Martin Glauer
Dr.-Ing. Martin Glauer
Institut für Intelligente Kooperierende Systeme (IKS)
In my previous work, I have covered a broad spectrum of activities. In a leading role in the development of the Open Energy Platform, I created a platform for data exchange in the energy modeling domain. My foundational work on the Open Energy Ontology enabled these data to be annotated using rich semantic technologies -- initially independently and later together with a team that I advised. Collaborations with Prof. Janna Hastings and Dr. Fabian Neuhaus provided me with in-depth experience in ontology development and its application, and resulted in multiple publications on this topic. In addition, my many years of work with Prof. Till Mossakowski have given me solid expertise in the theoretical aspects of formal semantics.
Research Interests
- Ontology
- Ontologies in Information Systems
- Semantics-based Quality of Ontologies
- Formal Semantics
- Formal Semantics of Modelling Languages
- Heterogenous Reasoning
- Neuro-Symbolic Integration
- Ontology-aided Machine Learning
- Automated Ontology Extension
2025
Peer-reviewed journal article
Box embeddings for extending ontologies: a data-driven and interpretable approach
Memariani, Adel; Glauer, Martin; Flügel, Simon; Hastings, Janna; Mossakowski, Till; Neuhaus, Fabian
In: Journal of cheminformatics - London : BioMed Central, Bd. 17 (2025), Heft 1, Artikel 138, insges. 18 S.
When one logic is not enough - integrating first-order annotations in OWL ontologies
Flügel, Simon; Glauer, Martin; Neuhaus, Fabian; Hastings, Janna
In: Semantic web - Amsterdam : IOS Press, Bd. 16 (2025), Heft 2, Artikel SW-243440, insges. 15 S.
Non-peer-reviewed journal article
Chebifier 2 - an ensemble for chemistry
Flügel, Simon; Glauer, Martin; Hastings, Janna; Mossakowski, Till; Mungall, Christopher J.; Tumescheit, Charlotte; Neuhaus, Fabian
In: CEUR workshop proceedings - Aachen, Germany : RWTH Aachen, Bd. 4064 (2024), insges. 6 S. [Konferenz: 21st International Conference on Semantic Systems, SEMANTiCS 2025, Vienna, Austria, September 3-5, 2025]
2024
Book chapter
A fuzzy loss for ontology classification
Flügel, Simon; Glauer, Martin; Mossakowski, Till; Neuhaus, Fabian
In: Neural-Symbolic Learning and Reasoning , 1st ed. 2024. - Cham : Springer Nature Switzerland ; Besold, Tarek R., S. 101-118 - (Lecture notes in computer science; volume 14979) [Konferenz: 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, Barcelona, Spain, September 9-12, 2024]
Peer-reviewed journal article
Chebifier - automating semantic classification in ChEBI to accelerate data-driven discovery
Glauer, Martin; Neuhaus, Fabian; Flügel, Simone; Wosny, Marie; Mossakowski, Bis; Memariani, Adel; Schwerdt, Johannes; Hastings, Janna
In: Digital discovery - Cambridge : Royal Society of Chemistry, Bd. 3 (2024), Heft 5, S. 896-907
Interpretable ontology extension in chemistry
Glauer, Martin; Memariani, Adel; Neuhaus, Fabian; Mossakowski, Till; Hastings, Janna
In: Semantic web - Amsterdam : IOS Press, Bd. 15 (2024), Heft 4, S. 937-958
Dissertation
Knowledge and learning - synergies between ontologies and machine learning
Glauer, Martin; Mossakowski, Till; Hastings, Janna
In: Magdeburg: Universitätsbibliothek, Dissertation Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik 2024, 1 Online-Ressource (vii, 134 Seiten, 14,94 MB) [Literaturverzeichnis: Seite 119-134][Literaturverzeichnis: Seite 119-134]
2023
Book chapter
Ontology pre-training for poison prediction
Glauer, Martin; Neuhaus, Fabian; Mossakowski, Till; Hastings, Janna
In: KI 2023: Advances in Artificial Intelligence , 1st ed. 2023. - Cham : Springer Nature Switzerland ; Seipel, Dietmar, S. 31-45 - ( Lecture notes in computer science; volume 14236) [Konferenz: 46th German Conference on AI, Berlin, Germany, September 26-29, 2023]
Neuro-Symbolic Semantic Learning for Chemistry
Glauer, Martin; Mossakowski, Till; Neuhaus, Fabian; Memariani, Adel; Hastings, Janna
In: Compendium of Neurosymbolic Artificial Intelligence - Amsterdam : IOS Press . - 2023, S. 460-484, Artikel 21 - (Frontiers in artificial intelligence and applications; volume 369)
Peer-reviewed journal article
Predicting outcomes of smoking cessation interventions in novel scenarios using ontology-informed, interpretable machine learning
Hastings, Janna; Glauer, Martin; West, Robert; Thomas, James; Wright, Alison J.; Michie, Susan
In: Wellcome open research - London : Wellcome Trust, Bd. 8 (2023), Artikel 503, insges. 21 S.
2022
Book chapter
ESC-Rules - explainable, semantically constrained rule sets
Glauer, Martin; West, Robert; Michie, Susan; Hastings, Janna
In: CEUR workshop proceedings - Aachen, Germany : RWTH Aachen, Bd. 3212 (2022), Artikel paper 7, insges. 10 S.
2021
Book chapter
Automated and explainable ontology extension based on deep learning - a case study in the chemical domain
Memarian, Adel; Glauer, Martin; Neuhaus, Fabian; Mossakowski, Till; Hastings, Janna
In: DAO-XAI 2021, Data meets Applied Ontologies in Explainable AI , 2021 - [Aachen, Germany] : [RWTH Aachen] ; Confalonieri, Roberto, insges. 15 S. [Workshop: Workshop on Data meets Applied Ontologies in Explainable AI, DAO-XAI 2021, Bratislava, Slovakia, September 18 - 19, 2021]
FOWL - an OWL to FOL translator
Flügel, Simon; Kleinau, Anna; Neuhaus, Fabian; Glauer, Martin; Hastings, Janna
In: CEUR workshop proceedings - Aachen, Germany : RWTH Aachen, Bd. 2969 (2021), insges. 8 S. [Workshop: 12th International Conference on Biomedical Ontologies, ICBO 2021, Bolzano, Italy, September 11-18, 2021]
Peer-reviewed journal article
Learning chemistry - exploring the suitability of machine learning for the task of structure-based chemical ontology classification
Hastings, Janna; Glauer, Martin; Memariani, Adel; Neuhaus, Fabian; Mossakowski, Till
In: Journal of cheminformatics - London : BioMed Central, Bd. 13 (2021), Artikel 23, insges. 20 S.
Introducing the Open Energy Ontology - enhancing data interpretation and interfacing in energy systems analysis
Booshehri, Meisam; Emele, Lukas; Flügel, Simon; Förster, Hannah; Frey, Johannes; Frey, Ulrich; Glauer, Martin; Hastings, Janna; Hofmann, Christian; Hoyer-Klick, Carsten; Hülk, Ludwig; Kleinau, Anna; Knosala, Kevin; Kotzur, Leander; Kuckertz, Patrick; Mossakowski, Till; Muschner, Christoph; Neuhaus, Fabian; Pehl, Michaja; Robinius, Martin; Sehn, Vera; Stappel, Mirjam
In: Energy and AI - Amsterdam : Elsevier ScienceDirect, Bd. 5 (2021), Artikel 100074, insges. 14 S.
2020
Peer-reviewed journal article
Identification of user requirements for an energy scenario database
Reder, Klara; Stappel, Mirjam; Hofmann, Christian; Förster, Hannah; Emele, Lukas; Hülk, Ludwig; Glauer, Martin
In: International Journal of Sustainable Energy Planning and Management - Aalborg : Univ., Bd. 25 (2020), S. 95-108
Article in conference proceedings
Conversion necessities in climate and energy system modelling
Emele, Lukas; Förster, Hannah; Glauer, Martin; Hofmann, Christian; Huelk, Ludwig; Stappel, Mirjam; Winger, Christian
In: Zenodo - Genève : CERN . - 2020, insges. 20 S.
File formats in climate and energy system modelling
Emele, Lukas; Förster, Hannah; Glauer, Martin; Hofmann, Christian; Huelk, Ludwig; Stappel, Mirjam; Winger, Christian
In: Zenodo - Genève : CERN . - 2020, insges. 13 S.
2019
Book chapter
Institutions for SQL database schemas and datasets
Glauer, Martin; Mossakowski, Till
In: Recent Trends in Algebraic Development Techniques , 1st ed. 2019 - Cham : Springer ; Fiadeiro, José Luiz, S. 67-86 - (Lecture Notes in Computer Science; volume 11563) [Workshop: 24th IFIP WG 1.3 International Workshop, WADT 2018, Egham, UK, July 2-5, 2018]
Peer-reviewed journal article
Towards fuzzy neural conceptors
Mossakowski, Till; Diaconescu, Razvan; Glauer, Martin
In: Journal of applied logics - IfCoLoG journal of logics and their applications - London : College Publications, Bd. 6 (2019), Heft 4, S. 725-744
2018
Peer-reviewed journal article
Transparency, reproducibility, and quality of energy system analyses - a process to improve scientific work
Hülk, Ludwig; Müller, Berit; Glauer, Martin; Förster, Elisa; Schachler, Birgit
In: Energy strategy reviews - Amsterdam [u.a.] : Elsevier, Bd. 22 (2018), S. 264-269
2017
Book chapter
An open database concept for open energy modeling
Glauer, Martin; Stephan, Günther; Ludwig, Huelk; Wolf-Dieter, Bunke
In: EnviroInfo 2017 , 2017 - Aachen : Shaker Verlag, S. 191 [Konferenz: 31st EnviroInfo 2017, Luxembourg, September 13th15th, 2017]
Article in conference proceedings
Institutions for database schemas and datasets
Glauer, Martin; Mossakowski, Till
In: CALCO Early Ideas 2017$a satellite workshop of CALCO 2017 - Ljubljana - 2017, S. 6:1-6:3 [Workshop: CALCO Early Ideas 2017, Ljubljana, 14-16 June 2017]
2015
Book chapter
An institution for simple UML state machines
Knapp, Alexander; Mossakowski, Till; Roggenbach, Markus; Glauer, Martin
In: Fundamental Approaches to Software Engineering / Egyed , Alexander - Berlin, Heidelberg : Springer . - 2015, S. 3-18 - (Lecture Notes in Computer Science; 9033) Kongress: FASE 18 London, UK 2015.04.11-18
Towards online detection of neural assemblies in parallel spike trains
Braune, Christian; Glauer, Martin; Kruse, Rudolf
In: 48th Hawaii International Conference on System Sciences (HICSS), 2015 - Piscataway, NJ : IEEE, S. 1503-1511
Current projects
Digitization of materials research on thin-film materials using the example of high-resolution piezoelectric ultrasonic sensors
Duration: 01.04.2024 to 30.09.2026
This project is dedicated to two central questions. The first is: How can information about the production of thin-film materials from a wide variety of sources be brought together and organized in computers in such a way that this knowledge can be reused and expanded by future knowledge? The solution is to use ontologies. The great advantage of this technology is that it enables the reuse of existing data sets in new projects, thereby saving costs. Another advantage is that it enables information from different data sets to be linked, thereby creating synergies.
The second question is: Can the data sets linked by the ontology be used to predict how changes in the manufacturing processes (e.g. a lower substrate temperature) affect the properties of the resulting thin film? To answer this question, we use artificial intelligence methods that combine artificial neural networks with a logical representation. If successful, this technology will accelerate the development of new materials.
This text was translated with DeepL on 28/11/2025
Completed projects
Robustness and transferability of inter-municipal energy transition scenarios in the urban-rural nexus
Duration: 01.08.2022 to 31.07.2025
In the Urban-Rural-Energy project, we are developing open and transferable methods and tools that make it possible to calculate and suitably prepare robust, regionally interlinked and sector-coupled energy transition scenarios for the urban-rural nexus. Our aim is to promote intercom- munal cooperation and accelerate the local energy transition. Researchers benefit from the innovative methodology for robustness analysis in energy system models, the improvement of model solution times and the further development of efficient and open data management. The sub-project 'Data model, ontology and workflows for transferability' focuses on qualitative methods that enable and improve the organization and transferability of the data and processes used in the Urban-Rural-Energy project. We will link terms from different areas important for urban-rural energy to the Open Energy Ontology (OEO), namely from the data model, the areas of robustness, uncertainty and urban-rural nexus, as well as from the energy system models. In this way, we can make the terms used more comprehensible (especially for stakeholders), make the data and models easier to find, better structure the analysis of uncertainties and improve the transferability between models. Another focus of the OVGU concerns the preparation of input data for the new model calculations planned in Stadt-Land-Energie. The effort involved in processing heterogeneous input data is often underestimated. We are therefore using a graph-based workflow tool to create an automatic processing pipeline that converts different scenario data into the developed format and makes it available on the Open Energy Platform (OEP) for easy use.
This text was translated with DeepL
Ontology-based classification of chemical substances
Duration: 01.01.2020 to 31.12.2023
With the introduction of the CHEBI ontology and the associated web lexicon, a structure has been created that can be used to illustrate the logical relationships between different chemical substances and their functional properties. The classification of chemicals can be based on a wide variety of characteristics and is a highly manual and time-consuming process. In the course of this research work, possibilities to automate the classification of chemicals are being investigated. For this purpose, not only the latest findings and models from deep learning and especially neuro-symbolic integration are used, but also the rich logical annotations of the CHEBI ontology.
This text was translated with DeepL
Axiom selection for automatic proof systems
Duration: 01.01.2020 to 31.12.2022
Automatic reasoning systems have undergone rapid development in recent years. The integration of machine learning techniques has made it possible to develop effective heuristics for reasoning. Nevertheless, large logical theories, as found in many ontologies, often lead to problems. Therefore, in this research we explore possible machine learning approaches that allow to automatically select those axioms from a large theory that are needed to fulfill a given proof goal.
This text was translated with DeepL on 28/11/2025