. Acknowledgements We are grateful to our knowledgeable panel of instructors from Swedish National Data Service, SOM-institutet, University of Gothenburg, NBIS – National Bioinformatics Infrastructure Sweden, Karolinska Institutet, SciLifeLab, and Lund University, for sharing their expertise and commitment!

Overview In 2026, Swedish National Data Service was proud co-host of the course "Open Science in the Swedish Context 2026" in Gothenburg! This release contains an archived version of the course website. The course website contains links to view or download editable, re-useable versions of the presentations and other course materials. Background Helping researchers and research support staff to develop Open Science skills is at the heart of the work of SND and our co-hosts SciLifeLab and NBIS – National Bioinformatics Infrastructure Sweden. As national infrastructures, we share responsibility for ensuring that the Swedish research community has the knowledge and tools to work transparently, collaboratively, and in accordance with FAIR principles. The course brought together participants spanning all career stages and disciplines from across Sweden for four days of training covering the full Open Science landscape: from policy, principles and ideology, to data management, intellectual property, open publishing, open educational resources, citizen science, and science communication. SND is proud to promote a research culture where openness is not an afterthought, but a natural part of how science is done. Acknowledgements We are grateful to our knowledgeable panel of instructors from Swedish National Data Service, SOM-institutet, University of Gothenburg, NBIS – National Bioinformatics Infrastructure Sweden, Karolinska Institutet, SciLifeLab, and Lund University, for sharing their expertise and commitment!

Rapporten är en sammanställning av arbetet i KAFFE-projektet 2025 (Kartläggning av förmågor inom forskningens e-infrastruktursystem), som bedrivits inom ramen för SND-nätverket i form av ett samarbete mellan SND-kontoret och nätverksmedlemmarna. Rapporten ger en strukturell jämförelse mellan hur utredningar och rapporter beskriver forskningsdatahantering som process och hur forskarna själva ser på arbetet med forskningsdata, och belyser diskrepansen mellan de två planen, vad gäller förväntningar men också i form av vilka begrepp som används. I anslutning till projektrapporten har SND:s styrgrupp tagit fram ett antal rekommendationer för det hur det fortsatta arbetet med forskningsdata kan organiseras, som läggs med som bilaga. The report presents a summary of the work in the 2025 KAFFE project (Sw. Kartläggning av förmågor inom forskningens e-infrastruktursystem, trans. Survey of capabilities within the research e-infrastructure system), a project run within the context of the Swedish National Data Service (SND) network. The report presents a structural comparison between how different public enquiries describe research data management as a process and how researchers view the work with research data, and highlights discrepancies between the two levels, in terms of expectations as well as concepts and terminology. In connection to the report the SND steering group has composed a number of recommendations for how the work with the research data can be organised going forward, here included as an appendix.