Proceedings of the Conference on Research Data Infrastructure最新文献

{"title":"Exchanging Research Data with SampleDB","authors":"Malte Deckers, Florian Rhiem","doi":"10.52825/cordi.v1i.362","DOIUrl":"https://doi.org/10.52825/cordi.v1i.362","url":null,"abstract":"Exchanging research data between systems is a vital task in research data management, especially in the context of collaborations. Therefore mapping data into standardized data descriptions and offering interfaces for efficient data exchange are required. The metadata database and electronic lab notebook SampleDB supports various ways of exporting data to other services, such as Dataverse, SciCat, and JupyterHub, as well as file exports in open formats. The concept of SampleDB federations allows data exchange in loosely coupled federations of SampleDB instances.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"103 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":"129301357","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":"Born-fair Data Projects Using Cookiecutter Templates","authors":"Felix Henninger","doi":"10.52825/cordi.v1i.331","DOIUrl":"https://doi.org/10.52825/cordi.v1i.331","url":null,"abstract":"Implementing research data management best practices and FAIR principles (Wilkinson et al., 2016) is vital for transparent, reproducible research, as well as efficient, sustainable science that avoids duplication of effort. Scientists can also benefit directly from incorporating data management into their data collection and analysis workflows. However, there is an initial cost to adoption that poses a burden and substantial barrier to entry even to well-intentioned researchers. In our experience in statistical and RDM-focused consulting, this cost increases as a project progresses, with a late-stage conversion being the most costly in terms of resources and energy because a working analysis needs to be adapted in one step. Therefore, we believe that it is useful to adopt best practices for data stewardship early-on in a project, and ideally from the get-go. \u0000In this contribution, we present a tool for creating and instantiating project templates that conform to good practices with regard to the data management and analysis projects more generally. In the same vein as \"born-open data\" (Rouder, 2016) where data is published immediately upon collection, our goal is to establish born-FAIR datasets that implement proven methods for data stewardship as early on in the research data lifecycle as is feasible. Our aim is to encourage researchers and analysts to incorporate best practices into their workflows from the onset by providing data and analysis templates that implement desirable properties. By adopting these templates, researchers immediately gain access to a number of tools that simplify their work and make it more efficient, while also providing a foundation for increased reproducibility, data documentation through codebooks, as well as metadata for long-term archival.Because a broad-strokes approach may not work in practice due to idiosyncrasies of individual research projects, one size may not fit all. For this reason, the templates contain customisation options that researchers can use to tailor the templates to their requirements. \u0000The templates build on the well-established cookiecutter library for the Python programming language (Greenfeld et al., 2022), which we additionally extend to R, a programming language somewhat more common among statisticians and social scientists, thereby creating a cross-platform infrastructure. Both libraries create a project skeleton with a pre-specified directory structure, and include configuration for commonly used tools. Upon template creation, a wizard guides users through a customisation step, allowing them to adapt templates to their needs and catering to the demands of a project at hand. \u0000Owing to the open-source nature of the project and the firmly established and well-documented standard, researchers can easily adapt templates and create their own, to accommodate their specific needs and domain requirements. We hope to foster a community of researchers who share and improve their workflows, and ant","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"72 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":"130254708","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":"Exploring and Improving Workflows for the Donation and Curation of Research Data","authors":"Natalie Kiesler, D. Schiffner","doi":"10.52825/cordi.v1i.284","DOIUrl":"https://doi.org/10.52825/cordi.v1i.284","url":null,"abstract":"Managing research data and preparing it for long term archiving at a research data center is a time-consuming, repetitive and error prone process without obvious rewards or incentives. To address these challenges, we aim at the integration of a standard data management tool into one of the research data centers of the German Network of Educational Research Data. The goal is to improve workflows for both, data donors and curators and to explore transferable solutions that allow researchers and curators to work on the same platform when entering and editing metadata.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"51 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":"126790733","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":"Research Data Management Curriculum of the Research Data Services at the University Library Duisburg-Essen","authors":"Sophia Leimer, Sonja Hendriks, Lisa Korte, Jessica Stegemann, Sarah Ann Stock, Henning Timm, Stephanie Rehwald","doi":"10.52825/cordi.v1i.209","DOIUrl":"https://doi.org/10.52825/cordi.v1i.209","url":null,"abstract":"Reproducible and transparent science requires good research data management (RDM). However, researchers are often not familiar with how to appropriately handle research data, publication options, legal aspects, and the multitude of available software tools. To support scientists at the University of Duisburg-Essen in gaining RDM knowledge and competencies, the Research Data Services developed a structured teaching program – the RDM Curriculum – for researchers from different disciplines and career levels. \u0000The RDM Curriculum is separated into a basic and an advanced module. In the basic module, participants can select from three full-day courses that address the basics of RDM with different disciplinary focus. The advanced module consists of various 2 hour online hands-on courses on diverse RDM topics and tools. As incentive to attend multiple courses, participants can earn the RDM Badge of the University Library Duisburg-Essen. The curriculum program is complemented by specialized RDM courses and self-learning materials. \u0000With the RDM Curriculum, we created an easily accessible and individually selectable RDM course offer that enables researchers to gain discipline-specific and individually relevant RDM knowledge. The curriculum structure can gradually be expanded to further target groups (e.g. students) and allows for continuously adding new contents in the advanced module. The high request for the RDM Badge after the first iteration of the RDM Curriculum in the winter semester 2022/2023 confirmed the positive effect of incentives. Consequently, we are planning to establish a Data Champion Award as appreciation of RDM achievements and to showcase best-practice examples at the University of Duisburg-Essen.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"26 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":"126557403","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":"Improving the Research Desktop Experience for OpenStack VDI Integrating Hardware Accelerated Rendering and Remote Transport","authors":"Dirk von Suchodoletz, Yi Sun, J. Hériché, Manuel Messner","doi":"10.52825/cordi.v1i.413","DOIUrl":"https://doi.org/10.52825/cordi.v1i.413","url":null,"abstract":"Using virtual machines with dedicated rendering and remote access capabilities, virtual workplaces for various usecases can be created, and then accessed from anywhere at any time. If this is to happen on a large scale in the cloud, so-called VDI for the dynamic provision of virtual desktops play an increasingly important role. A sustainable VDI should be freely available to everyone for modification and redistribution at no cost, be scalable, and should support various desktop use cases with different resource requirements. Some use cases involve hundreds of similar VM running in parallel, which requires proper resource planning.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"177 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":"122312984","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":"Long Term Interoperability of Distributed Research Data Infrastructures","authors":"Marius Politze, Yusra Shakeel, Siream Hunke, Philipp Ost, Rossella Aversa, Benedikt Heinrichs, Ilona Lang","doi":"10.52825/cordi.v1i.348","DOIUrl":"https://doi.org/10.52825/cordi.v1i.348","url":null,"abstract":"Research institutions have established a variety of research data infrastructures that orient towards discipline or methodology specific needs of their respective research community. Technically, these infrastructures ultimately are based on “off-the-shelf” hardware and software building blocks – both commercial and open-source. While such “enterprise ready” infrastructures can scale well, they apt to data silos and typically do not adhere to scientific standards like the FAIR (Findability, Accessibility, Interoperability, Reusability) principles out of the box. Using common architecture concepts such as the FAIR Digital Object (FAIR DO) allows interconnection of these silos by adding a long term interoperability layer on top of the existing infrastructure components. \u0000The presented approach provides a practical solution for interconnecting distributed research data infrastructures to national (like NFDI) and international (like EOSC and Gaia-X) infrastructures and preventing the creation of data silos. By allowing existing data infrastructures to make data FAIR, we enable researchers to access and reuse data from different domains, facilitating cross-disciplinary research and advancing new methods for scientific discoveries.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"18 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":"128129548","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 DAPHNE4NFDI and PUNCH4NFDI Consortia in the NFDI","authors":"Lisa Amelung, Anton Barty, Bridget Murphy, Christiane Schneide, Astrid Schneidewind, Thomas Schoerner","doi":"10.52825/cordi.v1i.293","DOIUrl":"https://doi.org/10.52825/cordi.v1i.293","url":null,"abstract":"The DAPHNE4NFDI and PUNCH4NFDI consortia represent the large scale facilities in the German physical sciences community. Work in DAPHNE4NFDI and PUNCH4NFDI is characterised by the use of large-scale research infrastructures – reactors, light sources, accelerators, telescopes, observatories, satellites – that serve international research communities of up to several thousand users and produce data in the terrabyte, often petabyte and in future exabyte range. The communities will have to master massive challenges in data management, building on and extending their leadership in “big data” management, distributed computing, multi-user management, and data loss / data irreversibility issues.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"43 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":"128220138","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":"A Survey on the Current Status of Research Data Management in Mecklenburg-Vorpommern Preliminary Results for a Questionnaire Study Among Researchers","authors":"Max Schröder, Sascha Genehr, Rüdiger Köhling, Stefan Schmidt, Ralf Schneider, Sascha Spors, G. Szepannek, Dagmar Waltemath, Frank Krüger","doi":"10.52825/cordi.v1i.303","DOIUrl":"https://doi.org/10.52825/cordi.v1i.303","url":null,"abstract":"High quality research data management (RDM) is essential to support state of the art comprehensible and reproducible research processes and, thus, foster the sustainable production of novel and trustworthy research findings. While there are lots of national and international initiatives supporting researchers in all respects of RDM, the local infrastructures provide the foundation for these concepts. In this contribution, we present preliminary results of a study that collects the requirements of researchers on these local infrastructures in all seven higher education research institutions in Mecklenburg-Vorpommern (MV).\u0000 ","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"47 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":"128500273","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":"Connecting National and International Data Infrastructures in Biodiversity Research The Case of NFDI4Biodiversity, a German Consortium for Biodiversity, Ecology and Environmental Data","authors":"Barbara Ebert, Judith Sophie Engel, Ivaylo Kostadinov, Anton Güntsch, F. Glöckner","doi":"10.52825/cordi.v1i.346","DOIUrl":"https://doi.org/10.52825/cordi.v1i.346","url":null,"abstract":"NFDI4Biodiversity is a consortium within the German National Research Data Infrastructure (NFDI) dedicated to data and services for biodiversity research and ecology. In the domain, well-developed international networks exist, with quite mature tools and data standards. These are used and disseminated in the NFDI4Biodiversity project in order to mobilise and publish data collected by national stakeholders according to the FAIR Guiding Principles for scientific data management and stewardship.The consortium partners provide methods and tools for archiving, publishing, searching and analysing data that are suitable for everyday use and have been tried and tested in practice. The consortium also functions as a forum for technical and legal matters of data and data-related workflows. In this way, the consortium is providing added value to the community regarding access to modern technologies and a comprehensive stock of biodiversity and environmental data.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"1 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":"134235122","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":"Ontology-Based Laboratory Data Acquisition With EnzymeML for Process Simulation of Biocatalytic Reactors","authors":"Alexander S. Behr, Elnaz Abbaspour, Katrin Rosenthal, Jürgen Pleiss, Norbert Kockmann","doi":"10.52825/cordi.v1i.324","DOIUrl":"https://doi.org/10.52825/cordi.v1i.324","url":null,"abstract":"The presented work explores the use of ontologies and standardized enzymatic data to set up enzymatic reactions in process simulators, such as DWSIM. Setting up an automated workflow to start a process simulation based on enzymatic data obtained from the laboratory can help save costs and time during the development phase. Standardized conditions are crucial for accurate comparison and analysis of enzymatic data, where ontologies provide a standardized vocabulary and semantic relations between relevant concepts. To ensure standardized data, an electronic lab notebook (ELN) is used based on EnzymeML, an open standard XML-based format for enzyme kinetics data. Furthermore, two ontologies are merged and the result is extended for the use in the Python-based workflow. The resulting data is stored in a knowledge graph for research data in a machine-accessible and human-readable format. Thus, the study demonstrates a workflow that allows for the direct translation of ELN data into a process simulation via ontologies.","PeriodicalId":359879,"journal":{"name":"Proceedings of the Conference on Research Data Infrastructure","volume":"375 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":"131870354","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}