Martin Giese

My complete list of publications, and downloadable versions of most of them, can be found on my personal homepage (no longer available).

• Kamburjan, Eduard; Klungre, Vidar Norstein; Qu, Yuanwei; Schlatte, Rudolf; Kostylev, Egor V. & Giese, Martin [Show all 7 contributors for this article] (2026). Semantically Reflected Programs. Transactions on Graph Data and Knowledge (TGDK). 4(1), p. 3:1–3:52. doi: 10.4230/TGDK.4.1.3. Full text in Research Archive Show summary

  This paper addresses the dichotomy between the formalization of structural and the formalization of executable behavioral knowledge by means of semantically lifted programs, which explore an intuitive connection between imperative programs and knowledge graphs. While knowledge graphs and ontologies are eminently useful to represent formal knowledge about a system’s individuals and universals, programming languages are designed to describe the system’s evolution. To address this dichotomy, we introduce a semantic lifting of the program states of an executing progam into a knowledge graph, for an object-oriented programming language. The resulting graph is exposed as a semantic reflection layer within the programming language, allowing programmers to leverage knowledge of the application domain in their programs during execution. In this paper, we formalize semantic lifting and semantic reflection for a small imperative programming language, SMOL, explain the operational aspects of the language, and consider type correctness and virtualization for runtime program queries through the semantic reflection layer. We illustrate semantic lifting and semantic reflection through a case study of geological modeling and discuss different applications of the technique. The language implementation is open source and available online.

• Klungre, Vidar Norstein; Soylu, Ahmet & Giese, Martin (2026). Avoiding unproductive SPARQL queries through optimized indices. World wide web (Bussum). ISSN 1386-145X. 29(4). doi: 10.1007/s11280-026-01419-6. Full text in Research Archive Show summary

  In interactive query formulation systems for SPARQL, suggested query extensions may result in queries with no answers, so-called unproductive queries. To avoid these, systems must detect and eliminate unproductive extensions. A straightforward approach is to check whether each extended query yields results, but this can be highly inefficient, especially for complex queries involving multiple costly joins. One possible solution is to construct an index that allows efficient checks. However, since queries can be arbitrarily large and complex, it is infeasible to build a complete index within finite space. A practical alternative is to index only the most common query patterns. This produces a smaller, finite index but may introduce inaccuracies in detecting unproductive extensions. The key challenge is balancing precision (the proportion of unproductive extensions correctly identified) against cost (the storage required for the index). In this article, we study this trade-off and present methods to construct indices with low cost while retaining high precision, given a dataset and representative query log. The problem is difficult because the space of possible indices is extremely large, making exhaustive search infeasible. Moreover, computing precision and cost for even a single index can be expensive. We therefore propose four heuristic-based search strategies to explore the index space efficiently, together with approximate cost and precision estimators. We evaluate these methods analytically and experimentally, using a benchmark based on Wikidata. Results show that our approaches identify non-trivial index configurations with high precision and low cost, making them practical for eliminating unproductive extensions in interactive systems.

• Ferreira, Carlos Eduardo A.; Ell, Basil; Giese, Martin & Carbonera, Joel L. (2025). Investigating Dynamic Example Selection for ICL-Based Text-to-SPARQL Generation. Proceedings - International Conference on Tools with Artificial Intelligence (ICTAI). ISSN 1082-3409. p. 1412–1419. doi: 10.1109/ICTAI66417.2025.00204. Full text in Research Archive
• Rollshausen, Nils; Kamburjan, Eduard & Giese, Martin (2024). Generating Transparent and Query-Based RDF Layers. In Kamburjan, Eduard; Fraga, David Chaves; Nathan, Paco; Roover, Coen De; Corcho, Oscar; Jimenez-Ruiz, Ernesto; Waaler, Arild Torolv Søetorp & Zhou, Baifan (Ed.), SOFLIM2KG-SEMIIM 2024 Joint Proceedings SOFLIM2KG and SEMIIM 2024. CEUR Workshop Proceedings. doi: https:/ceur-ws.org/Vol-3830/paper2.pdf. Full text in Research Archive Show summary

  We present inkblot, a software tool that generates object-oriented API code to represent the data found in a semantic model in a way suitable for programmers not familiar with semantic technologies. The API interacts with an RDF triple store via a SPARQL endpoint, but hides this connection from the programmer. The approach generates adequately typed fields and methods, based on the types and cardinalities in the data. Unlike previous work, the generation is not driven by an OWL ontology or similar declarative description of the application domain, but by a SPARQL query that accesses the pertinent data.

• Qu, Yuanwei; Kamburjan, Eduard; Torabi, Anita & Giese, Martin (2024). Semantically triggered qualitative simulation of a geological process. Applied Computing and Geosciences. 21. doi: 10.1016/j.acags.2023.100152. Full text in Research Archive
• Thapa, Ratan Bahadur & Giese, Martin (2023). Optimizing SPARQL Queries with SHACL. In Payne, Terry R.; Presutti, Valentina; Qi, Guilin; Stoilos, Giorgos; Cheng, Gong & Li, Juanzi (Ed.), The Semantic Web – ISWC 2023 22nd International Semantic Web Conference, Athens, Greece, November 6–10, 2023, Proceedings, Part I. Springer Cham. ISSN 9783031472398. p. 370–384. doi: 10.1007/978-3-031-47240-4_3. Full text in Research Archive
• Qu, Yuanwei; Perrin, Michel; Torabi, Anita; Abel, Mara & Giese, Martin (2023). GeoFault: A well-founded fault ontology for interoperability in geological modeling. Computers & Geosciences. ISSN 0098-3004. 182. doi: 10.1016/j.cageo.2023.105478. Full text in Research Archive Show summary

  Geological modeling currently uses various computer-based applications. Data harmonization at the semantic level using ontologies is essential to make these applications interoperable. Since geo-modeling is part of several multidisciplinary projects, interoperability requires semantic harmonization to exchange information between geological applications and integrate other domain knowledge at a general level. Therefore, domain ontologies that describe geological knowledge must be based on a sound ontological background to ensure this knowledge is integrable. Faults are essential for understanding and solving structural problems but are complex to model because the concept of fault includes a group of geological entities with a distinct ontological nature. A fault can correspond to thin, deformed rock volumes or spatial arrangements resulting from the displacement of geological blocks, but at a broader scale, geologists describe faults as surfaces or components of complex fault arrays. Our work intends to harmonize these views by presenting a domain ontology, GeoFault, resting on the Basic Formal Ontology (BFO) and the GeoCore ontology. GeoCore and GeoFault support the parametric description of geological sites as a preliminary step for quantitative and qualitative analysis. We have proposed GeoFault after systematically revising the literature and several knowledge-acquisition sessions with expert structural geologists. The ontology formalizes a vocabulary for fault “sensu stricto,” excluding ductile shear deformations. It covers the regional to outcrop scales, excluding structures at the microscopic, orogenic, and tectonics scales, and it avoids interpretive language associated with geological processes as far as possible. Extending the BFO and GeoCore ontologies allows the fault concept to be related to formal ontological classes in a consistent semantic-rich framework. The ontology artifact is implemented in OWL 2, validated by competency questions with two use cases, and tested using an in-house ontology-driven data entry application. The GeoFault ontology is publicly available and provides a solid framework for clarifying fault knowledge and a foundation for many applications.

• Kamburjan, Eduard; Klungre, Vidar Norstein; Tarifa, Silvia Lizeth Tapia; Schlatte, Rudolf; Giese, Martin & Cameron, David B. [Show all 7 contributors for this article] (2023). Emerging Challenges in Compositionality and Correctness for Digital Twins. CEUR Workshop Proceedings. 3507. Full text in Research Archive Show summary

  A digital twin is an information system that analyzes the behavior of a physical or digital system by connecting streams of observations to dynamic (e.g., simulation) and static (e.g., asset management) models of this twinned system. In large-scale industrial settings, the digital twin will often need to manage a multitude of models for subsystems reflecting different engineering disciplines, vendors, etc. To analyze such complex systems, digital twins must ensure the correct composition of these models and their correct exposure to the user. For the integration and transfer of information between models, digital twins may profit from a formalization of domain knowledge using ontologies, which have proven effective to unify data models. However, it is an open challenge to formalize and verify the correctness of digital twins. This paper discusses this problem for digital twins and illustrates challenges for formal methods with a focus on the composition of heterogeneous dynamic models.

• Qu, Yuanwei; Kamburjan, Eduard & Giese, Martin (2023). A Geological Case Study on Semantically Triggered Processes. In Pesquita, Catia; Jimenez-Ruiz, Ernesto; McCusker, Jamie; Faria, Daniel; Dragoni, Mauro; Dimou, Anastasia; Troncy, Raphaël & Hertling, Sven (Ed.), The Semantic Web: 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings. Springer. ISSN 9783031334559. Full text in Research Archive
• Kamburjan, Eduard; Klungre, Vidar Norstein & Giese, Martin (2022). Never Mind the Semantic Gap: Modular, Lazy and Safe Loading of RDF Data. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 13261. doi: 10.1007/978-3-031-06981-9_12. Full text in Research Archive
• Thapa, Ratan Bahadur & Giese, Martin (2022). Mapping Relational Database Constraints to SHACL. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. p. 214–230. doi: 10.1007/978-3-031-19433-7_13. Full text in Research Archive
• Thapa, Ratan Bahadur & Giese, Martin (2021). A Source-to-Target Constraint Rewriting for Direct Mapping. In Hotho, Andreas; Blomqvist, Eva; Dietze, Stefan; Fokoue, Achille; Ding, Ying; Barnaghi, Payam; Haller, Armin; Dragoni, Mauro & Alani, Harith (Ed.), The Semantic Web – ISWC 2021. 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24–28, 2021, Proceedings. Springer Nature. ISSN 9783030883614. p. 21–38. doi: 10.1007/978-3-030-88361-4_2. Full text in Research Archive
• Mumtaz, Summaya & Giese, Martin (2021). Hierarchy-based semantic embeddings for single-valued & multi-valued categorical variables. Journal of Intelligent Information Systems. ISSN 0925-9902. doi: 10.1007/s10844-021-00693-2. Full text in Research Archive
• Mumtaz, Summaya & Giese, Martin (2020). Frequency-Based vs. Knowledge-Based Similarity Measures for Categorical Data. In Martin, Andreas; Knut, Hinkelmann & Fill, Hans-George (Ed.), AAAI-MAKE 2020 Combining Machine Learning and Knowledge Engineering in Practice - Volume I: Spring Symposium. Technical University of Aachen. ISSN 9783642224126. Full text in Research Archive
• Mumtaz, Summaya; Pene, Irina; Latif, Adnan & Giese, Martin (2020). Data-based support for petroleum prospect evaluation. Earth Science Informatics [ESIN]. ISSN 1865-0473. doi: 10.1007/s12145-020-00502-4. Full text in Research Archive
• Karlsen, Leif Harald & Giese, Martin (2019). Qualitatively correct bintrees: an efficient representation of qualitative spatial information. Geoinformatica. ISSN 1384-6175. 23(4), p. 689–731. doi: 10.1007/s10707-019-00348-z. Full text in Research Archive
• Vega-Gorgojo, Guillermo; Slaughter, Laura & Giese, Martin (2019). Seeing the whole picture: Integrated pre-surgery reports with PreOptique. Journal of Biomedical Semantics. 10(1). doi: 10.1186/s13326-019-0197-1. Full text in Research Archive Show summary

  Background Information technology has transformed the way healthcare is conducted. There is a deluge of patient data dispersed in different systems that are commonly not interoperable. As a result, access to patient data has become a major bottleneck for healthcare professionals that struggle to find the relevant information in a timely way and without missing critical clinical information. Results We implemented PreOptique, a novel hybrid semantic and text-based system that was commissioned by a large hospital in Norway for providing integrated access to patient health records scattered over several databases and document repositories. We use ontology-based data access (OBDA) for the seamless integration of the structured databases at the hospital through the Optique platform. We employ text analysis techniques to extract vital sign measures and clinical findings from patient documents. PreOptique was developed and deployed at the hospital. This solution demonstrates how OBDA technology can provide integrated data access to disparate structured sources in healthcare, without requiring the replacement of existing databases. Unstructured clinical texts are also mined to extract patient findings, while the graphical user interface (GUI) provides a single access point that hides the underlying complexity of the system. We ran a usability study with 5 target users, obtaining a system usability score (SUS) of 86.0. Further, participants in the study stressed the simplicity of the GUI and the integration of data sources enabled by the system. Conclusions This pilot study showcases the use of OBDA technology and text analysis to enable the integration of patient data for supporting clinical surgery operations. PreOptique is usable and can be easily employed by medical personnel to find patient data in a timely way.

• Klungre, Vidar Norstein; Soylu, Ahmet; Jimenez-Ruiz, Ernesto; Kharlamov, Evgeny & Giese, Martin (2019). Query Extension Suggestions for Visual Query Systems Through Ontology Projection and Indexing. New generation computing. ISSN 0288-3635. 37(4), p. 361–392. doi: 10.1007/s00354-019-00071-1. Full text in Research Archive Show summary

  Ontology-based visual query formulation is a viable alternative to textual query editors in the Semantic Web domain for extracting data from structured data sources in terms of the skills and knowledge required. A visual query system is at any moment responsible for providing the user with query extension suggestions; however, suggestions leading to empty results are often not useful. To this end, in this article, we first present an approach for projecting OWL 2 ontologies into navigation graphs to be used for query formulation and then a solution where an efficient finite index is used to calculate non-ranked approximated extension suggestions for ontology-based visual query systems using navigation graphs. The results of our experiments suggest that one can efficiently project an ontology into a navigation graph, query it for running an interactive user interface, and suggest query extensions that do not lead to dead-ends.

• Xiao, Guohui; Hovland, Dag; Bilidas, Dimitris; Rezk, Martin; Giese, Martin & Calvanese, Diego (2018). Efficient Ontology-Based Data Integration with Canonical IRIs. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 10843 LNCS, p. 697–713. doi: 10.1007/978-3-319-93417-4_45. Full text in Research Archive Show summary

  In this paper, we study how to efficiently integrate multiple relational databases using an ontology-based approach. In ontology-based data integration (OBDI) an ontology provides a coherent view of multiple databases, and SPARQL queries over the ontology are rewritten into (federated) SQL queries over the underlying databases. Specifically, we address the scenario where records with different identifiers in different databases can represent the same entity. The standard approach in this case is to use sameAs to model the equivalence between entities. However, the standard semantics of sameAs may cause an exponential blow up of query results, since all possible combinations of equivalent identifiers have to be included in the answers. The large number of answers is not only detrimental to the performance of query evaluation, but also makes the answers difficult to understand due to the redundancy they introduce. This motivates us to propose an alternative approach, which is based on assigning canonical IRIs to entities in order to avoid redundancy. Formally, we present our approach as a new SPARQL entailment regime and compare it with the sameAs approach. We provide a prototype implementation and evaluate it in two experiments: in a real-world data integration scenario in Statoil and in an experiment extending the Wisconsin benchmark. The experimental results show that the canonical IRI approach is significantly more scalable.

• Klungre, Vidar Norstein & Giese, Martin (2018). Evaluating a Faceted Search Index for Graph Data. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11230 LNCS, p. 573–583. doi: 10.1007/978-3-030-02671-4_36. Full text in Research Archive Show summary

  We discuss the problem of implementing real-time faceted search interfaces over graph data, specifically the “value suggestion problem” of presenting the user with options that makes sense in the context of a partially constructed query. For queries that include many object properties, this task is computationally expensive. We show that good approximations to the value suggestion problem can be achieved by only looking at parts of queries, and we present an index structure that supports this approximation and is designed to scale gracefully to both very large datasets and complex queries. In a series of experiments, we show that the loss of accuracy is often minor, and additional accuracy can in many cases be achieved with a modest increase of index size.

• Klungre, Vidar Norstein & Giese, Martin (2018). Approximating Faceted Search for Graph Queries. CEUR Workshop Proceedings. p. 61–76. Full text in Research Archive
• Klungre, Vidar Norstein; Soylu, Ahmet; Giese, Martin; Waaler, Arild & Kharlamov, Evgeny (2018). On Enhancing Visual Query Building over KGs Using Query Logs. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11341, p. 77–85. doi: 10.1007/978-3-030-04284-4_6. Full text in Research Archive Show summary

  Knowledge Graphs have recently gained a lot of attention and have been successfully applied in both academia and industry. Since KGs may be very large: they may contain millions of entities and triples relating them to each other, to classes, and assigning them data values, it is important to provide endusers with effective tools to explore information encapsulated in KGs. In this work we present a visual query system that allows users to explore KGs by intuitively constructing tree-shaped conjunctive queries. It is known that systems of this kind suffer from the problem of information overflow: when constructing a query the users have to iteratively choose from a potentially very long list of options, sich as, entities, classes, and data values, where each such choice corresponds to an extension of the query new filters. In order to address this problem we propose an approach to substantially reduce such lists with the help of ranking and by eliminating the so-called deadends, options that yield queries with no answers over a given KG.

• Kharlamov, Evgeny; Mailis, Theofilos; Mehdi, Gulnar; Neuenstadt, Christian; Özçep, Özgür Lütfü & Roshchin, Mikhail [Show all 16 contributors for this article] (2017). Semantic access to streaming and static data at Siemens. Journal of Web Semantics. ISSN 1570-8268. 44, p. 54–74. doi: 10.1016/j.websem.2017.02.001. Full text in Research Archive Show summary

  We present a description and analysis of the data access challenge in Siemens Energy. We advocate Ontology Based Data Access (OBDA) as a suitable Semantic Web driven technology to address the challenge. We derive requirements for applying OBDA in Siemens, review existing OBDA systems and discuss their limitations with respect to the Siemens requirements. We then introduce the Optique platform as a suitable OBDA solution for Siemens. The platform is based on a number of novel techniques and components including a deployment module, BootOX for ontology and mapping bootstrapping, a query language STARQL that allows for a uniform querying of both streaming and static data, a highly optimised backend, ExaStream, for processing such data, and a query formulation interface, OptiqueVQS, that allows to formulate STARQL queries without prior knowledge of its formal syntax. Finally, we describe our installation and evaluation of the platform in Siemens.

• Soylu, Ahmet; Giese, Martin; Schlatte, Rudolf; Jimenez-Ruiz, Ernesto; Kharlamov, Evgeny & Özçep, Özgür [Show all 8 contributors for this article] (2017). Querying industrial stream-temporal data: An ontology-based visual approach. Journal of Ambient Intelligence and Smart Environments. ISSN 1876-1364. 9(1), p. 77–95. doi: 10.3233/AIS-160415. Full text in Research Archive Show summary

  An increasing number of sensors are being deployed in business-critical environments, systems, and equipment; and stream a vast amount of data. The operational efficiency and effectiveness of business processes rely on domain experts’ agility in interpreting data into actionable business information. A domain expert has extensive domain knowledge but not necessarily skills and knowledge on databases and formal query languages. Therefore, centralised approaches are often preferred. These require IT experts to translate the information needs of domain experts into extract-transform-load (ETL) processes in order to extract and integrate data and then let domain experts apply predefined analytics. Since such a workflow is too time intensive, heavy-weight and inflexible given the high volume and velocity of data, domain experts need to extract and analyse the data of interest directly. Ontologies, i.e., semantically rich conceptual domain models, present an intelligible solution by describing the domain of interest on a higher level of abstraction closer to the reality. Moreover, recent ontology-based data access (OBDA) technologies enable end users to formulate their information needs into queries using a set of terms defined in an ontology. Ontological queries could then be translated into SQL or some other database query languages, and executed over the data in its original place and format automatically. To this end, this article reports an ontology-based visual query system (VQS), namely OptiqueVQS, how it is extended for a stream-temporal query language called STARQL, a user experiment with the domain experts at Siemens AG, and STARQL’s query answering performance over a proof of concept implementation for PostgreSQL.

• Karlsen, Leif Harald & Giese, Martin (2017). An Efficient Representation of General Qualitative Spatial Information using Bintrees. Leibniz International Proceedings in Informatics. 86, p. 1–15. doi: 10.4230/LIPIcs.COSIT.2017.4. Full text in Research Archive Show summary

  In this paper we extend previous work on using bintrees as an efficient representation for qualitative information about spatial objects. Our approach represents each spatial object as a bintree satisfying the exact same qualitative relationships to other bintree representations as the corresponding spatial objects. We prove that such correct bintrees always exists and that they can be constructed as a sum of local representations, allowing a practically efficient construction. Our representation is both efficient, w.r.t. storage space and query time, and can represent many well-known qualitative relations, such as the relations in the Region Connection Calculus and Allen's Interval Algebra.

• Soylu, Ahmet; Kharlamov, Evgeny; Zheleznyakov, Dmitriy; Jimenez-Ruiz, Ernesto; Giese, Martin & Skjæveland, Martin G [Show all 11 contributors for this article] (2017). OptiqueVQS: a Visual Query System over Ontologies for Industry. Semantic Web – Interoperability, Usability, Applicability. ISSN 1570-0844. p. 1–28. doi: 10.3233/sw-180293. Full text in Research Archive Show summary

  An important application of semantic technologies in industry has been the formalisation of information models using OWL~2 ontologies and the use of RDF for storing and exchanging application data. Moreover, legacy data can be virtualised as RDF using ontologies following the ontology-based data access (OBDA) approach. In all these applications, it is important to provide domain experts with query formulation tools for expressing their information needs in terms of queries over ontologies. In this work, we present such a tool, OptiqueVQS, which is designed based on our experience with OBDA applications in Statoil and Siemens and on best HCI practices for interdisciplinary engineering environments. OptiqueVQS implements a number of unique techniques distinguishing it from analogous query formulation systems. In particular, it exploits ontology projection techniques to enable graph-based navigation over an ontology during query construction. Secondly, while OptiqueVQS is primarily ontology driven, it exploits sampled data to enhance selection of data values for some data attributes. Finally, OptiqueVQS is built on well grounded requirements, design rationale, and quality attributes. We evaluated OptiqueVQS with both domain experts and casual users and qualitatively compared our system against prominent visual systems for ontology-driven query formulation and exploration of semantic data. OptiqueVQS is available online and can be downloaded together with an example OBDA scenario.

• Vega-Gorgojo, Guillermo; Giese, Martin & Slaughter, Laura (2017). Exploring semantic datasets with RDF surveyor. CEUR Workshop Proceedings. 1963, p. 1–4. Full text in Research Archive
• Kharlamov, Evgeny; Hovland, Dag; Skjæveland, Martin G; Bilidas, Dimitris; Jimenez-Ruiz, Ernesto & Xiao, Guohui [Show all 16 contributors for this article] (2017). Ontology Based Data Access in Statoil. Journal of Web Semantics. ISSN 1570-8268. 44, p. 3–36. doi: 10.1016/j.websem.2017.05.005. Full text in Research Archive Show summary

  Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is ‘connected’ to the data via mappings that allow to automatically translate queries posed over the ontology into data-level queries that can be executed by the underlying database management system. Despite a lot of attention from the research community, there are still few instances of real world industrial use of OBDA systems. In this work we present data access challenges in the data-intensive petroleum company Statoil and our experience in addressing these challenges with OBDA technology. In particular, we have developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion; a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution over either a single DB of federated DBs; and a query formulation module to support query construction for engineers with a limited IT background. Our modules have been integrated in one OBDA system, deployed at Statoil, integrated with Statoil’s infrastructure, and evaluated with Statoil’s engineers and data.

• Klungre, Vidar Norstein & Giese, Martin (2017). A Faceted Search Index for OptiqueVQS. CEUR Workshop Proceedings. Full text in Research Archive
• Kharlamov, Evgeny; Mailis, Theofilis P.; Bereta, Konstantina; Bilidas, Dimitris; Brandt, Sebastian & Jimenez-Ruiz, Ernesto [Show all 20 contributors for this article] (2016). A Semantic Approach to Polystores. In Joshi, James (Eds.), Proceedings 2016 IEEE International Conference on Big Data. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781467390057. p. 2565–2573. doi: 10.1109/BigData.2016.7840898. Full text in Research Archive
• Kharlamov, Evgeny; Brandt, Sebastian; Giese, Martin; Jimenez-Ruiz, Ernesto; Kotidis, Yannis & Lamparter, Steffen [Show all 17 contributors for this article] (2016). Enabling semantic access to static and streaming distributed data with optique: demo. In Gal, Avigdor; Weidlich, Matthias; Kalogeraki, Vana & Venkasubramanian, Nalini (Ed.), Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, DEBS '16, Irvine, CA,USA, June 20 -24. ACM Publications. ISSN 9781450340212. p. 350–353. doi: 10.1145/2933267.2933290. Full text in Research Archive
• Zheleznyakov, Dmitriy; Kharlamov, Evgeny; Klungre, Vidar Norstein; Skjæveland, Martin G; Hovland, Dag & Giese, Martin [Show all 8 contributors for this article] (2016). KeywDB: A system for keyword-driven ontology-to-RDB mapping construction. CEUR Workshop Proceedings. 1690. Full text in Research Archive
• Vega-Gorgojo, Guillermo; Giese, Martin; Heggestøyl, Simen; Soylu, Ahmet & Waaler, Arild (2016). PepeSearch: Semantic Data for the masses. PLOS ONE. 11(3). doi: 10.1371/journal.pone.0151573. Full text in Research Archive Show summary

  With the emergence of the Web of Data, there is a need of tools for searching and exploring the growing amount of semantic data. Unfortunately, such tools are scarce and typically require knowledge of SPARQL/RDF. We propose here PepeSearch, a portable tool for searching semantic datasets devised for mainstream users. PepeSearch offers a multi-class search form automatically constructed from a SPARQL endpoint. We have tested PepeSearch with 15 participants searching a Linked Open Data version of the Norwegian Register of Business Enterprises for non-trivial challenges. Retrieval performance was encouragingly high and usability ratings were also very positive, thus suggesting that PepeSearch is effective for searching semantic datasets by mainstream users. We also assessed its portability by configuring PepeSearch to query other SPARQL endpoints.

• Soylu, Ahmet; Giese, Martin; Schlatte, Rudolf; Jiménez-Ruiz, Ernesto; Ozcep, Ozgur & Brandt, Sebastian (2016). Domain experts surfing on stream sensor data over ontologies. CEUR Workshop Proceedings. 1588, p. 11–20. Full text in Research Archive
• Vega-Gorgojo, Guillermo; Slaughter, Laura; Giese, Martin; Heggestøyl, Simen; Soylu, Ahmet & Waaler, Arild (2016). Visual query interfaces for semantic datasets: An evaluation study. Journal of Web Semantics. ISSN 1570-8268. 39, p. 81–96. doi: 10.1016/j.websem.2016.01.002. Full text in Research Archive
• Horrocks, Ian; Giese, Martin; Kharlamov, Evgeny & Waaler, Arild (2016). Using Semantic Technology to Tame the Data Variety Challenge. IEEE Internet Computing. ISSN 1089-7801. 20(6), p. 62–66. doi: 10.1109/MIC.2016.121. Full text in Research Archive
• Cameron, David B.; Skjæveland, Martin G; Giese, Martin; Hovland, Dag; Waaler, Arild & Bjørge, Eldar [Show all 7 contributors for this article] (2016). Optique: Simple, Oil & Gas-oriented access to big data in exploration, SPE Intelligent Energy Conference and Exhibition, Aberdeen, Scotland, UK, 6-8 September 2016 - Conference Proceedings. Society of Petroleum Engineers. ISSN 9781613994597. doi: 10.2118/181111-MS. Full text in Research Archive
• Soylu, Ahmet; Giese, Martin; Jiménez-Ruiz, Ernesto; Kharlamov, Evgeny; Zheleznyakov, Dmitriy & Horrocks, Ian (2016). Ontology-based end-user visual query formulation: Why, what, who, how, and which? Universal Access in the Information Society. ISSN 1615-5289. p. 1–33. doi: 10.1007/s10209-016-0465-0. Full text in Research Archive Show summary

  Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems.

• Soylu, Ahmet; Giese, Martin; Jimenez-Ruiz, Ernesto; Kharlamov, Evgeny; Schlatte, Rudolf & Neuenstadt, Christian [Show all 11 contributors for this article] (2016). Ontology-based visual querying with OptiqueVQS: Statoil and Siemens cases. CEUR Workshop Proceedings. 1818, p. 34–39. Full text in Research Archive
• Soylu, Ahmet; Giese, Martin; Schlatte, Rudolf; Jiménez-Ruiz, Ernesto; Özcep, Özgür & Brandt, Sebastian (2016). A visual query system for stream data access over ontologies. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 9989, p. 161–166. doi: 10.1007/978-3-319-47602-5_32. Full text in Research Archive
• Vega-Gorgojo, Guillermo; Slaughter, Laura; Giese, Martin; Heggestøyl, Simen; Kluwer, Johan Wilhelm & Waaler, Arild (2016). Pepesearch: Easy to use and easy to install semantic data search. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 9989 LNCS, p. 146–150. doi: 10.1007/978-3-319-47602-5_29. Full text in Research Archive
• Soylu, Ahmet & Giese, Martin (2015). Qualifying Ontology-Based Visual Query Formulation. In Andreasen, Troels; Christiansen, Henning; Kacprzyk, Janusz; Larsen, Henrik; Pasi, Gabriella; Pivert, Olivier; Tré, Guy De; Amparo, Maria; Yazici, Adnan & Zadrożny, Sławomir (Ed.), Flexible Query Answering Systems 2015 Proceedings of the 11th International Conference FQAS 2015, Cracow, Poland, October 26-28, 2015. Springer. ISSN 9783319261546. p. 243–255. doi: 10.1007/978-3-319-26154-6_19. Full text in Research Archive Show summary

  This paper elaborates on ontology-based end-user visual query formulation, particularly for users who otherwise cannot/do not desire to use formal textual query languages to retrieve data due to the lack of technical knowledge and skills. Then, it provides a set of quality attributes and features, primarily elicited via a series of industrial end-user workshops and user studies carried out in the course of an industrial EU project, to guide the design and development of successor visual query systems.

• Calvanese, Diego; Giese, Martin; Hovland, Dag & Rezk, Martin (2015). Ontology-Based Integration of Cross-Linked Datasets. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 9366, p. 199–216. doi: 10.1007/978-3-319-25007-6_12. Full text in Research Archive Show summary

  In this paper we tackle the problem of answering SPARQL queries over virtually integrated databases. We assume that the entity resolution problem has already been solved and explicit information is available about which records in the different databases refer to the same real world entity. Surprisingly, to the best of our knowledge, there has been no attempt to extend the standard Ontology-Based Data Access (OBDA) setting to take into account these DB links for SPARQL query-answering and consistency checking. This is partly because the OWL built-in owl:sameAs property, the most natural representation of links between data sets, is not included in OWL 2 QL, the de facto ontology language for OBDA. We formally treat several fundamental questions in this context: how links over database identifiers can be represented in terms of owl:sameAs statements, how to recover rewritability of SPARQL into SQL (lost because of owl:sameAs statements), and how to check consistency. Moreover, we investigate how our solution can be made to scale up to large enterprise datasets. We have implemented the approach, and carried out an extensive set of experiments showing its scalability.

• Karlsen, Leif Harald & Giese, Martin (2015). A Framework for Constructing Correct Qualitative Representations of Geometries using Mereology over Bintrees. In Lechowski, Tomasz; Wałęga, Przemysław & Zawidzki, Michał (Ed.), Proceedings of the LQMR 2015 Workshop. Polskie Towarzystwo Informatyczne. ISSN 9788360810781. p. 21–33. doi: 10.15439/978-83-60810-78-1. Full text in Research Archive
• Skjæveland, Martin G; Giese, Martin; Hovland, Dag; Lian, Espen Hallenstvedt & Waaler, Arild (2015). Engineering ontology-based access to real-world data sources. Journal of Web Semantics. ISSN 1570-8268. 33, p. 112–140. doi: 10.1016/j.websem.2015.03.002. Full text in Research Archive Show summary

  The preparation of existing real-world datasets for publication as high-quality semantic web data is a complex task that requires the concerted execution of a variety of processing steps using a range of different tools. Faced with both changing input data and evolving requirements on the produced output, we face a significant engineering task for schema and data transformation. We argue that to achieve a robust and flexible transformation process, a high-level declarative description is needed, that can be used to drive the entire tool chain. We have implemented this idea for the deployment of ontology-based data access (OBDA) solutions, where semantically annotated views that integrate multiple data sources on different formats are created, based on an ontology and a collection of mappings. Furthermore, we exemplify our approach and show how a single declarative description helps to orchestrate a complete tool chain, beginning with the download of datasets, and through to the installation of the datasets for a variety of tool applications, including data and query transformation processes and reasoning services. Our case study is based on several publicly available tabular and relational datasets concerning the operations of the petroleum industry in Norway. We include a discussion of the relative performance of the used tools on our case study, and an overview of lessons learnt for practical deployment of OBDA on real-world datasets.

• Soylu, Ahmet; Kharlamov, Evgeny; Zheleznyakov, Dmitriy; Jiménez-Ruiz, Ernesto; Giese, Martin & Horrocks, Ian (2015). OptiqueVQS: Ontology-based visual querying. CEUR Workshop Proceedings. 1456, p. 91–96. Full text in Research Archive
• Giese, Martin; Soylu, Ahmet; Vega, Gorgojo Guillermo; Waaler, Arild; Haase, Peter & Jimenez-Ruiz, Ernesto [Show all 11 contributors for this article] (2015). Optique: Zooming in on Big Data. Computer. ISSN 0018-9162. 48(3), p. 60–67. doi: 10.1109/MC.2015.82. Full text in Research Archive
• Soylu, Ahmet; Giese, Martin; Jimenez-ruiz, Ernesto; Vega, Gorgojo Guillermo & Horrocks, Ian (2015). Experiencing OptiqueVQS: A Multi-paradigm and Ontology-based Visual Query System for End Users. Universal Access in the Information Society. ISSN 1615-5289. 15(1), p. 129–152. doi: 10.1007/s10209-015-0404-5. Full text in Research Archive Show summary

  Data access in an enterprise setting is a determining factor for value creation processes, such as sense-making, decision-making, and intelligence analysis. Particularly, in an enterprise setting, intuitive data access tools that directly engage domain experts with data could substantially increase competitiveness and profitability. In this respect, the use of ontologies as a natural communication medium between end users and computers has emerged as a prominent approach. To this end, this article introduces a novel ontology-based visual query system, named OptiqueVQS, for end users. OptiqueVQS is built on a powerful and scalable data access platform and has a user-centric design supported by a widget-based flexible and extensible architecture allowing multiple coordinated representation and interaction paradigms to be employed. The results of a usability experiment performed with non-expert users suggest that OptiqueVQS provides a decent level of expressivity and high usability and hence is quite promising.

• Kharlamov, Evgeny; Brandt, Sebastian; Giese, Martin; Jiménez-Ruiz, Ernesto; Lamparter, Steffen & Neuenstadt, Christian [Show all 13 contributors for this article] (2015). Semantic access to siemens streaming data: The OPTIQUE way. CEUR Workshop Proceedings. 1486. Full text in Research Archive
• Kharlamov, Evgeny; Jiménez-Ruiz, Ernesto; Pinkel, Christoph; Rezk, Martin; Skjæveland, Martin G & Soylu, Ahmet [Show all 11 contributors for this article] (2015). OPTIQUE: Ontology-based data access platform. CEUR Workshop Proceedings. 1486. Full text in Research Archive
• Soylu, Ahmet; Kharlamov, Evgeny; Zheleznyakov, Dmitriy; Jiménez-Ruiz, Ernesto; Giese, Martin & Horrocks, Ian (2015). Ontology-Based Visual Query Formulation: An Industry Experience. In Bebis, George; Boyle, Richard; Parvin, Bahram; Koracin, Darko; Pavlidis, Ioannis; Feris, Rogerio; McGraw, Tim; Elendt, Mark; Kopper, Regis; Ragan, Eric; Ye, Zhao & Weber, Gunther (Ed.), Advances in Visual Computing 11th International Symposium, ISVC 2015, Las Vegas, NV, USA, December 14-16, 2015, Proceedings, Part I. Springer. ISSN 9783319278575. p. 842–854. doi: 10.1007/978-3-319-27857-5_75. Full text in Research Archive Show summary

  Querying is an essential instrument for meeting ad hoc information needs; however, current approaches for querying semantic data sources mostly target technologically versed users. Hence, there is a need for methods that make it possible for users with limited technological skills to express relatively complex ad hoc information needs in an easy and intuitive way. Visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. In this paper, we present an ontology-based visual query system, OptiqueVQS, and report user experiments in two industrial settings.

• Soylu, Ahmet; Giese, Martin; Jimenez-ruiz, Ernesto; Kharlamov, Evgeny; Zheleznyakov, Dmitriy & Horrocks, Ian (2014). Towards Exploiting Query History for Adaptive Ontology-based Visual Query Formulation. Communications in Computer and Information Science (CCIS). ISSN 1865-0929. 478, p. 107–119. doi: 10.1007/978-3-319-13674-5_11. Full text in Research Archive
• Heggestøyl, Simen; Vega-Gorgojo, Guillermo & Giese, Martin (2014). Visual Query Formulation for Linked Open Data: The Norwegian Entity Registry Case. NIKT: Norsk IKT-konferanse for forskning og utdanning. ISSN 1892-0713. 3. Full text in Research Archive
• Soylu, Ahmet; Kharlamov, Evgeny; Zheleznyakov, Dmitriy; Jimenez-ruiz, Ernesto; Giese, Martin & Horrocks, Ian (2014). OptiqueVQS: Visual Query Formulation for OBDA. CEUR Workshop Proceedings. 1193, p. 725–728. Full text in Research Archive
• Soylu, Ahmet; Giese, Martin; Jimenez-ruiz, Ernesto; Kharlamov, Evgeny; Zheleznyakov, Dmitriy & Horrocks, Ian (2014). Why not simply Google? In Olsson, Thomas & Hvannberg, Ebba Þóra (Ed.), NordiCHI '14 : Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational, Oct 26-30 2014, Helsinki, Finland. Association for Computing Machinery (ACM). ISSN 9781450325424. p. 1039–1042. doi: 10.1145/2639189.2670270. Full text in Research Archive
• Giese, Martin; Calvanese, Diego; Haase, Peter; Horrocks, Ian; Ioannidis, Yannis & Kllapi, Herald [Show all 16 contributors for this article] (2013). Scalable End-user Access to Big Data. In Akerkar, Rajendra (Eds.), Big Data Computing. Taylor & Francis. ISSN 9781466578371. doi: 10.1201/b16014-9. Full text in Research Archive
• grau, Bernardo Cuenca; Giese, Martin; Horrocks, Ian; Hubauer, Thomas; Jimenez-ruiz, Ernesto & Kharlamov, Evgeny [Show all 9 contributors for this article] (2013). Towards Query Formulation and Query-Driven Ontology Extensions in OBDA Systems. CEUR Workshop Proceedings. Full text in Research Archive
• Calvanese, Diego; Giese, Martin; Haase, Peter; Ioannidis, Yannis; Jimenez-ruiz, Ernesto & Kharlamov, Evgeny [Show all 20 contributors for this article] (2013). The Optique Project: Towards OBDA Systems for Industry. CEUR Workshop Proceedings. 1080. Full text in Research Archive
• Soylu, Ahmet; Skjæveland, Martin G; Giese, Martin; Horrocks, Ian; Jimenez-ruiz, Ernesto & Kharlamov, Evgeny [Show all 7 contributors for this article] (2013). A Preliminary Approach on Ontology-Based Visual Query Formulation for Big Data. In Garoufallou, Emmanouel & Greenberg, Jane (Ed.), Metadata and Semantics Research 7th Research Conference, MTSR 2013, Thessaloniki, Greece, November 19-22, 2013. Proceedings. Springer. ISSN 9783319034362. p. 201–212. doi: 10.1007/978-3-319-03437-9_21. Full text in Research Archive
• Soylu, Ahmet; Giese, Martin; Jimenez-ruiz, Ernesto; Kharlamov, Evgeny; Zheleznyakov, Dmitriy & Horrocks, Ian (2013). OptiqueVQS—Towards an Ontology-based Visual Query System for Big Data. In Ladid, Latif; Montes, Antonio; Bruck, Peter A.; Ferri, Fernando & Chbeir, Richard (Ed.), Fifth International Conference on Management of Emergent Digital EcoSystems, MEDES '13, Luxembourg, Luxembourg, October 29-31, 2013. Association for Computing Machinery (ACM). ISSN 9781450320047. p. 119–126. doi: 10.1145/2536146.2536149. Full text in Research Archive
• Calvanese, Diego; Giese, Martin; Haase, Peter; Horrocks, Ian; Hubauer, Thomas & Ioannidis, Yannis [Show all 23 contributors for this article] (2013). Optique: OBDA Solution for Big Data. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 7955, p. 293–295. doi: 10.1007/978-3-642-41242-4_48. Full text in Research Archive
• Kharlamov, Evgeny; Jimenez-ruiz, Ernesto; Zheleznyakov, Dmitriy; Bilidas, Dimitris; Giese, Martin & Haase, Peter [Show all 16 contributors for this article] (2013). Optique: Towards OBDA Systems for Industry. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 7955, p. 125–140. doi: 10.1007/978-3-642-41242-4_11. Full text in Research Archive
• Hansen, Christian Mahesh; Antonsen, Roger; Giese, Martin & Waaler, Arild (2012). Incremental variable splitting. Journal of symbolic computation. ISSN 0747-7171. 47(9), p. 1046–1065. doi: 10.1016/j.jsc.2011.12.032. Full text in Research Archive Show summary

  The variable splitting method for free-variable tableau calculi provides an admissibility condition under which the same free variables can be assigned values independently on different branches. While this has a large potential for automated proof search, a direct implementation of this condition is impractical. We adapt the incremental closure framework for free variables to variable splitting tableaux by recasting the admissibility condition for closing substitutions into a constraint satisfaction problem. The resulting mechanism allows to check the existence of an admissible closing substitution incrementally during the construction of a proof. We specify a rule-based algorithm for testing satisfiability of constraints that accounts for split variables, and present experimental results based on a prototype variable splitting theorem prover implementation measuring the computational overhead of the variable splitting framework.

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• Gutiérrez-Basulto, Víctor; Kliegr, Tomas; Soylu, Ahmet; Giese, Martin & Roman, Dumitru (2020). Rules and Reasoning. 4th International Joint Conference, RuleML+RR 2020, Oslo, Norway, June 29 – July 1, 2020, Proceedings. Springer. ISBN 9783030579777. 187 p. Full text in Research Archive
• Gao, Jerry; Giese, Martin & Zeng, Yifeng (2016). 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService 2016). IEEE (Institute of Electrical and Electronics Engineers). ISBN 9781509022519. 300 p. Full text in Research Archive

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• Wally, Youssef; Ell, Basil; Ricaud, Benjamin; Mylius-Kroken, Johan; Giese, Martin & Kampffmeyer, Michael [Show all 10 contributors for this article] (2026). Biologically Informed Across Space and Time Modelling of the Tumour Microenvironment. Full text in Research Archive Show summary

  Understanding spatial cell organisation in the tumour microenvironment is critical for cancer research, as it provides key insights into disease mechanisms. In this ongoing work, we explore two approaches that incorporate biological knowledge while analysing the tumour microenvironment. Firstly, we embed single-cell instances into a Lorentzian latent space using a fully hyperbolic variational autoencoder, which we have previously shown to retain significantly more biologically relevant information than Euclidean alternatives. Secondly, we adopt taxonomy-aware spatial association rule mining for quantifying cell interaction behaviour beyond pairwise interactions.

• Wally, Youssef; Mylius-Kroken, Johan; Kampffmeyer, Michael; Ehsani, Rezvan; Ell, Basil & Ricaud, Benjamin [Show all 10 contributors for this article] (2026). Biologically Informed Modelling of the Tumour Microenvironment: Hyperbolic Representation Learning and Hierarchical Association Rules. Full text in Research Archive Show summary

  Understanding spatial cell organisation in the tumour microenvironment is critical for cancer research, as it provides key insights into disease mechanisms. In this ongoing work, we explore two approaches that incorporate biological knowledge while analysing the tumour microenvironment. Firstly, we embed single-cell instances into a Lorentzian latent space using a fully hyperbolic variational autoencoder, which we have previously shown to retain significantly more biologically relevant information than Euclidean alternatives. Secondly, we adopt taxonomy-aware spatial association rule mining for quantifying cell interaction behaviour beyond pairwise interactions.

• Zuccato, Lorenzo; George, Anne-Marie; Vitelli, Valeria; Frigessi, Arnoldo; Giese, Martin & Scheel, Ida (2026). Bridging Statistical and Logical Perspectives on Inconsistency. Full text in Research Archive
• Wally, Youssef; Ell, Basil; Ricaud, Benjamin; Mylius-Kroken, Johan; Giese, Martin & Kampffmeyer, Michael [Show all 10 contributors for this article] (2026). Extracting Knowledge from Spatial Biology: Evaluating Cell Type Hierarchies in Breast Cancer Imaging Data. Full text in Research Archive Show summary

  Hyperbolic representation learning has shown compelling advantages over conventional Eu- clidean representation learning in modelling hierarchical relationships in data. In this work, we evaluate its potential to capture biological relations between cell types in highly multiplexed imaging data, where capturing subtle, hierarchical relationships between cell types is crucial to understand tissue composi- tion and functionality. Using a recent and thoroughly validated 42-marker Imaging Mass Cytometry (IMC) dataset of breast cancer tissue, we embed cells into both Euclidean and Lorentzian latent spaces via a fully hyperbolic variational autoencoder. We then introduce an information-theoretic framework based on k-nearest neighbour estimators to rigorously quantify the clustering performance in each geom- etry using mutual information and conditional mutual information. Our results reveal that hyperbolic embeddings retain significantly more biologically relevant information than their Euclidean counter- parts. We further provide open-source tools to extend Kraskov-Stögbauer-Grassberger based mutual information estimation to Lorentzian geodesic spaces, and to enable UMAP visualizations with hyper- bolic distance metrics. This work contributes a principled evaluation method for geometry-aware learning and supports the growing evidence of hyperbolic geometry’s benefits in spatial biology. Code is available at: https://github.com/youssefwally/FlatlandandBeyond

• Wally, Youssef; Ell, Basil; Ricaud, Benjamin; Giese, Martin; Vitelli, Valeria & Milosevic, Vladan [Show all 7 contributors for this article] (2026). Representing cell type hierarchies in breast cancer. Full text in Research Archive Show summary

  Understanding the spatial organisation of cells within tissues is fundamental for cell niches discovery. Advances in spatial omics technologies now yield high-resolution maps of cell populations across tissue sections, yet computational methods for systematically discovering recurrent, interpretable multi-cell assemblies remain limited, particularly when cell type annotations are organised in hierarchical taxonomies. Cell type ontologies in modern atlases naturally form hierarchies, ignoring this structure leads to either redundant or missed niche patterns. We present our on-going work for cell niche discovery based on spatial association rule mining that is explicitly aware of these hierarchical relationships. By propagating colocation evidence through the taxonomy, we are able to identify multi-cell-type assemblies that co-occur significantly across tissue regions at both fine-grained and coarser levels of cell-type resolution, reducing redundancy while improving interpretability

• Wally, Youssef; Ell, Basil; Ricaud, Benjamin; Giese, Martin; Vitelli, Valeria & Milosevic, Vladan [Show all 7 contributors for this article] (2026). Cell Niche discovery via taxonomy-aware spatial association rule mining. Full text in Research Archive Show summary

  Understanding the spatial organisation of cells within tissues is fundamental for cell niches discovery. Advances in spatial omics technologies now yield high-resolution maps of cell populations across tissue sections, yet computational methods for systematically discovering recurrent, interpretable multi-cell assemblies remain limited, particularly when cell type annotations are organised in hierarchical taxonomies. Cell type ontologies in modern atlases naturally form hierarchies, ignoring this structure leads to either redundant or missed niche patterns. We present our on-going work for cell niche discovery based on spatial association rule mining that is explicitly aware of these hierarchical relationships. By propagating colocation evidence through the taxonomy, we are able to identify multi-cell-type assemblies that co-occur significantly across tissue regions at both fine-grained and coarser levels of cell-type resolution, reducing redundancy while improving interpretability

• Wally, Youssef; Ell, Basil; Ricaud, Benjamin; Giese, Martin; Milosevic, Vladan & Vitelli, Valeria [Show all 7 contributors for this article] (2026). Cell Niche discovery via taxonomy-aware spatial association rule mining. Full text in Research Archive Show summary

  Understanding the spatial organisation of cells within tissues is fundamental for cell niches discovery. Advances in spatial omics technologies now yield high-resolution maps of cell populations across tissue sections, yet computational methods for systematically discovering recurrent, interpretable multi-cell assemblies remain limited, particularly when cell type annotations are organised in hierarchical taxonomies. Cell type ontologies in modern atlases naturally form hierarchies, ignoring this structure leads to either redundant or missed niche patterns. We present our on-going work for cell niche discovery based on spatial association rule mining that is explicitly aware of these hierarchical relationships. By propagating colocation evidence through the taxonomy, we are able to identify multi-cell-type assemblies that co-occur significantly across tissue regions at both fine-grained and coarser levels of cell-type resolution, reducing redundancy while improving interpretability

• Wally, Youssef; Giese, Martin; Ell, Basil; Ricaud, Benjamin & Wetzer, Elisabeth (2025). Cell Niche Discovery via Association Rules Mining. Full text in Research Archive Show summary

  Taxonomy-aware colocation pattern discovery seeks to identify groups of spatial feature types, or their hierarchical ancestors, that are frequently located together, given Boolean spatial features, their instances, a neighbourhood relation, and a feature taxonomy. Incorporating taxonomy is essential for many application domains, such as spatial pathology, where relationships among features are naturally hierarchical and semantically meaningful. However, accounting for parent–child relationships in the taxonomy greatly expands the candidate pattern space and introduces substantial redundancy. Traditional colocation mining approaches ignore hierarchical structure, leading to redundant computations and missed higher-level patterns. A taxonomy-aware perspective enables more expressive pattern discovery by leveraging hierarchical semantics while addressing redundancy arising from overlapping parent–child instances. Empirical studies on synthetic and real-world datasets show that taxonomy-aware colocation discovery can reveal meaningful patterns that are not captured by taxonomy-agnostic methods and can reduce duplication in the resulting colocations.

• Giese, Martin; Johnsen, Einar Broch; Tveito, Lars & Waaler, Arild Torolv Søetorp (2024). Roger Antonsen (1976 - 2024). Full text in Research Archive
• Giese, Martin; Johnsen, Einar Broch; Tveito, Lars & Waaler, Arild Torolv Søetorp (2024). Nekrolog: Roger Antonsen fanget publikum med sitt smittende engasjement. Full text in Research Archive
• Qu, Yuanwei; Zhou, Baifan; Kharlamov, Evgeny & Giese, Martin (2022). Industrial Geological Information Capture with GeoStructure Ontology. Full text in Research Archive Show summary

  Understanding geological structures plays an essential role in a wide range of industries. Various tools and software have been developed to support the observation and characterisation of the geological structures and they produce a large volume of heterogeneous data. Thanks to the development of semantic technologies, plenty of works have investigated industrial geological data. In contrast, geological sketches, figure interpretations, and illustrations as the initial data collection and analysis steps have received little attention. Most structure information is still reported as PDF files with forms, tables, and raster images with interpretations. We attempt to fill this gap by providing an ontology- based industrial geological information capture method to allow users to input and store structure information formally. Following users’ sketches, the corresponding knowledge graphs will be generated. This work aims to make the first-hand geological structure information findable, accessible, interoperable, reusable (FAIR), and to support qualitative information reasoning, from a user-driven perspective, and to meet the needs of digitised industry.

• Giese, Martin & Kindermann, Christian (2022). Building Good Information Models for Digital Twins Easily. Full text in Research Archive
• Gutiérrez-Basulto, Víctor; Soylu, Ahmet; Roman, Dumitru; Kliegr, Tomáš & Giese, Martin (2020). Preface. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 12173, p. v–vi. Full text in Research Archive
• Mumtaz, Summaya; Pene, Irina; Latif, Adnan & Giese, Martin (2020). Correction to: Data-based support for petroleum prospect evaluation (Earth Science Informatics, (2020), 13, 4, (1305-1324), 10.1007/s12145-020-00502-4). Earth Science Informatics [ESIN]. ISSN 1865-0473. 13(4), p. 1325–1325. doi: 10.1007/s12145-020-00536-8. Full text in Research Archive
• Latif, Adnan; ́enez-Ruiz, Ernesto Jim; Giese, Martin; Stahl, Oliver; Pene, Irina & Heeremans, Michel [Show all 10 contributors for this article] (2019). Ontology-driven annotation system for Geological Images. Full text in Research Archive
• Latif, Adnan; Waaler, Arild; Giese, Martin; Hovland, Dag & Skjæveland, Martin G (2018). Ontology-Based Data Access in Exploration. Full text in Research Archive
• Soylu, Ahmet; Giese, Martin; Jimenez-Ruiz, Ernesto; Kharlamov, Evgeny; Schlatte, Rudolf & Neuenstadt, Christian [Show all 11 contributors for this article] (2016). Ontology-based Visual Querying with OptiqueVQS: Statoil and Siemens Cases. CEUR Workshop Proceedings. 1818. Full text in Research Archive
• Cameron, David B.; Skjæveland, Martin G; Giese, Martin; Hovland, Dag; Waaler, Arild & Bjørge, Eldar [Show all 7 contributors for this article] (2016). Optique: Simple, Oil & Gas-oriented access to big data in exploration. Full text in Research Archive
• Heggestøyl, Simen; Vega-Gorgojo, Guillermo & Giese, Martin (2014). Visual Query Formulation for Linked Open Data: The Norwegian Entity Registry Case. Full text in Research Archive
• Kharlamov, Evgeny; Giese, Martin; Jimenez-ruiz, Ernesto; Skjæveland, Martin G; Soylu, Ahmet & Zheleznyakov, Dmitriy [Show all 21 contributors for this article] (2013). Optique 1.0: Semantic Access to Big Data: The Case of Norwegian Petroleum Directorate's FactPages. Full text in Research Archive
• Giese, Martin (2013). Optique - Scalable End-user Access to Big Data. Full text in Research Archive
• Giese, Martin & Waaler, Arild (2013). Optique - Scalable End-user Access to Big Data. Full text in Research Archive
• Giese, Martin (2013). Optique - Scalable End-user Access to Big Data. Full text in Research Archive
• Hovland, Dag; Holen, Bjarne & Giese, Martin (2012). Efficient Rule-Matching for Hyper-Tableaux. Full text in Research Archive Show summary

  Over the past decades, a number of calculi for automated reasoning have been proposed that share some core features: 1. proofs are built in a tableau/sequent style as trees where nodes are labeled with literals, and 2. these proofs are expanded by interpreting the problem clause set as a set of rules, and requiring all negative literals in clauses to present on a branch for expansion. This applies to hyper-tableaux [2], MGTP [8], coherent logic [4, 5], and others. Existing implementations typically spend much of their time in the process of matching branch literals with the negative literals of the input clauses. We present an alternative to this matching process by applying a modified version of the Rete algorithm [7]. The Rete algorithm was developed in the 1970s for production systems in artificial intelligence. We exploit the similarities between the mentioned calculi and production systems in order to make the Rete algorithm solve the matching problem. We also investigate the effect of working on several independent branches present in tableau proof search but not in production systems. 9th International Workshop on the Implementation of Logics. Merida, 10.03.12 - 10.03.12.

• Giese, Martin & Ivanovska, Magdalena (2012). Logics for Decision Making. Full text in Research Archive
• Ivanovska, Magdalena & Giese, Martin (2012). A Probabilistic Logic for Sequences of Decisions. Full text in Research Archive
• Søberg, Anders; Giese, Martin & Kostylev, Egor V. (2025). Description Logics with Epsilon Individuals (long version). Universitetet i Oslo. ISSN 9788273686077. Full text in Research Archive Show summary

  We investigate the extension of description logics (DLs) with definite descriptions—that is, references to individuals based on descriptions of their properties. Specifically, we introduce the syntax and semantics for ε-individuals, modelled on the ε-terms that Hilbert introduced for first-order logic. We present sound and complete reasoning algorithms for the logics that result from adding ε-individuals to several well-known DLs. In particular, for the extension of the basic DL ALC with ε-individuals, we provide a tableau calculus and show that the language without TBoxes is as expressive as the language with TBoxes; both also share EXPTIME-completeness of reasoning. In the case of the extension ALCO of the language with nominals, we give a reduction to the language ALCOu with the universal role and show that reasoning remains EXPTIME-complete. Finally, for the lightweight DL ΕLO, we show that the usual saturation calculus can be extended for ε-individuals, while maintaining the PTIME complexity.

• Thapa, Ratan Bahadur & Giese, Martin (2023). Optimizing SPARQL Queries with SHACL (Extended Version). Universitetet i Oslo. ISSN 9788273686046. Full text in Research Archive Show summary

  We propose a set of optimizations that can be applied to a given SPARQL query, and that guarantee that the optimized query has the same answers under bag semantics as the original query, provided that the queried RDF graph validates certain SHACL constraints. Our optimizations exploit the relationship between graph patterns in the SPARQL queries and the SHACL constraints that describe those patterns in the RDF graph. We prove the correctness of these optimizations and show how they can be propagated to larger queries while preserving answers. Further, we prove the confluence of rewritings that employ these optimizations, guaranteeing convergence to the same optimized query regardless of the rewriting order.

• Kamburjan, Eduard; Klungre, Vidar Norstein & Giese, Martin (2022). Never Mind the Semantic Gap: Modular, Lazy and Safe Loading of RDF Data (Full Paper). Universitetet i Oslo. ISSN 9788273686022. Full text in Research Archive Show summary

  Any attempt at a tight integration between semantic technologies and object oriented programming will invariably stumble over the gap between the two underlying object models. We illustrate how this semantic gap manifests from the point of view of data retrieval with SPARQL. We present a novel mechanism to load data from RDF knowledge graphs into object-oriented languages that gives static guarantees about the data access and modularly integrates the mapping between the program and the RDF view with the class definition in the program. This allows us to preserve the separation of concerns between the class system of RDF (geared towards domain modeling and data), and that of the program (geared towards typing and code reuse). Loading of RDF can be performed lazily, when required by the program, based on query-futures - subqueries that are only evaluated if and when the data is accessed. We formulate a Liskov principle for the mapping queries to characterize when they respect the subclass relation. Moreover, we provide tool support to detect when the user-provided mapping would cause the loading mechanisms to result in data structures that manifest the semantic gap.

• Thapa, Ratan Bahadur & Giese, Martin (2022). Mapping Relational Database Constraints to SHACL (Extended Version). Universitetet i Oslo. ISSN 9788273686039. Full text in Research Archive Show summary

  Most structured data today is still stored in relational databases, which makes it important to provide a translation between relational and semantic data. A relational to RDF mapping, such as R2RML [14], provides a way to view existing relational data in the RDF data model through declarative mappings. While relational to RDF mapping translates relational instance data to RDF, it does not specify any translation of existing relational constraints such as primary and foreign key constraints. Since the introduction of R2RML, interest in RDF constraint languages has increased and SHACL [17] has been standardised. This raises the question of which SHACL constraints are guaranteed to be valid on a dataset produced by a relational to RDF mapping. For arbitrary SQL constraints and relational to RDF mappings, this is a hard problem, but we introduce a number of restrictions on the mappings that allow us to introduce a constraint rewriting for relational to RDF mappings that faithfully transfers SQL integrity constraints to SHACL constraints. We define and prove two fundamental properties, namely maximal semantics preservation and monotonicity.

• Kamburjan, Eduard; Klungre, Vidar; Schlatte, Rudolf; Johnsen, Einar Broch & Giese, Martin (2021). Programming and Debugging with Semantically Lifted States (Full Paper). Universitetet i Oslo. Institutt for informatikk. ISSN 9788273684646. Full text in Research Archive Show summary

  We propose a novel integration of programming languages with semantic technologies. We create a semantic reflection mechanism by a direct mapping from program states to RDF knowledge graphs. This mechanism enables several promising novel applications including the use of semantic technology, including reasoning, for debugging and validating the sanity of program states, and integration with external knowledge graphs. Additionally, by making the knowledge graph accessible from the program, method implementations can refer to state semantics rather than objects, establishing a deep integration between programs and semantics. This allows the programmer to use domain knowledge formalized as, e.g., an ontology directly in the program’s control flow. We formalize this integration by defining a core object based programming language that incorporates these features. A prototypical interpreter is available for download.

• Thapa, Ratan Bahadur & Giese, Martin (2021). A Source-to-Target Constraint rewriting for Direct Mapping (Extended Version). Universitetet i Oslo. ISSN 9788273684639. Full text in Research Archive Show summary

  Most of the existing structured digital information today is still stored in relational databases. That’s why it is important for the Semantic Web effort to expose the information in relational databases as RDF, or allow to query it using SPARQL. Direct mapping is a fully automated approach for converting well-structured relational data to RDF that does not require formulating explicit mapping rules [2,9]. Along with the mapped RDF data, it is desirable to have a description of that data. Previous work [9,3] has attempted to describe the RDF graph in terms of OWL axioms, which is problematic, partly due to the open world semantics of OWL. We start from the direct mapping suggested by Sequeda et al. [9], which integrates and extends the functionalities of proposal [10] and the W3C recommendation [2], and present a source-to-target semantics preserving rewriting of constraints in an SQL database schema to equivalent SHACL [8] constraints on the RDF graph. We thus provide a SHACL description of the RDF data generated by the direct mapping without the need to perform a costly validation of those constraints on the generated data. Following the approach of [9], we define the rewriting from SQL constraints to SHACL by a set of Datalog rules. We prove that our source-to-target rewriting of constraints is constraint preserving and weakly semantics preserving. September 15, 2021

• Karlsen, Leif Harald & Giese, Martin (2018). A simple, General and Efficient Representation of Qualitative Spatial Information; An Approach Based on Bintrees. Series of dissertations submitted ti the Faculty of Mathematics and Natural Sciences, University of Oslo. Full text in Research Archive
• Karlsen, Leif Harald & Giese, Martin (2017). An Efficient Representation of Qualitative Spatial Information using Bintrees. Department of Informatics, University of Oslo. ISSN 9788273684257. Full text in Research Archive Show summary

  We present a representation of spatial data that supports answering of qualitative queries (involving e.g. containment and overlap), using less time than numerical computations on coordinates, and less space than explicitly storing the relations. The representation is based on the well-known bintree indexing data structure, which we refine to provide exact answers instead of approximations. We have imple- mented the method, and tested it on several real-world datasets with promising results.

• Karlsen, Leif Harald & Giese, Martin (2017). Qualitatively Correct Bintrees With Roles. Department of Informatics, University of Oslo. ISSN 9788273684325. Full text in Research Archive Show summary

  The concrete problem this paper addresses is the following: Given a set of objects with a spatial interpretation and a set of qualitative relations, construct a bintree representation that returns the same answers to queries with the given relations over the spatial objects. We have previously constructed both theory [8] and an implementation [9] for constructing such qualitatively correct bintrees, with promising results. However, our previous work has been restricted to the construction of bintree-representations that are correct only w.r.t. part-of and overlaps relationships. In this paper we will extend the theoretical foundation to allow for representations that are correct with respect to a more expressive set of relations.

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