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{"first" : "Henk", "last" : "Birkholz"}, {"first" : "Matthias", "last" : "Jung"}, {"first" : "Jörg", "last" : "Waitelonis"}, {"first" : "Lutz", "last" : "Mädler"}, {"first" : "Harald", "last" : "Sack"} ], "volume": "237","pages": "112603", "doi" : "10.1016/j.matdes.2023.112603", "bibtexKey": "bayerlein2024pmd" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2656665361e97a5f1c7fabc959e861a76/diglezakis", "tags" : [ "test" ], "intraHash" : "656665361e97a5f1c7fabc959e861a76", "interHash" : "91d3ddc3dea4ed80a9f94c747fa78742", "label" : "Atmospheric transmission models for FIFI-LS: altitude 35kft, 39deg O3", "user" : "diglezakis", "description" : "", "date" : "2026-02-11 15:20:32", "changeDate" : "2026-02-11 15:20:32", "count" : 2, "pub-type": "article", "publisher":"DaRUS", "year": "2026", "url": "https://doi.org/10.18419/DARUS-5705", "author": [ "SOFIA Data Center" ], "authors": [ {"first" : "SOFIA Data", "last" : "Center"} ], "version" : "V1", "doi" : "10.18419/DARUS-5705", "bibtexKey": "DARUS-5705_2026" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/26c58a1aea07ea5e76b67d69883eee407/lisabagdenand", "tags" : [ "JoDaKISS" ], "intraHash" : "6c58a1aea07ea5e76b67d69883eee407", "interHash" : "a2b7b21d25fe54b07b312c73a464edf3", "label" : "micro-XRCT data sets of a stone mastic asphalt drill core before and after a uniaxial\r\n compression test (sample 2): sample 2-1", "user" : "lisabagdenand", "description" : "", "date" : "2026-02-11 11:15:41", "changeDate" : "2026-02-11 11:15:41", "count" : 1, "pub-type": "article", "journal": "JoDaKISS - Journal of Data- and Knowledge-integrated Simulation Science","publisher":"Centre pour la Communication Scientifique Directe (CCSD)", "year": "2025", "url": "http://dx.doi.org/10.46298/jodakiss.15205", "author": [ "Matthias Ruf","Tim Teutsch","Stefan Alber","Holger Steeb","Wolfram Ressel" ], "authors": [ {"first" : "Matthias", "last" : "Ruf"}, {"first" : "Tim", "last" : "Teutsch"}, {"first" : "Stefan", "last" : "Alber"}, {"first" : "Holger", "last" : "Steeb"}, {"first" : "Wolfram", "last" : "Ressel"} ], "volume": "1", "issn" : "2944-7666", "doi" : "10.46298/jodakiss.15205", "bibtexKey": "Ruf_2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2ecc3103c5c53ce160ea82692daa222e1/lisabagdenand", "tags" : [ "JOSS" ], "intraHash" : "ecc3103c5c53ce160ea82692daa222e1", "interHash" : "9f5568df31220d710ca1202af17c8cf7", "label" : "conmat: generate synthetic contact matrices for a given age-stratified population", "user" : "lisabagdenand", "description" : "", "date" : "2026-02-11 08:40:58", "changeDate" : "2026-02-11 08:40:58", "count" : 1, "pub-type": "article", "journal": "Journal of Open Source Software","publisher":"The Open Journal", "year": "2026", "url": "http://dx.doi.org/10.21105/joss.08326", "author": [ "Nicholas Tierney","Chitra Saraswati","Aarathy Babu","Michael Lydeamore","Nick Golding" ], "authors": [ {"first" : "Nicholas", "last" : "Tierney"}, {"first" : "Chitra", "last" : "Saraswati"}, {"first" : "Aarathy", "last" : "Babu"}, {"first" : "Michael", "last" : "Lydeamore"}, {"first" : "Nick", "last" : "Golding"} ], "volume": "11","number": "118","pages": "8326", "issn" : "2475-9066", "doi" : "10.21105/joss.08326", "bibtexKey": "Tierney_2026" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/26d15b4908d4e5dbb792b3f9f2ce83bda/lisabagdenand", "tags" : [ "JoDaKISS" ], "intraHash" : "6d15b4908d4e5dbb792b3f9f2ce83bda", "interHash" : "2bc08bfb2da65b088dc69d748063d940", "label" : "BayesValidRox 2.0.0", "user" : "lisabagdenand", "description" : "", "date" : "2026-02-10 18:25:33", "changeDate" : "2026-02-10 18:25:33", "count" : 4, "pub-type": "article", "journal": "JoDaKISS - Journal of Data- and Knowledge-integrated Simulation Science","publisher":"Centre pour la Communication Scientifique Directe (CCSD)", "year": "2025", "url": "http://dx.doi.org/10.46298/jodakiss.15337", "author": [ "Rebecca Kohlhaas","Maria Fernanda Morales Oreamuno","Alina Lacheim" ], "authors": [ {"first" : "Rebecca", "last" : "Kohlhaas"}, {"first" : "Maria Fernanda", "last" : "Morales Oreamuno"}, {"first" : "Alina", "last" : "Lacheim"} ], "volume": "1", "issn" : "2944-7666", "doi" : "10.46298/jodakiss.15337", "bibtexKey": "Kohlhaas_2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/255d62ac6771158e22c668c0e3e1993a4/lisabagdenand", "tags" : [ "JoDaKISS" ], "intraHash" : "55d62ac6771158e22c668c0e3e1993a4", "interHash" : "93af529478ff7012ca56d82c1e01af35", "label" : "Replication Data for: Data-Parallel PU-RBF Interpolation", "user" : "lisabagdenand", "description" : "", "date" : "2026-02-10 18:04:16", "changeDate" : "2026-02-11 14:38:39", "count" : 1, "pub-type": "article", "journal": "JoDaKISS - Journal of Data- and Knowledge-integrated Simulation Science","publisher":"Centre pour la Communication Scientifique Directe (CCSD)", "year": "2026", "url": "http://dx.doi.org/10.46298/jodakiss.16884", "author": [ "David Schneider" ], "authors": [ {"first" : "David", "last" : "Schneider"} ], "volume": "2", "issn" : "2944-7666", "doi" : "10.46298/jodakiss.16884", "bibtexKey": "Schneider_2026" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2b1fed673da0a39c99c4bb5e55065f464/karolinewein", "tags" : [ "myown" ], "intraHash" : "b1fed673da0a39c99c4bb5e55065f464", "interHash" : "5aeae50dd696bc93b818230a0ba97180", "label" : "Integration Scripts for DFG Classification for Dataverse-based Repositories", "user" : "karolinewein", "description" : "", "date" : "2026-01-09 15:11:34", "changeDate" : "2026-01-09 15:11:34", "count" : 2, "pub-type": "misc", "year": "2025", "url": "", "author": [ "Sarbani Roy","Fangfang Wang","Karoline Weinspach" ], "authors": [ {"first" : "Sarbani", "last" : "Roy"}, {"first" : "Fangfang", "last" : "Wang"}, {"first" : "Karoline", "last" : "Weinspach"} ], "abstract": "These scripts integrate the DFG classification from the TIB ontology into Dataverse as an external vocabulary according to the Dataverse Guidelines. get_dfg_class.js: Displays entries from DFG classification in Topic Classification field once user has entered at least three characters. get_dfg_class_with_suggestions.js: Displays entries from DFG classification in Topic Classification field once user has entered at least three characters. Additionally, a button is provided that, when clicked, suggests relevant DFG categories based on the description text. cvocConf_dfg.json (Dataverse-Config-file. Integrates a Javascript file. Path to respective js file on server has to be set.) Please note that when using the TIB Terminology API, you must include a custom HTTP header named 'caller' in every request. This header identifies your institution or organization when accessing the API. In these scripts, the caller header is commented out as shown in the example: headers: \"accept\": \"application/json\", //\"caller\": \"DARUS\" Before using the scripts, uncomment the caller line and replace \"DARUS\" with the name of your own institution or organization. To activate the feature use: curl -X PUT --upload-file cvocConf_dfg.json http://localhost:8080/api/admin/settings/:CVocConf. If other CVOC functionalities are to be used, they would need to be integrated into the json file.", "affiliation" : "Roy, Sarbani/University of Stuttgart, Wang, Fangfang/University of Stuttgart, Weinspach, Karoline/University of Stuttgart", "orcid-numbers" : "Roy, Sarbani/https://orcid.org/0000-0002-5990-0076, Weinspach, Karoline/https://orcid.org/0009-0005-0587-1117", "doi" : "10.18419/darus-5428", "bibtexKey": "roy2025integration" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2b0fa6245dfc6696677adbc55a2d95b6a/karolinewein", "tags" : [ "myown" ], "intraHash" : "b0fa6245dfc6696677adbc55a2d95b6a", "interHash" : "1caf77b2e74fa028c6efecab01c5e124", "label" : "Training dataset for AI-supported subject indexing of research data with DFG classification", "user" : "karolinewein", "description" : "", "date" : "2026-01-09 15:10:13", "changeDate" : "2026-01-09 15:10:13", "count" : 2, "pub-type": "misc", "year": "2025", "url": "", "author": [ "Karoline Weinspach" ], "authors": [ {"first" : "Karoline", "last" : "Weinspach"} ], "abstract": "This is a structured JSON dataset for training and evaluating AI models for automated subject indexing of research data and linking of research data and publications. It was created for the project DA-FDM in order to train a vector based model to give automated suggestions for the topic classification of research datasets in DaRUS. In the context of this project, the DFG-classification was integrated as a controlled vocabulary in DaRUS for the Topic Classification field. DFG classes were added manually to datasets from DaRUS that were uploaded prior to the integration.This dataset includes classification tags (DFG, GND, Wikidata), publication links, respective open-access information, and, if the publication is open-access, the respective full texts for datasets from DaRUS as well as TUdatalib.", "affiliation" : "Weinspach, Karoline/University of Stuttgart", "orcid-numbers" : "Weinspach, Karoline/https://orcid.org/0009-0005-0587-1117", "doi" : "10.18419/darus-5500", "bibtexKey": "weinspach2025training" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2b0f0912a16d04a3c97351904e9487898/diglezakis", "tags" : [ "provenance","metadata","profile","prov" ], "intraHash" : "b0f0912a16d04a3c97351904e9487898", "interHash" : "2a1696235209d95bba6ec7f540319552", "label" : "Lightweight Distributed Provenance Model for Complex Real--world Environments", "user" : "diglezakis", "description" : "Lightweight Distributed Provenance Model for Complex Real\u2013world Environments | Scientific Data", "date" : "2025-10-13 09:04:04", "changeDate" : "2025-10-13 09:04:04", "count" : 1, "pub-type": "article", "journal": "Scientific Data", "year": "2022", "url": "https://doi.org/10.1038/s41597-022-01537-6", "author": [ "Rudolf Wittner","Cecilia Mascia","Matej Gallo","Francesca Frexia","Heimo Müller","Markus Plass","Jörg Geiger","Petr Holub" ], "authors": [ {"first" : "Rudolf", "last" : "Wittner"}, {"first" : "Cecilia", "last" : "Mascia"}, {"first" : "Matej", "last" : "Gallo"}, {"first" : "Francesca", "last" : "Frexia"}, {"first" : "Heimo", "last" : "Müller"}, {"first" : "Markus", "last" : "Plass"}, {"first" : "Jörg", "last" : "Geiger"}, {"first" : "Petr", "last" : "Holub"} ], "volume": "9","number": "1","pages": "503","abstract": "Provenance is information describing the lineage of an object, such as a dataset or biological material. Since these objects can be passed between organizations, each organization can document only parts of the objects life cycle. As a result, interconnection of distributed provenance parts forms distributed provenance chains. Dependant on the actual provenance content, complete provenance chains can provide traceability and contribute to reproducibility and FAIRness of research objects. In this paper, we define a lightweight provenance model based on W3C PROV that enables generation of distributed provenance chains in complex, multi-organizational environments. The application of the model is demonstrated with a use case spanning several steps of a real-world research pipeline --- starting with the acquisition of a specimen, its processing and storage, histological examination, and the generation/collection of associated data (images, annotations, clinical data), ending with training an AI model for the detection of tumor in the images. The proposed model has become an open conceptual foundation of the currently developed ISO 23494 standard on provenance for biotechnology domain.", "issn" : "2052-4463", "doi" : "10.1038/s41597-022-01537-6", "bibtexKey": "Wittner2022" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2fd766b4d17a1867d99f5c2444b6f26c6/diglezakis", "tags" : [ "forschungsdaten","metadata","AI","tools","LLM" ], "intraHash" : "fd766b4d17a1867d99f5c2444b6f26c6", "interHash" : "036177862ba9a7384486e5139d629765", "label" : "KONDA: An LLM-based Tool for Semantic Annotation\r\n and Knowledge Graph Creation Using Ontologies for\r\n Research Data", "user" : "diglezakis", "description" : "", "date" : "2025-10-09 14:34:45", "changeDate" : "2025-10-09 14:34:45", "count" : 2, "pub-type": "misc", "publisher":"Zenodo", "year": "2025", "url": "https://doi.org/10.5281/zenodo.16735948", "author": [ "Soo-Yon Kim","Martin Görz","Sandra Geisler" ], "authors": [ {"first" : "Soo-Yon", "last" : "Kim"}, {"first" : "Martin", "last" : "Görz"}, {"first" : "Sandra", "last" : "Geisler"} ], "doi" : "10.5281/zenodo.16735948", "bibtexKey": "kim_2025_16735948" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2272022da616d11298b613dbf01d20881/diglezakis", "tags" : [ "metadata","ontologie","simulation","nfdi4ing","multiscale" ], "intraHash" : "272022da616d11298b613dbf01d20881", "interHash" : "9d093c42aec1f0f187504d013484a772", "label" : "Enhancing Multiscale Simulation Data Management with Domain Ontologies and an ELN: Addressing Challenges and Implementing Strategies", "user" : "diglezakis", "description" : "", "date" : "2025-10-07 10:47:17", "changeDate" : "2025-10-07 10:47:17", "count" : 2, "pub-type": "article", "journal": "Data Science Journal", "year": "2025", "url": "", "author": [ "Hafiz Muhammad Noman","Michael Selzer" ], "authors": [ {"first" : "Hafiz Muhammad", "last" : "Noman"}, {"first" : "Michael", "last" : "Selzer"} ], "abstract": "Data plays a fundamental role in advancing knowledge and driving research across all fields. Despite the abundance of data, several challenges still need to be addressed. These challenges include limited accessibility, heterogeneous data, lack of interconnections between associated topics, difficulty retrieving required information, semantic mismatches, and several other challenges. Ontologies provide a structured method to address these challenges effectively.\r\nThis study addresses two central aspects of ontology research. First, it details the multidisciplinary ontology development process, highlighting the challenges, mitigation strategies, and impacts on domain data management. It then offers guidelines for beginners and individuals with a background in data management on effective engagement in ontology creation.\r\nSecond, it introduces the Ontology for Multiscale Simulation methods (Onto-MS), constructed by following the guidelines from the first part. The ontology, developed in Web Ontology Language (OWL) using Protégé, integrates with other ontologies, such as the Elementary Multiperspective Material Ontology (EMMO), aligning this research with the Linked Data concept. A custom Python script was used to incorporate the ontology into an Electronic Laboratory Notebook (ELN), enabling the automatic creation of knowledge graphs and systematic data organization conforming to the ontology.\r\nThis research successfully answers the fundamental questions in interdisciplinary or domain-level ontology development. Onto-MS provides a robust framework for organizing and linking data in multiscale simulations within computational materials science. Furthermore, ontology incorporation into an ELN simplifies its integration into data management practices. While ontology development is ongoing, the current version is functional and continuously refined with new insights and feedback.", "keyword" : "en", "doi" : "10.5334/dsj-2025-028", "bibtexKey": "Noman-2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/27b0ff014a770fd41df75b72133a392d1/diglezakis", "tags" : [ "enrichment","NLP","forschungsdaten","metadata","ontologie","AI","catalysis","extraction" ], "intraHash" : "7b0ff014a770fd41df75b72133a392d1", "interHash" : "c9546ba455ebfbfdb3b0d76d7cfb9fef", "label" : "Generating knowledge graphs through text mining of catalysis research related literature", "user" : "diglezakis", "description" : "", "date" : "2025-09-16 09:26:11", "changeDate" : "2025-10-07 14:32:41", "count" : 3, "pub-type": "article", "journal": "Catal. Sci. Technol.","publisher":"The Royal Society of Chemistry", "year": "2024", "url": "http://dx.doi.org/10.1039/D4CY00369A", "author": [ "Alexander S. Behr","Diana Chernenko","Dominik Koßmann","Arjun Neyyathala","Schirin Hanf","Stephan A. Schunk","Norbert Kockmann" ], "authors": [ {"first" : "Alexander S.", "last" : "Behr"}, {"first" : "Diana", "last" : "Chernenko"}, {"first" : "Dominik", "last" : "Koßmann"}, {"first" : "Arjun", "last" : "Neyyathala"}, {"first" : "Schirin", "last" : "Hanf"}, {"first" : "Stephan A.", "last" : "Schunk"}, {"first" : "Norbert", "last" : "Kockmann"} ], "volume": "14","number": "19","pages": "5699-5713","abstract": "Structured research data management in catalysis is crucial, especially for large amounts of data, and should be guided by FAIR principles for easy access and compatibility of data. Ontologies help to organize knowledge in a structured and FAIR way. The increasing numbers of scientific publications call for automated methods to preselect and access the desired knowledge while minimizing the effort to search for relevant publications. While ontology learning can be used to create structured knowledge graphs, named entity recognition allows detection and categorization of important information in text. This work combines ontology learning and named entity recognition for automated extraction of key data from publications and organization of the implicit knowledge in a machine- and user-readable knowledge graph and data. CatalysisIE is a pre-trained model for such information extraction for catalysis research. This model is used and extended in this work based on a new data set, increasing the precision and recall of the model with regard to the data set. Validation of the presented workflow is presented on two datasets regarding catalysis research. Preformulated SPARQL-queries are provided to show the usability and applicability of the resulting knowledge graph for researchers.", "doi" : "10.1039/D4CY00369A", "bibtexKey": "D4CY00369A" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2490b2c8474705588bc318906e9448df1/diglezakis", "tags" : [ "Verknüpfung","forschungsdaten","FAIR","rechtlicheFragestellungen","Datenschutz" ], "intraHash" : "490b2c8474705588bc318906e9448df1", "interHash" : "c62deab6fea554909a668eef1cf00d97", "label" : "FAIR-Prinzipien und Datenschutz | Factsheet 3 - Data Linkage: FAIR und datenschutzkonform", "user" : "diglezakis", "description" : "", "date" : "2025-07-16 14:26:58", "changeDate" : "2025-07-16 14:26:58", "count" : 1, "pub-type": "misc", "publisher":"Zenodo", "year": "2025", "url": "https://doi.org/10.5281/zenodo.15917014", "author": [ "Antonia Schier","Oliver Vettermann","Oliver Watteler","Ulrich Sax" ], "authors": [ {"first" : "Antonia", "last" : "Schier"}, {"first" : "Oliver", "last" : "Vettermann"}, {"first" : "Oliver", "last" : "Watteler"}, {"first" : "Ulrich", "last" : "Sax"} ], "version" : "1.1", "doi" : "10.5281/zenodo.15917014", "bibtexKey": "schier_2025_15917014" } ] }