Proceedings of the Conference on Research Data Infrastructure最新文献

{"title":"Which FAIR are you? A Detailed Comparison of Existing FAIR Metrics in the Context of Research Data Management","authors":"Mario Moser, Jonas Werheid, Tobias Hamann, Anas Abdelrazeq, Robert H. Schmitt","doi":"10.52825/cordi.v1i.401","DOIUrl":"https://doi.org/10.52825/cordi.v1i.401","url":null,"abstract":"In data management the high-level FAIR principles are interpreted and implemented in various FAIR metrics. While this specific interpretation is intended, it leads to the situation of several metrics with different evaluation results for the same digital object. This work conducts an organizational-formal comparison, showing up elements like categories of importance in the considered metrics, as well as a content-wise comparison of selected metrics how their differ in their interpretation. The results give orientation especially to everyone in science aiming to find the right metric to make their data FAIR.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121364457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spreading the Love for Mathematical Research Data","authors":"Tabea Bacher, Christiane Görgen, Tabea Krause, Andreas Matt, Daniel Ramos-Castro, Bianca Violet","doi":"10.52825/cordi.v1i.369","DOIUrl":"https://doi.org/10.52825/cordi.v1i.369","url":null,"abstract":"The Mathematical Research Data Initiative (MaRDI) is the NFDI consortium for the mathematics community. We outline some of the challenges we face in spreading a culture of mathematical research data to a large community and starting a cultural change. We highlight our approach to tackling these challenges and present some successful activities: a colorful newsletter, personal interviews, an entertaining rabbit, FAIR chocolate, and interactive formats.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122835725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Landscape of Ontologies for Catalysis Research Data Management","authors":"Alexander S. Behr, Hendrik Borgelt, Taras Petrenko, Mark Dörr, Norbert Kockmann","doi":"10.52825/cordi.v1i.232","DOIUrl":"https://doi.org/10.52825/cordi.v1i.232","url":null,"abstract":"This work provides a survey of ontologies for catalysis research to improve the findability, accessibility, interoperability, and reusability (FAIRness) of research data. Applying tools that are commonly used by lab scientists, ontologies relevant to catalysis research are classified in a simple, well formatted spreadsheet template (Excel). This enables a scientist and domain expert without programming skills to evaluate a certain ontology. The entries of this template are then processed and visualized through automated creation of markdown files on GitHub using Python scripts. Furthermore, ontology mapping by searching for similar pairs of classes across different ontologies is performed, using the outcome of the ontology classification. This work contributes to the development of ontologies for catalysis research, facilitating better data integration and knowledge sharing while reusing existing semantic artefacts.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128450820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Federal State Initiatives for RDM as Intermediaries in a Dynamic Landscape of RDM Infrastructures and Services","authors":"Ortrun Brand, Karen Bruhn, M. Cyra, Matthias Fingerhuth, Roman Gerlach, Boris Jacob, Cora Krömer, Ralph Müller-Pfefferkorn, Heike Neuroth, Thilo Paul-Stüve, Stephanie Rehwald, Janine Straka, Barbara Weiner","doi":"10.52825/cordi.v1i.242","DOIUrl":"https://doi.org/10.52825/cordi.v1i.242","url":null,"abstract":"A number of German federal states have established initiatives to support the institutionalization of RDM infrastructures and services. They can serve as intermediaries between disciplinary approaches to RDM like NFDI and RDM services in individual research institutions. This presentation gives an overview of the current state of these initiatives and provides an outlook on their role in creating synergies in RDM with a focus on their integrating potential for NFDI.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126518186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The RDM System LARA - Semantics Through Automation From Bottom Up","authors":"Mark Doerr, Stefan T. Maak, Marian J. Menke, U. Bornscheuer","doi":"10.52825/cordi.v1i.359","DOIUrl":"https://doi.org/10.52825/cordi.v1i.359","url":null,"abstract":"LARAsuite (https://gitlab.com/larasuite) is a free and open source research data management system that addresses the problematic of manual data insertion and metadata assignment into the corresponding databases by a radically automated processes. Data and Metadata is mainly not inserted by humans, but by the machines producing the data and automatically transferring this generated data and metadata to the LARA RDM system. This data transfer is achieved through the intensive utilisation of the free and open lab-automation standard SiLA (Standardisa- tion in Labautomation) (https://sila-standard.org), combined with a simple to note process description language (pythonLab) and orchestration, scheduling, data aggre- gation and evaluation. Many LARA instances can be selectively synchronised to form a decentralised network of data infrastructures across labs and institutions. Research data and meta-data can be queried by a SPARQL endpoint. As the LARAsuite comes close to an ideal FAIR-principles based RDM System1, is generic to the most common natural science applications, is open source (python based), modular and easy deploy- able, it can be used to showcase NFDI goals for a wide range of scientists","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114368887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Terminologies in RDM for Engineering - a Service Approach NFDI4Ing Terminology Service","authors":"Angelina Kraft, Felix Engel, Axel Klinger","doi":"10.52825/cordi.v1i.207","DOIUrl":"https://doi.org/10.52825/cordi.v1i.207","url":null,"abstract":"The frameworks which have been established since the start of the NFDI allow for a coordinated development of RDM services, which include the introduction of community specific Terminology Services. To address the challenge of alignment and re-use of established ontologies and terminologies in the engineering domain, a Terminology Service (TS) was set-up for the NFDI4Ing initiative: https://terminology.nfdi4ing.de. The NFDI4Ing TS provides a single point of access to relevant research concepts and offers the building blocks for (meta-) data schemata and data annotation. As an open source platform, it features more than 50 ontologies, 147,000 terms and over 5,800 properties from a range of engineering-related terminology collections. The use of the NFDI4Ing TS fosters interoperability and reuse in a FAIR data context.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114447901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The German Human Genome-Phenome Archive in an International Context: Toward a Federated Infrastructure for Managing and Analyzing Genomics and Health Data","authors":"Luiz Gadelha, Jan Eufinger","doi":"10.52825/cordi.v1i.394","DOIUrl":"https://doi.org/10.52825/cordi.v1i.394","url":null,"abstract":"With increasing numbers of human omics data, there is an urgent need for adequate resources for data sharing while also standardizing and harmonizing data processing. As part of the National Research Data Infrastructure (NFDI), the German Human Genome-Phenome Archive (GHGA) strives to connect the data from German researchers and their institutions to the international landscape of genome research. To achieve this, GHGA partners up with international activities such as the federated European Genome-Phenome Archive (EGA) [1] and the recently funded European Genomic Data Infrastructure (GDI) project to enable participation in international studies while ensuring at the same time the proper protection of the sensitive patient data included in GHGA.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124228845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Reproducibility in Research Through FAIR Digital Objects","authors":"Zeyd Boukhers, Leyla Jael Castro","doi":"10.52825/cordi.v1i.406","DOIUrl":"https://doi.org/10.52825/cordi.v1i.406","url":null,"abstract":"The FAIR principles were introduced to enhance data reuse by providing guidelines for effective data management practices. In the broader context of research, assets encompass not only data but also artifacts such as code, software, and publications. FAIRifying these artifacts is as essential as FAIRifying data, given the increasing complexity of current AI approaches that make reproducibility extremely challenging. Therefore, the reuse of these artifacts is growing in importance. The concept of FAIR Digital Objects (FDOs) presents a solution to FAIRify these artifacts, treating them as FDOs. NFDI4DataScience is embracing FDOs and proposing an architecture to efficiently manage them.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123667673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed Privacy-Preserving Data Analysis in NFDI4Health With the Personal Health Train","authors":"Yongli Mou, Feifei Li, Sven Weber, Sabith Haneef, Hans Meine, Liliana Caldeira, Mehrshad Jaberansary, Sascha Welten, Yeliz Yediel Ucer, Guido Prause, Stefan Decker, O. Beyan, Toralf Kirsten","doi":"10.52825/cordi.v1i.282","DOIUrl":"https://doi.org/10.52825/cordi.v1i.282","url":null,"abstract":"Data sharing is often met with resistance in medicine and healthcare, due to the sensitive nature and heterogeneous characteristics of health data. The lack of standardization and semantics further exacerbate the problems of data fragments and data silos, which makes data analytics challenging. NFDI4Health aims to develop a data infrastructure for personalized medicine and health research and to make data generated in clinical trials, epidemiological, and public health studies FAIR (Findable, Accessible, Interoperable, and Reusable). Since this research data infrastructure is distributed over various partners contributing to their data, the Personal Health Train (PHT) complements this infrastructure by providing a required analytics infrastructure considering the distribution of data collections. Our research have demonstrated the capability of conducting data analysis on sensitive data in various formats distributed across multiple institutions and shown great potential to facilitate medical and health research.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122858414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"NFDI4Energy Case-Study: Comparative Analysis and Visualisation of Long-Term Energy System Scenarios","authors":"Mirko Schäfer, Ramiz Qussous, Ludwig Hülk, Johan Lilliestam, Anke Weidlich","doi":"10.52825/cordi.v1i.294","DOIUrl":"https://doi.org/10.52825/cordi.v1i.294","url":null,"abstract":"Analysis and comparison of energy system scenarios provide valuable insights into potential transformation pathways. These studies on long-term developments can serve as new inputs for scientific research and decision-making processes, providing policymakers and other stakeholders with the necessary guidance to achieve sustainable energy systems. Generally, such scenarios are derived from energy system models which often seek a cost-optimal system design under a variety of boundary conditions, ranging from technical constraints to limits of land availability or a cap on overall greenhouse gas emissions [1]. For Germany, several larger energy system scenario studies have been published, addressing the goal of carbon neutrality in 2045 as prescribed in the German climate protection act [2]. These studies show differences in their specific methodology, sector representation, parameter settings or, more generally, overall scenario narratives. This diversity represents a challenge regarding the comparability of these studies, and consequently the ability to identify consensus and controversies in their findings. Often only limited access to data for parameter settings and scenario results is provided. Almost always the data is presented in different detail and formats, thus imposing further barriers for comparison and usability for the scientific community [3].\u0000As one of the three use cases applied in Task Area 6 of the NFDI4Energy research project, we aim to address this challenge by providing transparent and open comparative information and data on long-term energy system scenarios. Selected scenarios for the transition towards a climate-neutral Germany will be annotated with terms form the Open Energy Ontology (OEO) [4]. The comparison is building on an already existing database infrastructure from the Open Energy Platform (OEP) [5]. Existing concepts for qualitative and quantitative comparisons will be used and improved to cover a wide range of existing energy system studies.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"60 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123393346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}