bluuebunny/crossref_metadata_2025 huggingface dataset:
Establishing Adaptive Governance in NFDI Consortia:
Authors: Apondo Eric , Züger Andrea , Bruns Andreas , Mehlis Katja , Schickhardt Christoph , Winkler Eva
Published: September 2023

There is widespread support for patient and public involvement (PPI) as an ethical requirement in biomedical research and policy development [1, 2], including research using personal health data, such as genomic data [3]. Sharing genomic and other personal health data is important for progress in health research [4], but poses ethical, legal and societal challenges for the governance of research and the institutions that conduct and support it. These challenges arise in part from the varied interests of the stakeholders involved, including patients, researchers, and funders [5]. In recent years, there has been a rise in collaborations between research institutions that conduct joint research programs. In these research consortia, the objectives and stakeholders in research are multiplied and more varied, making governance even more complex  [6].  There has been debate about strengths and weaknesses of different forms of governance of research, with proponents of adaptive governance highlighting its responsiveness and flexibility to evolving goals and needs of stakeholders [5, 7]. However, there are no set standards for involving patients in the governance of health research. Moreover, as it is a highly context-specific process, cultural, legal and social contexts of the individual institutions or consortia must be considered.
Within the German National Research Data Infrastructure (NFDI), there are consortia supporting research with personal health data, one of which is the German Human Genome-Phenome Archive (GHGA) [8]. We describe GHGA’s PaGODA Project (Patient Involvement in the Governance of an Omics Data Archive), whose goals are to gather patients’ views for their involvement in the governance of GHGA by conducting deliberative forums, and to implement these views. We focus here on the process of translating the findings from the forums into the GHGA governance policy, and identify procedural factors that were important for the process.
The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI
Authors: Rossenova Lozana , Schubotz Moritz , Shigapov Renat
Published: September 2023

The Strategic Research and Innovation Agenda (SRIA) of the European Commission identifies Knowledge Graphs (KGs) as one of the most important technologies for building an interoperability framework and enabling data exchange among users across countries, sectors, and disciplines [1]. KG is a graph-structured knowledge base containing a terminology (vocabulary or ontology) and data entities interrelated via the terminology [2]. KGs are based on semantic web technologies (RDF, SPARQL, etc.) and often used for agile data integration. KGs also play an essential role within Germany as a vehicle to connect research data and research-related entities and make those accessible – examples include the GESIS Knowledge Graph Infrastructure, TIB Open Research Knowledge Graph, and GND.network. Furthermore, the Wikidata knowledge graph, maintained by Wikimedia Germany, contains a large number of research-related entities and is widely used in scientific knowledge management in addition to being an important advocacy tool for open data [3]. Extending domain-specific ontology-supported KGs with the multidisciplinary, crowdsourced knowledge in Wikidata KG would enable significant applications. The linking between expert knowledge systems and world knowledge empowers lay persons to benefit from high-quality research data and ultimately contributes to increasing confidence in scientific research in society.
Transparency and Involvement of the Energy-Related Industry in a Data Sharing Platform
Authors: Pan Zhiyu , Gürses-Tran Gonca , Speck Christina , Jaquart Patrick , Niebisch Michael , Monti Antonello
Published: September 2023

The integration of renewable energy sources, the decentralization of the energy system, and the increasing digitization of energy-related processes require the integration of a wide range of energy-related data. In this context, a data sharing platform can serve as a hub for exchanging energy-related data and developing innovative solutions to improve the efficiency and sustainability of the energy system. However, especially because of the involvement of the energy-related industry in such a platform poses several challenges related to data protection, intellectual property, and business interests. This paper presents a framework for ensuring transparency and involvement of the energy-related industry in a data sharing platform, based on the FAIR data principles and a co-creation approach involving industry partners.
Pathways Between National and European Research Infrastructures: A Humanities’ Perspective
Authors: Rißler-Pipka Nanette , Stein Regine , Barbot Laure , Chambers Sally , Tasovac Toma , Wieder Philipp
Published: September 2023

In this poster we will discuss challenges, requirements and good practices for creating synergies and inter-connections between national and international research and research data infrastructures from the perspective of the humanities. Stakeholders of the NFDI consortium Text+, of the German national node of DARIAH, of the SSH Open Cluster and of related EOSC projects are presenting benefits and outcomes of these structures and their linkages for the actual research data management and for the researchers. How are research data repositories connected and researchers guided to all the various service offers? With an example about the tool registry in the SSH Open Marketplace reused by Text+ and connected to EOSC, we illustrate the overall picture of these infrastructures and their impact in practice.
Architectural Design of BERD Information Portal
Authors: Saleh Ahmed , Tochtermann Klaus
Published: September 2023

The management of Business, Economic, and Related Data can be a complex task involving various types of data and diverse research needs. BERD@NFDI develops a powerful platform to collect, process, analyze, and preserve such data in one place.
Overarching Data Management Ecosystem at HZDR
Authors: Knodel Oliver , Gruber Thomas , Kelling Jeffrey , Lokamani Mani , Müller Stefan , Pape David , Voigt Martin , Juckeland Guido
Published: September 2023

When dealing with research data management, researchers at Helmholtz- Zentrum Dresden – Rossendorf (HZDR) face a variety of systems and tools. These range from the project planning phase (proposal management, data management plans and policies), over documentation during the experiment or simulation campaign, to the publication (collaborative authoring tools, metadata catalogs, publication systems, data repositories). In addition, modern research projects usually are required to interact with a variety of software stacks and workflow management systems to allow comprehensi- ble and FAIR science on the underlying IT infrastructure (HPC, data storage, network file systems, archival). This article first demonstrates the data management systems and services provided at HZDR, followed by an overview of a self-developed guidance system. It is concluded by a real-world example.
Machine-Actionable Metadata for Software and Software Management Plans for NFDI
Authors: Giraldo Olga , Dessi Danilo , Dietze Stefan , Rebholz-Schuhmann Dietrich , Castro Leyla Jael
Published: September 2023

Research data is on its way to be recognized as a first-class citizen in research; however, and despite its importance for science, software still has a long way to go. Recent initiatives are paving the way, including FAIR for Research Software and Software Management Plans. A step further towards machine-actionability is adding a structured metadata layer. Here we discuss some metadata elements useful to represent software and integrate it into management plans, and how it could be of benefit for NFDI.
Schema.org as a Lightweight Harmonization Approach for NFDI
Authors: Castro Leyla Jael , Fluck Juliane , Arend Daniel , Lange Matthias , Martini Daniel , Neumann Steffen , Schimmler Sonja , Rebholz-Schuhmann Dietrich
Published: September 2023

Schema.org is a controlled vocabulary that makes it easier for web pages to describe their actual content in a semantic, structured and machine-processable way. It is recognized by major search engines and data aggregators, making it easier for researchers to expose metadata describing their research outcomes. Here we present how Schema.org is used (or planned to be) by some NFDI consortia, becoming a lightweight approach to harmonize digital objects coming from different sources so they can be connected to each other in a meaningful way
Distributed Privacy-Preserving Data Analysis in NFDI4Health With the Personal Health Train
Authors: Mou Yongli , Li Feifei , Weber Sven , Haneef Sabith , Meine Hans , Caldeira Liliana , Jaberansary Mehrshad , Welten Sascha , Yediel Ucer Yeliz , Prause Guido , Decker Stefan , Beyan Oya , Kirsten Toralf
Published: September 2023

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.
Zarr
Authors: Moore Josh , Kunis Susanne
Published: September 2023

For decades, the sharing of large N-dimensional datasets has posed issues across multiple domains. Interactively accessing terabyte-scale data has previously required significant server resources to properly prepare cropped or down-sampled representations on the fly. Now, a cloud-native chunked format easing this burden has been adopted in the bioimaging domain for standardization. The format — Zarr — is potentially of interest for other consortia and sections of NFDI.
Isn’t a Number and a URL Enough?
Authors: Hagemann-Wilholt Stephanie , Schrader Antonia C. , Czerniak Andreas
Published: September 2023

Persistent identifiers (PIDs) are an integral part of research data management and can be found throughout the entire lifecycle of research data. However, their ability to function – to ensure persistence – depends on numerous factors: technical infrastructure, international standards and best practices and their dissemination, agreements on long-term governance of infrastructures, etc. Their applicability is diverse and requires adaptation to the resources and entities referenced by them. The paper describes two projects – PID4NFDI and PID Network Germany – that aim to address these challenges.
NFDI4Energy Case-Study: Comparative Analysis and Visualisation of Long-Term Energy System Scenarios
Authors: Schäfer Mirko , Qussous Ramiz , Hülk Ludwig , Lilliestam Johan , Weidlich Anke
Published: September 2023

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].
As 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.
Open Science Best Practices in Data Science and Artificial Intelligence
Authors: Borisova Ekaterina , Abu Ahmad Raia , Rehm Georg
Published: September 2023

In the past years, scientific research in Data Science and Artificial Intelligence has witnessed vast progress. The number of published papers and digital objects (data, code, models) is growing exponentially. However, not all of these research artifacts are findable, accessible, interoperable and reusable (FAIR), contributing to a rather low level of reproducibility of the experimental findings reported in scholarly publications (reproducibility crisis). In this paper, we focus on Data Science and Artificial Intelligence Open Science best practices, i.e., a set of recommendations that eventually contribute to the management and development of digital artefacts that are as FAIR as possible. While several guidelines exist, we add best practices for the FAIR collection, processing, storing and sharing of scholarly findings via Research Knowledge Graphs. The final list of recommendations will be openly available on the NFDI4DS webpage as an interactive web application.
Linked Open Research Data for Social Science
Authors: Siegers Pascal , May Antonia , Saalbach Claudia , Nebelin Jana , Kern Dagmar , Daniel Andreas , Zapilko Ben , Momeni Fakhri , Wenzig Knut , Goebel Jan
Published: September 2023

The re-use of research data is an integral part of research practice in the social and economic sciences. To find relevant data, researchers need adequate search facilities. However, a comprehensive, thematic search for research data is made more difficult by inconsistent or missing semantic indexing of data at the level of social science concepts (e.g., representing the theory language). Either the data is not documented at a granular level, or primary investigators use their ad-hoc terminology to describe their data. Consequently, researchers have to make great efforts to find relevant or comparable data. From the user's perspective, the lack of theory language in data documentation impedes effective data searches and thus significantly limits the research potential of existing data collections. Because there is currently no semantic model for indexing the data content, the specific challenge for improving data search lies in establishing concept-based indexing of research data. Research infrastructures need technology for the harmonized semantic indexing of their research data. The LORD concept registry aims at closing this gap by developing a registry of sociological and economic concepts and, following the FAIR principles, making this concept registry generally available to the scientific community. As a first step, we developed a basic data model for the Concept Registry using United Modeling Language (UML). All links between are created and managed in the form of so-called RDF triples. An annotation application allows for linking specific questions/variables to concepts. The application also includes the two SKOS-compliant thesauri, "Thesaurus Social Sciences" (TheSoz) and "Standard Thesaurus Economics" (STW) but could be extended to other resources like ELSST.
We illustrate the application of the LORD concept registry with examples from three large-scale survey programmes (German Socio-Economic Panel, German General Social Survey, National Academics Panel Study). The initial focus is on variables and questions with overlapping content in the three survey programmes, as they form a sound basis for cross-linking with concepts.
RSpace + iRODS
Authors: Macneil Rory , Russell Terrell
Published: September 2023

Research infrastructures enabling scalable sharing of data are proliferating, at the institutional, project/consortium and national/international levels.  Many of these are domain-specific, but there also is a growing focus on Research Commons that enable general data sharing across domains.  Examples include the EUDAT Collaborative Data Infrastructure in Europe, the Gakunin RDM platform in Japan, and the Research Commons planned by Canada’s Digital Research Alliance (DRA).
In some cases, such as Gakunin RDM, Research Commons are architected as an integrated set of complementary services, but in most existing and planned Research Commons a disparate set of unconnected services is offered.  This paper describes the integration between RSpace, an active content management digital research platform, and iRODS, a policy-driven data management platform, and explains how it is designed to serve as a flexible connecting component that ties together other services that make up a Research Commons.
The paper discusses how, by tying together otherwise unconnected services, inclusion of RSpace + iRODS in Research Commons enables streamlined flows of data and metadata between services, enhancing FAIR principles.  This will be illustrated by considering inclusion of RSpace + iRODS in the two specific examples of Canada’s proposed Research Commons and the EUDAT Collaborative Data Infrastructure.  In both cases the interaction between RSpace, iRODS, and individual services provided  by the Commons will be discussed, and a comparison will be made between the two Commons and the benefits derived from the inclusion of RSpace + iRODS.
Ontology-Based Laboratory Data Acquisition With EnzymeML for Process Simulation of Biocatalytic Reactors
Authors: Behr Alexander S. , Abbaspour Elnaz , Rosenthal Katrin , Pleiss Jürgen , Kockmann Norbert
Published: September 2023

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.
Object-Related Research Data Workflows Within NFDI4Objects and Beyond
Authors: Thiery Florian , Mees Allard W. , Weisser Bernhard , Schäfer Felix F. , Baars Stefanie , Nolte Sonja , Senst Henriette , Von Rummel Philipp
Published: September 2023

NFDI4Objects (N4O) represents a broad community dealing with material remains of human history from around 3 million years and involves numerous disciplines from the humanities, cultural studies and natural sciences with an archaeological and historical focus [1]. The objects examined include potsherds of common ware, artworks such as sculptures or jewellery, serially produced objects such as coins, organic remains such as wood, bones or pollen, inscribed clay tablets, papyri and stones, architectural remains, as well as human-modified landscapes. Modern research materials such as plaster casts, analogue photographs and drawings, archival documents, books and raw digital data are equally relevant.
FAIRification of Historical Geodata
Authors: Herold Hendrik , Hartmann André , Schwartz Anna Lisa , Hellstern Michael , Schmalzl Markus
Published: September 2023

A key challenge for the NFDI community is to share and connect datasets across spatial and temporal scales. In particular for Earth System Sciences (ESS) coupling of different RDIs and access to long-term time series data are crucial. In this paper we propose a workflow pipeline for making analogue bound archival geodata FAIR and hence accessible to the different scientific disciplines and reusable in a long-term perspective. We describe an interface for enabling data exchange between an archive (GDA) and a geospatial RDI (IOER Monitor) as well as other RDIs by applying the FAIR data principles.
“Hello ELSA, how are you?”
Authors: Boehm Franziska , Sax Ulrich , Vettermann Oliver , Kamocki Paweł , Stoilova Vasilka
Published: September 2023

The proposed contribution will shed light on current and future challenges on legal and ethical questions in research data infrastructures. The authors of the proposal will present the work of NFDI’s section on Ethical, Legal and Social Aspects (hereinafter: ELSA), whose aim is to facilitate cross-disciplinary cooperation between the NFDI consortia in the relevant areas of management and re-use of research data.
Base4NFDI - Basic Services for NFDI
Authors: Schimmler Sonja , Altenhöner Reinhard , Bernard Lars , Fluck Juliane , Klinger Axel , Lorenz Soeren , Mathiak Brigitte , Miller Bernhard , Ritz Raphael , Schörner-Sadenius Thomas , Sczyrba Alexander , Stein Regine
Published: September 2023

NFDI is a German initiative to set up research data infrastructures across all disciplines. Within NFDI, Base4NFDI is a unique joint effort of all NFDI consortia to develop and deploy NFDI-wide basic services. Within this talk, we will give an overview of Base4NFDI, especially its structures and emerging work program, and inform about ways to participate and contribute ideas for potential basic services.
Data Management Plan Tools: Overview and Evaluation
Authors: Becker Carina , Hundt Carolin , Engelhardt Claudia , Sperling Johannes , Kurzweil Moritz , Müller-Pfefferkorn Ralph
Published: September 2023

Data Management Plans (DMPs) are crucial for a structured research data management and often a mandatory part of research proposals. DMP tools support the development of DMPs. Among the variety of tools available, it can be difficult for researchers, data stewards and institutions to choose the one that is most appropriate for their specific needs and context. We evaluated 18 DMP tools according to 31 requirement parameters covering aspects relating to basic functions, DMP contents, technical aspects and user friendliness. The highest total evaluation scores were reached by Data Stewardship Wizard (703.5), DMPTool (615.5) and RDMO NFDI4Ing (549.5). The tools evaluated satisfied between 10 % and 87 % of the requirement parameters. 11 tools cover at least half of the parameters. In terms of correlation among the tools, which indicates to which degree their scores in the different requirement parameters are alike, we found the highest correlation for ezDMP and GFBio DMPT. Regarding the relatedness between the tools, 85 % of the DMP tools were positively and 16 % negatively correlated. Accounting for the recent developments in the area of DMP tools, this study provides an up-to-date evaluation that can support tool developers in identifying potential improvements, and hosting institutions to select a tool suited to their specific needs.
Provenance Core Data Set
Authors: Sax Ulrich , Henke Christian , Dräger Christian , Bender Theresa , Kuntz Alessandra , Golebiewski Martin , Ulrich Hannes , Löbe Mattias
Published: September 2023

The exchange, dissemination, and reuse of biological specimens and data have become essentialfor life sciences research. This requires standards that enable cross-organizational documentation, traceability, and tracking of data and its corresponding metadata. Thus, data provenance, or the lineage of data, is an important aspect of data management in any information system integrating data from different sources [1]. It provides crucial information about the origin, transformation, and accountability of data, which is essential for ensuring trustworthiness, transparency, and quality of healthcare data [2]. For biological material and derived data, a novel ISO standard was recently introduced that specifies a general concept for a provenance information model for biological material and data and requirements for provenance data interoperability and serialization [3,4]. However, a specific standard for health data provenance is currently missing. In recent years, there has been a growing need for developing a minimal core data set for representing provenance information in health information systems. This paper presents a Provenance Core Data Set (PCDS), a generalized data model that aims to provide a set of attributes for describing data provenance in health information systems and beyond.
Current Insights From Task Area 1 in NFDI4Energy: Building and Serving the Energy Research Community
Authors: Werth Oliver , Ferenz Stephan , Niesse Astrid , German Reinhard , Huelck Ludwig , Weinhardt Christof , Vogel Berthold
Published: September 2023

Energy system research has become increasingly reliant on modeling and simulation approaches. These endeavors are enabled by continuously improving tools and methods for developing, maintaining and sharing models and data. Knowledge of how to better conduct, share and archive one’s research has become increasingly complex and hard to manage for individual researchers or single research groups. Identifying and including relevant scientists from energy research, social sciences, and further disciplines is sometimes difficult. Furthermore, a plethora of best practices and guidelines exist on how to prepare data, models and results in ways that make them easier to discover, verify and build upon. To present a sustainable, problem-solving, technical solution for the energy research community, NFDI4Energy develops in Task Area 1 (TA1) two services of the NFDI4Energy platform. Consequentially, the intention of this abstract within the disciplinary track “Engineering” is to provide an overview of the development process with a special focus on Competence and Best Practices. In addition, it discusses interconnections with other Task Areas as well as the chances and challenges that are associated with those connections. The academic audience, e.g., from the Information Systems and (Software) Engineering domain at CoRDI 2023, can observe and discuss our proposed procedure with other community members. Furthermore, we expect interested individuals to compare the proposed procedures with their own, which can lead to meaningful discussions and knowledge-sharing situations within the Engineering domain.
EOSC-Life Workflow Collaboratory for the Life Sciences
Authors: Goble Carole , Bacall Finn , Soiland-Reyes Stian , Owen Stuart , Eguinoa Ignacio , Droesbeke Bert , Ménager Hervé , Rodriguez-Navas Laura , Fernández José M. , Grüning Björn , Leo Simone , Pireddu Luca , Crusoe Michael , Gustafsson Johan , Capella-Gutierrez Salvador , Coppens Frederik
Published: September 2023

Workflows have become a major tool for the processing of Research Data, for example, data collection and data cleaning pipelines, data analytics, and data update feeds populating public archives. The EOSC-Life Research Infrastructure Cluster project brought together Europe’s Life Science Research Infrastructures to create an Open, Digital and Collaborative space for biological and medical research to develop a cloud-based Workflow Collaboratory. As adopting FAIR practices extends beyond data, the Workflow Collaboratory drives the implementation of FAIR computational workflows and tools. It fosters tool-focused collaborations and reuse via the sharing of data analysis workflows and offers an ecosystem of services for researchers and workflow specialists to find, use and reuse workflows. It’s web-friendly Digital Object Metadata Framework, based on RO-Crate and Bioschemas, supports the description and exchange of workflows across the services.
RDM System LARA
Authors: Doerr Mark , Maak Stefan T. , Menke Marian J. , Bornscheuer Uwe T.
Published: September 2023

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
We are Still Here, too! Research Data Management at Universities of Applied Sciences
Authors: Richter Manuela , Puztke Johannes , Schimmer Thomas M. , Mehler-Bicher Anett
Published: September 2023

The objective of the German non-profit association NFDI (German short form for ”National Research Data Infrastructure”) is to make the data stock of the entire German science system accessible to the public. To do so, it should involve all stakeholders. However, currently the Universities of Applied Sciences (UAS) are underrepresented in the NFDI, and there is a danger of neglecting their needs. Therefore, we present the project ”Research Data Management at Universities of Applied Sciences in the State of Rhineland-Palatinate” (FDM@HAW.rlp), which is funded by the German Federal Ministry of Education and Research (BMBF) and financed within the Recovery and Resilience Facility of the European Union. In the project, seven public UAS in Rhineland-Palatinate and the Catholic University of Applied Sciences (CUAS) Mainz follow a common goal: They intend to establish an institutional RDM within a period of three years by building up competencies at the UAS, setting up services for researchers and finding solutions for a common technical infrastructure.
NFDI4Health Local Data Hubs for Finding and Accessing Health Data
Authors: Meineke Frank , Golebiewski Martin , Hu Xiaoming , Kirsten Toralf , Löbe Matthias , Klammt Sebastian , Sax Ulrich , Müller Wolfgang
Published: September 2023

To support federated data structuring and sharing for sensitive health data from clinical trial, epidemiological and public health studies in the context of the German National Research Data Infrastructure for Personal Health Data (NFDI4Health), we have developed Local Data Hubs (LDHs) based on the FAIRDOM-SEEK platform. Those LDHs connect to the German Central Health Study Hub (CSH) to make the health data searchable and findable. This decentralised approach supports researchers to make health studies with their data FAIR (Findable, Accessible, Interoperable and Reusable), and at the same time fully preserves data protection for sensitive data.
Two-Step Approach in Metadata Management for Data Publications at Research Centers
Authors: Gruber Thomas , Schlenvoigt Hans-Peter , Knodel Oliver , Tippey Kristin , Juckeland Guido
Published: September 2023

Data repositories like Zenodo have a limited list of metadata to search for. Metadata catalogue are designed to provide a community-specific parameters search, but their deployment has just started. These catalogues require metadata standards for interoperability, which in turn are often in development for many communities. To support publications with a metadata standard in the future, a two-step concept is presented in this article. It discusses how the electronic documentation should be constructed, in order to convert this later into a standardized schema for publication. We will present examples from the laser-plasma community for both steps, firstly how we deal with the complex challenges of metadata management and secondly for methods for developing metadata schemas.
FAIRmat Guide to Writing Data Management Plans
Authors: Mansour Ahmed E. , Rotheray Lucia , Helbig Kerstin , Botti Silvana , Weber Heiko B. , Aeschlimann Martin , Draxl Claudia
Published: September 2023

Research data management is becoming an increasingly important topic due to the growing amounts of types, formats, and sizes of data produced by scientific research. In addition, a growing demand to make data accessible and comprehensible requires standardizing, managing, and planning the data life-cycle. For this reason, many funding agencies now require a data management plan (DMP) as part of submitted research proposals. While some of them and other scientific bodies offer DMP templates, there is no one-size-fits-all solution, due to the heterogeneity of data generated by different scientific disciplines. Here, we present as an example FAIRmat’s effort in enhancing data literacy on the topic of DMP aiming to guide physicists and materials scientists to writing DMPs that comply with the requirements of the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG).
MetaBelgica Project
Authors: Lieber Sven , Van Camp Ann , De Witte Dieter , Coudyzer Eva , Buelinckx Erik , Angenon Els , Lowagie Hannes , Birkholz Julie , Lasaracina Karine
Published: September 2023

Trustworthy metadata about entities related to cultural heritage is important to correctly identify bibliographic meta-data, attribute works, identify works of public domain (based on contributors’ date of death), or to support Named Entity Linking (NEL) for digitised documents. However, in Belgium such data is currently dispersed between numerous institutions, modelled with different ontologies, represented in different formats and curated in different languages. GLAM institutions would profit from data about Belgian entities to correctly annotate their collections.Furthermore, this would facilitate research in Belgium and abroad. The current situation does not only complicate data exchange in a national and international setting, but also leads to duplicate data curation efforts and data quality issues, negatively impacting the users’ experience.
This paper introduces the MetaBelgica project, coordinated by KBR - The Royal Library of Belgium with the Royal Museums of Fine Arts, the Royal institute for Cultural Heritage, and the Royal Museum of Art and History, to improve the status quo. The aforementioned Federal Scientific Institutes (FSIs), belonging to the Belgian Science Policy Office (BELSPO), joined forces to develop a shared Linked Data platform for managing shared entities. This platform, based on Wikibase (the technology behind Wikidata), aims to ensure FAIR data about persons, organisations, time/events and locations related to Belgian cultural heritage. We will integrate data about millions of Belgian entities from the four participating FSIs into a Wikibase instance and make it accessible by using Persistent Identifiers. This will not only professionalize our own data management and improve data quality, but according to received project support letters, also impact other regional, national and European institutions.
Embedding the de.NBI Cloud in the National Research Data Infrastructure Activities
Authors: Hoffmann Nils , Maus Irena , Beier Sebastian , Belmann Peter , Krüger Jan , Tauch Andreas , Goesmann Alexander , Eils Roland , Bork Peer , Kohlbacher Oliver , Kummer Ursula , Backofen Rolf , Buchhalter Ivo , Sczyrba Alexander
Published: September 2023

In recent years, modern life sciences research underwent a rapid development driven mainly by the technical improvements in analytical areas leading to miniaturization, parallelization, and high throughput processing of biological samples. This has led to the generation of huge amounts of experimental data. To meet these rising demands, the German Network for Bioinformatics Infrastructure (de.NBI) was established in 2015 as a national bioinformatics consortium aiming to provide high quality bioinformatics services, comprehensive training, powerful computing capacities (de.NBI Cloud) as well as connections to the European Life Science Infrastructure ELIXIR, with the goal to assist researchers in exploring and exploiting data more effectively.
Since its foundation, de.NBI Cloud has formed the scientific and collaborative backbone for new major German initiatives like NFDI or EOSC-Life in the European sector of computational biosciences. Above all, the cooperation with various NFDI consortia such as NFDI4Biodiversity, DataPLANT, GHGA, FAIRagro or NFDI4Microbiota showcases the power, range and flexibility of the de.NBI Cloud, especially for the national life science community.
In conclusion, the de.NBI Cloud provides the ability to unlock the full potential of research data and enables easier collaboration across different ecosystems and research areas, which in turn enables scientists to innovate and scale-up their data-driven research, not only in the life and computational biosciences, but across the different science domains addressed by the NFDI.
NFDI4DS Gateway and Portal
Authors: Usbeck Ricardo , Taffa Tilahun Abedissa , Garrido Veliz Rudy Alexandro , Abdullah Rana , Shams Najeebullah , Wentzel Bianca , Chen Zongxiong , Schimmler Sonja
Published: September 2023

©NFDI4DataScience (NFDI4DS) is a consortium to support researchers in all stages of the research data lifecycle to conduct their research in line with the FAIR principles. The developed infrastructure targets researchers from a wide range of disciplines in data science and AI.
We present the ideas of the NFDI4DS gateway and the NFDI4DS portal. Two approaches to navigate digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) from various NFDI4DS resources such as the ORKG, the DBLP database, and other research knowledge graphs (KGs). Transparency, reproducibility, and fairness will be fostered by a step-wise integration of existing and newly developed services into the overall system.
With this paper, we want to engage with the community and understand the needs and challenges of researchers in various disciplines regarding data science and AI. Therefore, we will discuss the currently developed prototypes and outline our plans for future development steps.
Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI)
Authors: Emery Tom , Karpinska Kasia , Maineri Angelica , Van der Meer Lucas
Published: September 2023

The Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) equips social scientists in the Netherlands with the data, tools, and skills that are necessary to answer groundbreaking questions for scientific and policy making purposes. With a variety of use cases to pick from, we aim at engaging in a discussion with other Research data infrastructures to identify synergies but also challenges ahead.
RO-Crates Meets FAIR Digital Objects
Authors: Castro Leyla Jael , Soiland-Reyes Stian , Rebholz-Schuhmann Dietrich
Published: September 2023

RO-Crates makes it easier to package research digital objects together with their metadata so both dependencies and context can be captured. Combined with FAIR good practices such as the use of persistent identifiers, inclusion of license, clear object provenance, and adherence to community standards, RO-crates provides a way to increase FAIRness in science. In this abstract we present the use of RO-Crates, combined with Linked Data best practices, as an implementation for lightweight FAIR Digital Objects, and its possible use in NFDI consortia.
Enhancing Reproducibility in Research Through FAIR Digital Objects
Authors: Boukhers Zeyd , Castro Leyla Jael
Published: September 2023

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.
Digitalization in Catalysis and Reaction Engineering: Automatizing Work Flows
Authors: Chacko Rinu , Gossler Hendrik , Riedel Johannes , Schunk Stephan Andreas , Deutschmann Olaf
Published: September 2023

Digitalization and surrounding efforts fostered by the advent of Industry 4.0 have been a development topic in the fields of chemistry and chemical engineering for several years – so timing may be right to look back and to question what the impact of efforts made, and to judge the impact of workflows and technologies developed. First and foremost, the first two key principle of Industry 4.0, namely Interconnectivity and Information Transparency play the crucial role in the context of Digitalization as only a seamless flow of data based on standardized formats remains key to enabling Decentralized Decisions and Technical Assistance. Digitization and digital tools play a key role in the acceleration data transfer and development efforts, the automation and autonomation of technical equipment employed, and the digital transformation of “classical” chemical reaction engineering processes towards an ideal originally projected by the high-tech agenda of Industry 4.0.
In this presentation we will start our journey with fully integrated environments on a laboratory level where data are not only made available in data warehouses but can be used to drive feedback loops to autonomously drive experimental devices.
A FAIR Future for Engineering Sciences
Authors: Silva Pimenta Izadora , Logan Kevin T. , Leštáková Michaela , Pelz Peter F.
Published: September 2023

The emergence of FAIR data management (FDM) is being witnessed in more and more disciplines, including the engineering sciences. However, until recently, little academic credit has been given for the work that sound FDM practices in research publications require. Moreover, there has been a lack of space where the engineering sciences community could discuss and share experiences, ideas and advice about this topic. In academia, a suitable platform for such information exchange are journals. In this publication, the concept behind ing.grid, the newly established open access journal for FDM in engineering sciences, is presented, illuminating how these challenges can be addressed by providing a platform for the publication of manuscripts, research data, and software as well as by incorporating open peer review.
Physicochemical profile, amino acid, and flavors of probiotic yogurt with the addition of nano ZnO food grade
Authors: ARIEF Irma Isnafia , ABIDIN Zaenal , WULANDARI Zakiah , BUDIMAN Cahyo , ADIYOGA Reza , KAMILA Elfa Aida
Published: September 2023

Yogurt is a functional food produced through milk fermentation by yogurt bacteria. The addition of Lactiplantibacillus plantarum IIA-1A5 in the fermentation of yogurt yielding a yogurt probiotic has been shown to exhibit some functional properties. The effects of adding ZnO on the overall properties of the yogurt are unknown. This study aimed to investigate the effect of ZnO nanoparticles on the characteristics of conventional yogurt and yogurt probiotics. Four sets of yogurts were prepared: conventional yogurt, yogurt with added ZnO, yogurt probiotic, and yogurt probiotic with added ZnO. Most of the physicochemical properties of all yogurts were found to be comparable, except for fat and solid non-fat contents. The addition of ZnO increased the total lactic acid bacteria (LAB) in the yogurt, but it apparently inhibited L. plantarum IIA-1A5 as indicated by a lower LAB population in the yogurt probiotic with added ZnO compared with the yogurt probiotic without ZnO. However, the combination of L. plantarum IIA-1A5 and ZnO in yogurt significantly enhanced the DPPH inhibition activity. Additionally, the positive effects of ZnO were also observed on the total amino acid content, which significantly modulate the flavor compounds. This indicates that, overall, ZnO contributed to the better characteristics of yogurts.
Functional properties of Ganoderma lucidum extract: antimicrobial and antioxidant activities
Authors: TEHRANIAN Mahdis Jamshidi , JOUKI Mohammad , SHAKOURI Mohammad Javad , JAFARI Sara
Published: September 2023

This research was conducted to investigate the functional properties of Ganoderma lucidum extract. The antimicrobial activity was evaluated on some bacteria causing food spoilage like Staphylococcus aureus and Escherichia coli. Antioxidant activity was investigated by examining the effect of the extract on DPPH and ABTS free radicals, determining the amount of total phenolic compounds and flavonoids. Based on the results, the antimicrobial and antioxidant activities of the extract were increased by increasing the concentration. Staphylococcus aureus showed the highest sensitivity to Ganoderma extract with minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of 50 and 100 μg/mL, respectively. The total phenols amount was equal to 383.727 milligrams of gallic acid equivalent per gram (mg GAE/g) of the extract and the total flavonoid was equal to 28.047 milligrams of quercetin equivalents per gram (mg QE/g) of extract. The results of antioxidant activity tests showed that the concentration of 400 μg/mL had the highest scavenging activity of 85.9 and 90.12% for DPPH and ABTS free radicals, respectively. Therefore, considering the potential antioxidant activity and the rich amounts of phenolic compounds in Ganoderma extract, it can be used in the pharmaceutical and food industries instead of synthetic antioxidants and other chemical preservatives to delay lipid peroxidation and prevent the growth of food pathogens.