BLAST: Block Applications for Things - Freund, Michael; Wehr, Thomas; Harth, Andreas (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022)
We introduce a block-based visual programming language called BLAST for programs involving connected devices with a Web of Things abstraction. We developed an editor and an execution environment for BLAST programs that runs in a web browser. We demonstrate that BLAST can be used to create programs that interact with a variety of devices. In particular we show the use of connected devices in a geofencing scenario.
CRIS-Team Scopus Importer:2022-08-05
Keywords: Block-based programming; Graphical programming; Web of Things

Enriching RDF Data with LLM Based Named Entity Recognition and Linking on Embedded Natural Language Annotations - Freund, Michael; Dorsch, Rene; Schmid, Sebastian Josef; Wehr, Thomas; Harth, Andreas (Knowledge Graphs and Semantic Web, 2025)
In this paper, we present a processing pipeline for transforming natural language annotations in RDF graphs into machine-readable and interoperable semantic annotations. The pipeline uses Named Entity Recognition (NER) and Entity Linking (EL) techniques based on a foundational Large Language Model (LLM), combined with a Knowledge Graph (KG) based knowledge injection approach for entity disambiguation and self-verification. Through a running example in the paper, we demonstrate that the pipeline can increase the number of semantic annotations in an RDF graph derived from information contained in natural language annotations. The evaluation of the proposed pipeline shows that the LLM-based NER approach produces results comparable to those of fine-tuned NER models. Furthermore, we show that the pipeline using a chain-of-thought prompting style with factual information retrieved via link traversal from an external KG achieves better entity disambiguation and linking than both a pipeline without chain-of-thought prompting and an approach relying only on information within the LL
Keywords: Natural Language Processing; KG enhanced LLM; RDF

Generating Visual Programming Blocks based on Semantics in W3C Thing Descriptions - Freund, Michael; Fries, Justus; Wehr, Thomas; Harth, Andreas (CEUR Workshop Proceedings, 2023)
We present mappings that leverage the semantic information in W3C Thing Descriptions (TDs) to generate structure definitions and code generator functions for visual programming blocks. In addition, we use link following to discover and consume related TDs. This approach extends device support in low-code IoT environments. Our implementation generates blocks and code generators in O(n), where n is the number of interaction affordances in a consumed TD, and follows links to Thing Descriptions in O(n + m), where n is the number of TDs and m the number of links to follow. Specifically, our implementation can discover 35 TDs with 128 interaction affordances and generate blocks and code in less than 200 ms, which is considered acceptable for interactive user interfaces.
CRIS-Team Scopus Importer:2023-10-06
Keywords: Block Generation; Low Code; Web of Things

Taking Control of Your Health Data: A Solid-based Mobile App for Wearable Data Collection and RDF Visualization - Wehr, Thomas; Freund, Michael; Harth, Andreas (21st Extended Semantic Web Conference (ESWC2024), 2025)
While wearables generate valuable health data, proprietary ecosystems limit interoperability and user control. We address this challenge with a user-friendly Android application that seamlessly collects data from diverse wearables via the Web of Things (WoT), converts the collected data into interoperable RDF using the SOSA/SSN ontology, and stores RDF in user-controlled Solid servers. Unlike existing solutions, our approach includes mapping the data to established ontologies and provides a user interface, empowering everyday users to explore their health data through interactive visualizations. We showcase the application's functionalities through live demonstrations – code, demo videos, and an installable apk are publicly available at https://github.com/derwehr/WoT-Solid/.<br
Keywords: RDF; Solid; Web of Things

The SPA Ontology: Towards a Web of Things Ready for Robotic Agents - Freund, Michael; Schraudner, Daniel; Schmid, Sebastian Josef; Stade, Christoph; Wehr, Thomas; Harth, Andreas (AKR³: 1st International Workshop on Actionable Knowledge Representation and Reasoning for Robots, 2024)
We present the Simple Planning Annotation (spa) ontology for modeling preconditions and effects of interaction affordances within Web of Things Thing Descriptions and propose a mapping to the Planning Domain Definition Language to enable robot-device interaction. We use encoded semantic knowledge to generate a planning problem that can be used within existing AI planning algorithms to dynamically plan interaction sequences to achieve specified goals without the extensive pre-programming traditionally required, as demonstrated by the validation of our approach through a prototypical implementation. The scalability evaluation shows that when the number of input Web of Things actions increases by a factor of 1,000, the runtime of the implemented prototype increases by about 14.3% and the memory consumption by about 9.4%, indicating vertical scalability.<br
Keywords: Actionable Knowledge Representation; Web of Things; AI planning