Dr. Stefan Thiemann

@article{02c53b332ccf448c84741b4e41f7bf00,

title = "Building sustainable information systems and transformer models on demand",

abstract = "The growing practice of archiving research data in repositories reflects an upward trend. However, storing data in an RDR (Research Data Repository) does not guarantee that the archived data will always be readily reusable, even if this fulfils the FAIR (Findable, Accessible, Interoperable, Reusable) principles. To ensure sustainable RDM (Research Data Management), archiving must consider the future potential for data reuse in a low-threshold fashion. In this article, we demonstrate the utilisation of straightforward methods to implement a so-called warm or hot archiving for research data within an RDR, as opposed to the conventional cold archiving approach. We explore the additional value of using research data in the humanities, emphasising the advantages of maintaining data accessibility and relevance over time. In the humanities, evaluating numerous data sets efficiently is crucial for current and future projects. Reviewing and evaluating relevance is important, particularly when dealing with a substantial number of data sets. Rapid evaluation facilitates profound decisions on the utility of the data for one{\textquoteright}s ongoing or upcoming projects. For hot archiving, this means that in addition to the research data, the data should be available in a human-friendly way, i.e., a viewer application to visualise the data should be easily accessible. However, as rapid developments in the IT sector mean that after a few years, it cannot be guaranteed that these viewers or other tools will work, we also show how data can be viewed in a user-specific way via the RDR and how sustainable viewing can be integrated into the RDR. This article presents a generic approach to building sustainable viewers, which we call information systems, or transformer models on demand using data from pre-modern Arabic. In addition, we show that the easy-to-use chatbot ChatGPT can alternatively be context-specifically prepared to deliver more precise results and associated resources in the field of humanities. On the one hand, we have achieved a substantial reduction in the development time of an information system, from months to seconds, as well as the ability to fine-tune BERT (Bidirectional Encoder Representations from Transformers) models without specific knowledge in selecting models or tools. On the other hand, we have developed a chatbot that not only provides project-specific responses but also references the sources.",

author = "Thomas Asselborn and Sylvia Melzer and Simon Schiff and Magnus Bender and Florian Marwitz and Said Aljoumani and Stefan Thiemann and Konrad Hirschler and Ralf M{\"o}ller",

year = "2025",

month = feb,

day = "15",

doi = "10.1057/s41599-025-04491-x",

language = "English",

volume = "12",

journal = "Humanities and Social Sciences Communications",

issn = "2662-9992",

publisher = "Springer Nature",

number = "1",

@article{ae6cf57d46eb4d56bc762c3f86a960b4,

title = "Implementation of a Federated Information System by means of Reuse of Research Data archived in Research Data Repositories",

abstract = "At universities, research data is increasingly stored in research data repositories according to a data management plan (DMP) and thus made available for further use. The challenge of reusing hundreds, thousands, or millions of data sets is to obtain an overview of the data in a short period of time and to search through all the data. The high variability of the formats used to store research data requires a new approach to data reusability that focuses on the visualisation and searchability of archived research data, which can also be combined with each other. In this article, we present a practical DMP that describes how information systems can be created on demand by reusing research data archived in research data repositories and how these systems can be merged into a federated information system. As a result, in our projects, information systems have been created in minutes or a couple of hours with few resources. The initial effort to create a federated system remains; however, this allows federated searches to be performed. Extending a federated system to include other information systems can then be accomplished by making a few configurations and manageable adjustments to the source code.",

keywords = "FAIR principles, data management plan, databasing on demand, federated information system",

author = "Sylvia Melzer and Stefan Thiemann and Simon Schiff and Ralf M{\"o}ller",

year = "2023",

month = oct,

day = "12",

doi = "10.5334/dsj-2023-039",

language = "English",

volume = "22",

journal = "Data Science Journal",

issn = "1683-1470",

publisher = "Ubiquity Press",

number = "39",

@article{d0d7e0145c024e608d68c2b14a5d63a5,

title = "Das Forschungsdatenzentrum der Universit{\"a}t Hamburg: Auf dem Weg zu einem gemeinsamen Verst{\"a}ndnis im Umgang mit Forschungsdaten in den Natur-, Sozial- und Geisteswissenschaften",

abstract = "Die Umsetzung und Etablierung eines generischen Forschungsdatenmanagements ander Universit{\"a}t Hamburg folgt dem Ansatz des Kaizen-basierten Continuous Improve-ment Prozesses (CIP)1, bei dem induktiv und kleinschrittig aus disziplinenspezifischenBest-Practices gelernt wird. Der Forschungsdatenlebenzyklus, in dem sich die Prozes-se jeder Disziplin wiederfinden lassen, dient als gemeinsamer Ausgangspunkt. Eben-so werden die strategischen Vorgaben der Universit{\"a}t zum Open Science ber{\"u}cksich-tigt. Dieser Erfahrungsbericht stellt ein Ergebnis des CIPs dar, dessen Hauptaufgabedarin besteht, die Prozesse so zu gestalten und in verschiedenen Softwarel{\"o}sungenabzubilden, dass sich eine stetig wachsende Zahl an disziplinenspezifischen Prakti-ken umsetzen lassen.",

author = "Hagen Peukert and Sylvia Melzer and Juliane Jacob and Iris Vogel and Kai W{\"o}rner and Steffen Gr{\"u}nler and Lisa Brase and Alexander Heinrich and Stefan Thiemann",

year = "2023",

month = may,

day = "31",

doi = "10.17192/BFDM.2023.3.8562",

language = "Deutsch",

volume = "2",

pages = "2--13",

journal = "Bausteine Forschungsdatenmanagement",

number = "3",