A Context-aware Conversational Interface for Controlling Internet-of-Things Devices - Gui, Zhou; Freund, Michael; Harth, Andreas (IoT '24: Proceedings of the 13th International Conference on the Internet of Things, 2024)
This paper presents a demonstration of a context-aware conversational interface for interacting with multiple IoT devices using multi-turn natural language commands. Our system facilitates device discovery and identification through a Knowledge Graph (KG) and addresses the interoperability issue by using the Web of Things (WoT) specifications as an intermediate abstraction layer. The proposed system comprises four major components: a context-aware multi-turn dialogue interface, a device discovery and identification module using a domain-specific KG, a text-to-code module to parse natural language commands into an executable code format, and a customized code execution engine. We demonstrate our system using two Philips Hue smart lamps and one Elgato Stream Deck controller. The Philips Hue smart lamp device can be controlled standalone via natural language, allowing users to adjust the power state, the color, and the brightness. Also, the lamp can be integrated with the Elgato Stream Deck Controller to enable user-defined automation rules following the Trigger Action programming (TAP) paradigm.</smal
Keywords: Conversational Interface; Internet of Things; Trigger Action Programming; Natural Language Understanding; Knowledge Graph

Adaptive Planning on the Web: Using LLMs and Affordances for Web Agents - Schmid, Sebastian Josef; Freund, Michael; Harth, Andreas (Knowledge Graphs and Semantic Web, 2025)
We investigate the adaption of agents using plans on the Web despite its large and dynamic nature, as well as agents’ constrained perception. Based on Semantic Web technologies and affordances, we compare how agents choose appropriate actions to adapt to their environment by condition-action rules or suggested actions of large language models. We conduct experiments on execution cost and plan stability distance to see whether agents choose appropriate actions to adapt their plans. We find that cost and stability of rule-based and LLMs for adaptation with affordances are close together, while performance differs great

A Natural Language Interface for IoT Systems Using the Web of Things Abstraction - Gui, Zhou; Freund, Michael; Harth, Andreas (IoT '23: Proceedings of the 13th International Conference on the Internet of Things, 2024)
We present a demo of a Natural Language Interface (NLI) for controlling Internet of Things (IoT) devices using the Web of Things (WoT) specification as an intermediate abstraction layer. All interaction information of a device is stored in a Knowledge Graph using the thing description ontology. The central component of the NLI is a sequence-to-sequence neural network model for text to code translation. We build a data corpus based on the functionalities of a Philips Hue smart lamp and use the corpus to train the text to code model. Our demonstration illustrates how to control the power state, the light colour, and the brightness of a Philips Hue smart lamp using natural language commands. The implementation of an NLI system based on the WoT specification represents an approach towards the development of easy-to-use and interoperable IoT system
Keywords: Human-centered computing; Human computer interaction (HCI); Natural language interfaces; Information systems; Resource Description Framework (RDF)

Applying the Web of Things Abstraction to Bluetooth Low Energy Communication - Freund, Michael; Dorsch, Rene; Harth, Andreas (Connected World & Semantic Interoperability Workshop, 2022)
We apply the Web of Things (WoT) communication pattern, i.e., the semantic description of metadata and interaction affordances, to Internet of Things (IoT) devices that rely on non-IP-based protocols, using Bluetooth Low Energy (LE) as an example. The reference implementation of the WoT Scripting API, node-wot, currently supports only IP-based application layer protocols such as HTTP and MQTT. However, a significant number of IoT devices do not communicate over IP, but via other network layer protocols, e.g. L2CAP used by Bluetooth LE. To leverage the WoT abstraction in Bluetooth Low Energy communication, we specified two ontologies to describe the capabilities of Bluetooth LE devices and transmitted binary data, considered the different interaction possibilities with the Linux Bluetooth stack BlueZ, and due to better documentation, used the D-Bus API to implement Bluetooth LE bindings in JavaScript. Finally, we evaluated the latencies of the bindings in comparison to the BlueZ tool bluetoothctl, showing that the Bluetooth LE bindings are on average about 16 percent slower than the comparison program during connection establishment and about 6 percent slower when disconnecting, but have almost the same performance during reading (about 3 percent slower).<br
Keywords: Web of Things; Internet of Things; Bluetooth Low Energy; Protocol Bindings; Wireless Sensor Networks

A RESTful Interaction Model for Semantic Digital Twins - Schraudner, Daniel; Harth, Andreas (Proceedings of the Third International Workshop on Semantic Digital Twins co-located with the 19th Extended Semantic Web Conference (ESWC 2022), 2022)

A Solid Architecture for Machine Data Exchange with Access Control - Fries, Justus; Freund, Michael; Harth, Andreas (SWoCoT’23: 1st International Workshop on Semantic Web on Constrained Things, 2023)

A Unifying Framework for Agency in Hypermedia Environments - Charpenay, Victor; Käfer, Tobias; Harth, Andreas (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022)
One of the emerging trends in engineering multi-agent systems (MASs) is to use the Web as an environment. On the Web, hypermedia is the guiding principle of agent perception and action. Web standards allows agents to have a single uniform interface to their environment, be it real or simulated. Most recent proposals for hypermedia MASs tend, however, to introduce a coupling between agents or between agents and their environment. This paper introduces a framework based on Semantic Web technologies to formalize interactions between agents and a hypermedia environment. Semantic Web technologies and, more specifically Web ontologies, guarantee interoperability on the Web and maximize uncoupling between components. We show how existing ontologies can be used to make existing MAS prototypes fit our framework. Our framework formalizes the guiding principle of agent-environment interactions in hypermedia, state transfer, with respect to a reference formalism originally introduced by Genesereth and Nilsson. We also show the equivalence between the two in the paper, under certain conditions.
CRIS-Team Scopus Importer:2022-04-08
Keywords: Hypermedia; Linked Data; Multi-agent system; Semantic Web

AuthApp – Portable, Reusable Solid App for GDPR-Compliant Access Granting - Both, Andreas; Kastner, Thorsten; Yeboah, Dustin; Braun, Christoph; Schraudner, Daniel; Schmid, Sebastian Josef; Käfer, Tobias; Harth, Andreas (Web Engineering. 24th International Conference, ICWE 2024, Tampere, Finland, June 17–20, 2024, Proceedings, 2024)
The Solid (Social Linked Data) technology family was developed to provide the foundation for Data Sovereignty in the context of web applications. The advantage of this innovative approach is the opportunity to dynamically bind an identity to a Solid application and a user-specific Solid data store (Solid Pod). These three basic components can be combined dynamically, allowing users to share their data with an application while retaining full control of the data in self-managed Solid Pods. This paper presents a prototype of a web-based user interface to grant access to data in a Solid Pod. To enable a dynamic binding into Solid-driven environments, we made the implementation available as a Solid application – AuthApp – with a specific focus on allowing users to configure the data access granting efficiently. To comply with data protection regulations, in particular Europe’s GDPR, we extended the standard to include the validation of the purpose of data sharing. Unlike previous work, we also make full use of robust technologies to avoid the need to copy or store data outside the personal context, meaning all data remains under the user’s control and so does the AuthApp.<br
Keywords: Solid; Authorization; Access Control; Data Sharing; Access Granting; Zero Trust; Data Sovereignty

Autonomous Agents on the Web (Dagstuhl Seminar 21072) - Boissier, Oliver; Ciortea, Andrei; Harth, Andreas; Ricci, Alessandro (Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021)
The World Wide Web has emerged as the middleware of choice for most distributed systems. Recent standardization efforts for the Web of Things and Linked Data are now turning hypermedia into a homogeneous information fabric that interconnects everything - devices, information resources, abstract concepts, etc. The latest standards allow clients not only to browse and query, but also to observe and act on this hypermedia fabric. Researchers and practitioners are already looking for means to build more sophisticated clients able to meet their design objectives through flexible autonomous use of this hypermedia fabric. Such autonomous agents have been studied to large extent in research on distributed artificial intelligence and, in particular, multi-agent systems. These recent developments thus motivate the need for a broader perspective that can only be achieved through a concerted effort of the research communities on the Web Architecture and the Web of Things, Semantic Web and Linked Data, and Autonomous Agents and Multi-Agent Systems. The Dagstuhl Seminar 21072 on "Autonomous Agents on the Web" brought together leading scholars and practitioners across these research areas in order to support the transfer of knowledge and results - and to discuss new opportunities for research on Web-based autonomous systems. This report documents the seminar’s program and outcomes.<br
Keywords: Web Architecture; Web of Things; Semantic Web; Linked Data; Multi-Agent Systems

Best practices for publishing, retrieving and using spatial data on the web - van den Brink, Linda; Barnaghi, Payam; Tandy, Jeremy; Atemezing, Ghislain; Atkinson, Rob; Cochrane, Byron; Fathy, Yasmin; García Castro, Raúl; Haller, Armin; Harth, Andreas; Janowicz, Krzysztof; Kolozali, Sefki; et al. (Semantic Web, 2019)
Data owners are creating an ever richer set of information resources online, and these are being used for more and more applications. Spatial data on the Web is becoming ubiquitous and voluminous with the rapid growth of location-based services, spatial technologies, dynamic location-based data and services published by different organizations. However, the heterogeneity and the peculiarities of spatial data, such as the use of different coordinate reference systems, make it difficult for data users, Web applications, and services to discover, interpret and use the information in the large and distributed system that is the Web. To make spatial data more effectively available, this paper summarizes the work of the joint W3C/OGC Working Group on Spatial Data on the Web that identifies 14 best practices for publishing spatial data on the Web. The paper extends that work by presenting the identified challenges and rationale for selection of the recommended best practices, framed by the set of principles that guided the selection. It describes best practices that are employed to enable publishing, discovery and retrieving (querying) spatial data on the Web, and identifies some areas where a best practice has not yet emerged.<br
Keywords: Geographic information systems; spatial data; Web technologies; World Wide Web; W3C; Open Geospatial Consortium; OGC

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

Building a Knowledge Graph with Inference for a Production Machine Using the Web of Things Standard - Meckler, Sascha; Steinmüller, Harald; Harth, Andreas (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021)
This paper presents an architecture for a knowledge-based system (KBS) that consists of a Knowledge Graph, an inference engine and services. The Web of Things standard is used to translate sensor data from a production machine into an RDF graph. The KBS architecture is implemented for a physical twin of a real machine using open-source Semantic Web technologies. The performance evaluation of the system reveals limitations for the application in production.
CRIS-Team Scopus Importer:2021-08-27
Keywords: Digital Twin; Knowledge Graph; Web of Things

Constructing demand-driven wikidata subsets? - Henselmann, Daniel; Harth, Andreas (CEUR Workshop Proceedings, 2021)
A Wikidata subset is a selected subset from the set of all triples included in Wikidata. We approach the task to create a subset with a demand-based subset that satises a present use case. The introduced algorithm constructs triples in multiple steps starting from a seed of URIs. Dierent input options for the seed, the sequence of construction steps, and a filter enable adaptations to the use case. A formal description and matching SPARQL queries complement the algorithm. Hospital data provides a running example.
CRIS-Team Scopus Importer:2021-11-05
Keywords: Neighbourhood; Subgraph; Subset; Wikidata

DALI: A Decentralized, Agent-Based Approach for Adaptive Manufacturing Using Local Information - Schmid, Sebastian Josef; Harth, Andreas (ACM SIGAPP Applied Computing Review, 2024)
We study how decentralized multi-agent systems adapt on local data in dynamic environments. In this extension of our earlier work, we build on our original setting of a driverless transportation system for a manufacturing scenario with Autonomous Guided Vehicles (AGVs) to include not only disturbances, but also perception and communication errors that hinder the information sharing of agents. We analyze how well the decentralized MAS can correct these errors, where corrections come from, how the errors impact the performance, and consider the communication efficiency among the MAS populatio

Data-Sovereign Enterprise Collaboration using the Solid Protocol - Kastner, Thorsten; Braun, Christoph; Both, Andreas; Yeboah, Dustin; Schmid, Sebastian Josef; Schraudner, Daniel; Kaefer, Tobias; Harth, Andreas (20th International Conference on Semantic Systems (SEMANTICS'24), 2024)
We demonstrate a system architecture for seamless and sovereign business-to-business (B2B) data sharing using the Solid Protocol. We highlight two core system components: The Rights Delegation Proxy allows organizations to internally manage and enforce access policies on requests from their employees to external data providers. The Data Provision Proxy allows organizations to share data from an external data provider in a privacy-preserving manner. Organizations define and enforce the policies for internal and external data sharing themselves, thereby maintaining sovereignty in enterprise collaboratio

Decentralized Self-Adaption With Epidemic Algorithms for Agent-Based Transportation - Schmid, Sebastian Josef; Harth, Andreas (Proceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops, ICDCSW 2022, 2022)
We investigate epidemic algorithms to enable agent-based transporters to be self-adaptive to disturbances and avoid centralized communication mechanisms. We conduct simulation experiments of a shop floor to compare the ability of mobile agents with limited perception to deliver items and adapt to a randomly disturbed environment by communicating decentralized with epidemic algorithms, and centralized via blackboard and direct messages. For evaluation of their adaption, we measure their task performance and communication efficiency. We conclude that agent-based transportation with epidemic algorithms can self-adapt to a disturbed environment, can still perform close to centralized ones, and avoid monolithic components.
Created from Fastlane, Scopus look-up
Keywords: Decentralization; Disturbance; Epidemic Algorithms; Multi-agent system; Transportation

Design and Implementation of a Natural Language Interface for Controlling the Web of Things Devices - Gui, Zhou; Kuty, Layla; Harth, Andreas (Natural Language Processing and Information Systems, 2024)
We present a systematic workflow for developing a Natural Language Interface (NLI) using Knowledge Graphs (KGs) and the Web of Things (WoT) specification as an abstraction layer. We first synthesize a data corpus from a given device interface description using manually created templates and parameter sheets. Then we paraphrase the synthesized data corpus with pre-trained Large Language Models (LLMs). The resulting corpus serves as training data for a text-to-code encoder- decoder neural network model, enabling the mapping of diverse natural language commands into an executable code format. To the best of our knowledge, no existing data corpus or NLI system has been tailored for WoT device interactions. Our work provides a baseline and can be ex- tended to a broader range of real world WoT use cases.
Keywords: Natural Language Interface; Knowledge Graphs; Large Language Models; Web of Things

Distributed Fault Detection For Multi-Agent Systems Based On Vertebrate Foraging - Schmid, Sebastian Josef; Harth, Andreas (Proceedings of the Adaptive and Learning Agents Workshop (ALA 2023), 2023)

Enabling Adaptation in Dynamic Manufacturing Environments with Decentralized Agent-Based Systems and Local Perception - Schmid, Sebastian Josef; Harth, Andreas (SAC '24: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024)
Modern industrial landscapes, like Industry 4.0, pose a formidable challenge: how to maintain high-performance levels in dynamic manufacturing environments while minimizing downtime for adaption? Control systems have to be capable of making real-time decisions between adaptation and task fulfillment yet to external, changing production goals. Centralized control systems promise ideal decisions based on global data, but need clean and extensive data. Decentralized multi-agent systems (MAS) instead may decide on local data, yet, the efficiency of decentralized MAS to adapt in dynamic manufacturing settings remains largely unexplored. Thus, we study the potential of a MAS of decentralized agents characterized by adapting exclusively with local information, in addressing the challenges posed by dynamic manufacturing environments. We illustrate the problem using a driverless transportation system for a manufacturing scenario where a control system guides Autonomous Guided Vehicles (AGVs) in response to unforeseen disturbances and unknown product transportation tasks. We compare the decentralized MAS approach to an omniscient centralized control system, measure the performance of both systems and consider the communication efficiency among the MAS population. We show that decentralized agents with local information can adapt efficiently and shed light on their effectiveness in dynamic environments.<br
Keywords: Dynamic Environment; Autonomous Guided Vehicles; Multi-Agent System; Self-Adaption; Intralogistics

Enriching integrated statistical open city data by combining equational knowledge and missing value imputation - Bischof, Stefan; Harth, Andreas; Kämpgen, Benedikt; Polleres, Axel; Schneider, Patrik (Journal of Web Semantics, 2018)
Several institutions collect statistical data about cities, regions, and countries for various purposes. Yet, while access to high quality and recent such data is both crucial for decision makers and a means for achieving transparency to the public, all too often such collections of data remain isolated and not re-usable, let alone comparable or properly integrated. In this paper we present the Open City Data Pipeline, a focused attempt to collect, integrate, and enrich statistical data collected at city level worldwide, and re-publish the resulting dataset in a re-usable manner as Linked Data. The main features of the Open City Data Pipeline are: (i) we integrate and cleanse data from several sources in a modular and extensible, always up-to-date fashion; (ii) we use both Machine Learning techniques and reasoning over equational background knowledge to enrich the data by imputing missing values, (iii) we assess the estimated accuracy of such imputations per indicator. Additionally, (iv) we make the integrated and enriched data, including links to external data sources, such as DBpedia, available both in a web browser interface and as machine-readable Linked Data, using standard vocabularies such as QB and PROV. Apart from providing a contribution to the growing collection of data available as Linked Data, our enrichment process for missing values also contributes a novel methodology for combining rule-based inference about equational knowledge with inferences obtained from statistical Machine Learning approaches. While most existing works about inference in Linked Data have focused on ontological reasoning in RDFS and OWL, we believe that these complementary methods and particularly their combination could be fruitfully applied also in many other domains for integrating Statistical Linked Data, independent from our concrete use case of integrating city data.<br
Keywords: open data; linked data; data cleaning; data integration

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

FAIR Internet of Things Data: Enabling Process Optimization at Munich Airport - Freund, Michael; Rott, Julian; Dorsch, Rene; Harth, Andreas (21st Extended Semantic Web Conference (ESWC2024), 2024)
We present how data collected from Internet of Things (IoT) devices adhering to the FAIR data principles forms the foundation for data analytics applications at Munich Airport. We describe how the collected IoT data is annotated, how our APIs are structured, present two data analytics applications currently in use to analyze FAIR IoT data for process optimization, and share lessons learned.<br
Keywords: FAIR data principles; Internet of Things; Solid

Finding Root Causes for Outliers in Semantically Annotated Sensor Data - Strobel, Tim; Pychynski, Tim; Harth, Andreas (Extended Semantic Web Conference, 2024)
Causal inference creates insights into observational data. Such insights could explain an outlying value to perform Root Cause Analysis. But how can causal inference be used with semantically annotated observations? The following demo showcases how to use semantically annotated sensor data for causal inference. The method’s implementation uses an agent pattern interacting with a knowledge grap

FlexRML: A Flexible and Memory Efficient Knowledge Graph Materializer - Freund, Michael; Schmid, Sebastian Josef; Dorsch, Rene; Harth, Andreas (21st Extended Semantic Web Conference (ESWC2024), 2024)
We present FlexRML, a flexible and memory efficient software resource for interpreting and executing RML mappings. As a knowledge graph materializer, FlexRML can operate on a wide range of systems, from cloud-based environments to edge devices, as well as resourceconstrained IoT devices and real-time microcontrollers. The primary goal of FlexRML is to balance memory efficiency with fast mapping execution. This is achieved by using C++ for the implementation and a result size estimation algorithm that approximates the number of N-Quads generated and, based on the estimate, optimizes bit sizes and data structures used to save memory in preparation for mapping execution. Our evaluation shows that FlexRML’s adaptive bit size and data structure selection results in higher memory efficiency compared to conventional methods. When benchmarked against state-of-the-art RML processors, FlexRML consistently shows lower peak memory consumption across different datasets while delivering faster or comparable execution time
Keywords: Knowledge Graph Construction; RML; Internet of Things

FusE: Entity-Centric Data Fusion on Linked Data - Thoma, Steffen; Thalhammer, Andreas; Harth, Andreas; Studer, Rudi (Acm Transactions on the Web, 2019)
Many current web pages include structured data which can directly be processed and used. Search engines, in particular, gather that structured data and provide question answering capabilities over the integrated data with an entity-centric presentation of the results. Due to the decentralized nature of the web, multiple structured data sources can provide similar information about an entity. But data from different sources may involve different vocabularies and modeling granularities, which makes integration difficult. We present FusE, an approach that identifies similar entity-specific data across sources, independent of the vocabulary and data modeling choices. We apply our method along the scenario of a trustable knowledge panel, conduct experiments in which we identify and process entity data from web sources, and compare the output to a competing system. The results underline the advantages of the presented entity-centric data fusion approach.<br

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

Impact of Knowledge Graph Representations on Question Answering with Language Models - Henselmann, Daniel; Dorsch, Rene; Harth, Andreas (3rd Workshop on Hybrid Artificial Intelligence and Enterprise Modelling, 2025)
Keywords: Question answering; Knowledge graphs; Large language models; Knowledge representation

MOSAIK: A Formal Model for Self-Organizing Manufacturing Systems - Charpenay, Victor; Schraudner, Daniel; Seidelmann, Thomas; Spieldenner, Torsten; Weise, Jens; Schubotz, Rene; Mostaghim, Sanaz; Harth, Andreas (IEEE Pervasive Computing, 2020)
In this article, we review past and current system architectures displaying self-organization in the domain of manufacturing. Based on a corpus of 84 reference papers, we find that multiagent systems (MAS) play a significant role in self-organization, especially MAS featuring bio-inspired algorithms for agent coordination. The emergence of new classes of cyber-physical systems further strengthens the prevalence of MAS on the subject. As outcome of our review, we devise the MOSAIK model, a generic model synthesizing all system architectures found in our corpus. The MOSAIK model can be used as a reference for formally comparing distinct architectures. We also use it to identify gaps for future research on self-organizing manufacturing systems. The model includes the central concepts of Agent and Artifact, which suggest that the Web is an adequate communication infrastructure for modern manufacturing systems: Agents become (autonomous) Web Agents and Artifacts become resources exposed by Web servers.
Created from Fastlane, Scopus look-up
Keywords: Biological system modeling; Complexity theory; Computer architecture; Manufacturing; Optimization; Unified modeling language; Workstations

MOSAIK: An Agent-Based Decentralized Control System with Stigmergy for a Transportation Scenario - Schmid, Sebastian Josef; Schraudner, Daniel; Harth, Andreas (2023)
We investigate possibilities for implementing the decentralized control of transporters with Semantic Web agents to fulfill a given transportation task. We present the MOSAIK framework as a system to build and simulate agents to control transporters using stigmergy for communication, and self-organize based on local decisions. Our framework uses Semantic Web technologies because the communication paradigm of stigmergy directly maps to the REST constraints of the application architecture of the web. The system achieves self-organization by implementing a combination of simple reflex web agents that coordinate using web resources as environment for stigmergy. Finally, we evaluate our system compared to an agent-based simulation and discuss requirements of decentralized systems on the Semantic Web using stigmergy.<br

N3X: Notation3 with SPARQL Expressions - Farnbauer-Schmidt, Matthias; Charpenay, Victor; Harth, Andreas (The Semantic Web: ESWC 2020 Satellite Events, 2020)
Writing calculations with many intermediate steps in Notation3 (N3) rules is complex and verbose. This issue is addressed by extending N3 with SPARQL expressions. In this paper, we introduce and evaluate the syntax of this approach, called N3X. In our examples N3X reduces the number of triples in calculation heavy N3 rules by 30%, the number of triples with a math:*-predicate by 65% and the number of non-blank characters by 24.4% on average.<br
Keywords: Notation3; N3X; SPARQL expressions

Open Information Extraction on German Wikipedia Texts - Klose, Christian; Gui, Zhou; Harth, Andreas (CEUR Workshop Proceedings (CEUR-WS), 2022)
Knowledge Graphs are becoming a fundamental building block for semantic search and voice assistants. This paper deals with the automated Knowledge Graph Construction from unstructured data. Predominantly, the focus is on Open Information Extraction (Open IE), an unsupervised learning approach that attempts to extract triples from plain text independent of their domain. Hence, it is the first step towards automated Knowledge Graph Construction. Previous work mainly applied Open IE to English texts. In this paper, the focus is on German texts. Due to the lack of German Open Information Extraction datasets, a dataset on the basis of Wikipedia is created. Two Open Information Extraction Systems for German are introduced. Finally, the performance of the systems are evaluate
Keywords: Open Information Extraction; Natural Language Processing; Knowledge Graph Construction

Performance Comparison of Simple Reflex Agents Using Stigmergy with Model-Based Agents in Self-Organizing Transportation - Schmid, Sebastian Josef; Schraudner, Daniel; Harth, Andreas (2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), 2021)
Multi-agent systems utilizing simple reflex agents are assumed to have a significant competitive disadvantage when compared to more sophisticated agent-based approaches. However, in terms of resilience and adaptivity, this simple design turns out be an advantage when used together with stigmergy. In this paper we show that simple reflex agents that use stigmergy, are fit and flexible enough to outperform rivaling model-based agents in a disturbed transportation setting that simulates a dynamic, real-world industrial shop floor, and have a performance closer to a centralized, monolithic approach which we compare to as gold standard. This leads to opportunities for simpler, but nevertheless more robust agent design for self-organizing, decentralized multiagent approaches just by sharing knowledge of the world and exploiting their environment.

Performance Results of FlexRML in the KGCW Challenge 2024 - Freund, Michael; Schmid, Sebastian Josef; Dorsch, Rene; Harth, Andreas (Fifth International Workshop on Knowledge Graph Construction@ ESWC2024, 2024)
The Knowledge Graph Construction Workshop introduced a challenge to evaluate the performance metrics of different RML interpreters using a set of standardized benchmarks. We participated in the challenge's performance track with our RML interpreter, FlexRML, and report the median execution time and peak memory consumption over five runs on the provided virtual machine using the challenge tool. Through this challenge, we were able to identify weaknesses in FlexRML, such as its current support for CSV data only, lack of support for the latest RML vocabulary, and a crash that occurs when the system executing the mapping runs out of memory. These are issues that we plan to address in future releases of FlexRM

Proceedings of the All the Agents Challenge (ATAC 2021) co-located with the 20th International Semantic Web Conference (ISWC 2021) - Käfer, Tobias; Harth, Andreas; Ciortea, Andrei; Charpenay, Victor (2021)

Realizing New Data-Driven Business Models by Launching Containers into the Cloud - Zink, Mathias; Naumann, Victor; Harth, Andreas; Pflaum, Alexander (Digital Business Models in Industrial Ecosystems, 2021)
Data-driven business models are modern ways for innovation in traditional environments. The vision of the Internet of Things (IoT), by making products smart and leveraging the data into services, is a modern paradigm of value creation. A representative case study evolved business models for industrial containers in the automotive industry into a cloud-based data-driven business model. This publication outlines the background for industrial containers and provides insights into the relevant technological architectures. Additionally, the data-driven business model and the expansion of the ecosystem are outlined. Thereby this publication enhances the necessary interdisciplinary understanding of business model research and information science.<br

Rule-based Programming of User Agents for Linked Data - Käfer, Tobias; Harth, Andreas (WWW2018 Workshop on Linked Data on the Web (LDOW2018), 2018)
While current Semantic Web languages and technologies are wellsuited for accessing and integrating static data, methods and technologies for the handling of dynamic aspects – required in many modern web environments – are largely missing. We propose to use Abstract State Machines (ASMs) as the formal basis for dealing with changes in Linked Data, which is the combination of the Resource Description Framework (RDF) with the Hypertext Transfer Protocol (HTTP). We provide a synthesis of ASMs and Linked Data and show how the combination aligns with the relevant specifications such as the Request/Response communication in HTTP, the guidelines for updating resource state in the Linked Data Platform (LDP) specification, and the formal grounding of RDF in model theory. Based on the formalisation of Linked Data resources that change state over time, we present the syntax and operational semantics of a small rule-based language to specify user agents that use HTTP to interact with Linked Data as the interface to the environment. We show the feasibility of the approach in an evaluation involving the specification of automation in a Smart Building scenario, where the presented approach serves as a theoretical foundation.<br

SaVeWoT: Scripting and Verifying Web of Things Systems and Their Effects on the Physical World - Fries, Justus; Freund, Michael; Harth, Andreas (KI 2024: Advances in Artificial Intelligence, 2024)
We introduce SaVeWoT (Scripting and Verifying Web of Things Systems), an approach for designing, formally verifying, and deploying decentralized control systems based on the W3C WoT. SaVeWoT consists of two main parts: the SaVeWoT language and the SaVeWoT compiler. The SaVeWoT language models devices (i.e., Things), controllers that orchestrate Things, virtual composite Things (i.e., subsystems consisting of multiple Things), interactions between these components, and their effects on the physical world. The SaVeWoT compiler uses Thing Descriptions (TDs) and SaVeWoT behavior descriptions along with correctness specifications in Linear-time Temporal Logic (LTL) to automatically generate a Promela model, which is validated using the SPIN model checker. We demonstrate the feasibility of the SaVeWoT approach by verifying a conveyor belt system as an example and conducting an empirical evaluation.<br
Keywords: Web of Things; Static Verification; Safety

Solid Proof of Concept in an Enterprise Loan Request Use Case - Henselmann, Daniel; Kolinsky, Karina; Schmid, Sebastian Josef; Schraudner, Daniel; Both, Andreas; Harth, Andreas (Proceedings of Poster and Demo Track and Workshop Track of the 18th International Conference on Semantic Systems co-located with 18th International Conference on Semantic Systems (SEMANTiCS 2022), 2022)
Keywords: Read/Write Linked Data; Enterprise Data Exchange; WebID; Solid

Specifying, Monitoring, and Executing Workflows in Linked Data Environments - Käfer, Tobias; Harth, Andreas (International Semantic Web Conference 2018 (ISWC 2018), 2018)
We present an ontology for representing workflows over components with Read-Write Linked Data interfaces and give an operational semantics to the ontology via a rule language. Workflow languages have been successfully applied for modelling behaviour in enterprise information systems, in which the data is often managed in a relational database. Linked Data interfaces have been widely deployed on the web to support data integration in very diverse domains, increasingly also in scenarios involving the Internet of Things, in which application behaviour is often specified using imperative programming languages. With our work we aim to combine workflow languages, which allow for the high-level specification of application behaviour by non-expert users, with Linked Data, which allows for decentralised data publication and integrated data access. We show that our ontology is expressive enough to cover the basic workflow patterns and demonstrate the applicability of our approach with a prototype system that observes pilots carrying out tasks in a virtual reality aircraft cockpit. On a synthetic benchmark from the building automation domain, the runtime scales linearly with the size of the number of Internet of Things devices.<br

Spezifikation, Ausführung und Monitoring von Workflows in verteilten Wissensgraphen (Abstract) - Käfer, Tobias; Harth, Andreas (INFORMATIK 2020, 2021)

Spezifikation, Ausführung und Monitoring von Workflows in verteilten Wissensgraphen - Käfer, Tobias; Harth, Andreas (INFORMATIK 2020, 2020)
Während BPM-Systeme typischerweise Web-Service-Schnittstellen annehmen, auf welchen Daten im Datenmodell XML übertragen werden, haben sich im Web REST-APIs etabliert, auf welchen Daten in anderen Datenmodellen übertragen werden, beispielsweise Wissensgraphen in RDF. Diese Kombination von RDF mit REST wird in der Literatur häufig mit Read-Write-Linked-Data[Be09] bezeichnet, wobei man Linked Data auch als verteilten Wissensgraphen ansehen kann. Die Systemumgebung Read-Write-Linked-Data unterscheidet sich fundamental von den Annahmen über die Systemumgebung traditioneller BPM-Systeme, da Read-Write-Linked-Data (1) nicht auf der Annahme der Weltabgeschlossenheit (Closed-World Assumption) basiert und (2) ohne Ereignisdaten arbeitet, da Read-Write-Linked-Data auf dem Architekturstil REST basiert. Komponenten mit Read-Write-Linked-Data-Schnittstellen finden sich beispielsweise im kürzlich standardisierten Web der Dinge[Kä20]; durch entsprechendes Lifting der Daten nach RDF kann man auch REST-basierte Microservices [Ne15] als Read-Write-Linked-Data anspreche
Keywords: Linked Data; REST; RDF; workflow

Stream Containers for Resource-oriented RDF Stream Processing - Schraudner, Daniel; Harth, Andreas (Stream Reasoning Workshop, 2021)
We introduce Stream Containers inspired by the Linked Data Platform as an alternative way to process RDF streams. A Stream Container represents a single RDF data stream that can be accessed in a resource-oriented way which allows for better interoperability with the existing Semantic Web infrastructure. Stream Containers are managed by webservers that are responsible for implementing the S2R operator, i.e. calculating the window for their clients. The clients on the other hand can use a standard SPARQL processor in combination with HTTP request to do RDF processing. Query results can be converted back to an RDF stream (R2S operator) by posting the data to a Stream Container. Our approach of resource-oriented RDF stream processing can lead to better distribution of load and thus to a better worldwide scalability. We give a general overview of the proposed architecture as well as the formal semantics of the overall syste
Keywords: RDF Stream Processing; Stream Reasoning; Linked Data Platform; Resource-Oriented; REST

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

TGDK, Volume 2, Issue 1, Complete Issue - Harth, Andreas; Kaefer, Tobias; Rula, Anisa; Calbimonte, Jean-Paul; Kamburjan, Eduard; Giese, Martin (Transactions on Graph Data and Knowledge, 2024)
We work towards a vocabulary to represent processes and temporal logic specifications as graph-structured data. Different fields use incompatible terminologies for describing essentially the same process-related concepts. In addition, processes can be represented from different perspectives and levels of abstraction: both state-centric and event-centric perspectives offer distinct insights into the underlying processes. In this work, we strive to unify the representation of processes and related concepts by leveraging the power of knowledge graphs. We survey approaches to representing processes and reasoning with process descriptions from different fields and provide a selection of scenarios to help inform the scope of a unified representation of processes. We focus on processes that can be executed and observed via web interfaces. We propose to provide a representation designed to combine state-centric and event-centric perspectives while incorporating temporal querying and reasoning capabilities on temporal logic specifications. A standardised vocabulary and representation for processes and temporal specifications would contribute towards bridging the gap between the terminologies from different fields and fostering the broader application of methods involving temporal logics, such as formal verification and program synthesi
Keywords: Process modelling; Process ontology; Temporal logic; Web services

Theories about World Representations for the Internet of Things - Färber, Michael; Svetashova, Yulia; Harth, Andreas (Workshop on Concepts in Action: Representation, Learning, and Application (CARLA), 2018)

Theories of Meaning for the Internet of Things - Färber, Michael; Svetashova, Yulia; Harth, Andreas (Concepts in Action: Representation, Learning, and Application, 2021)
Färber, Svetashova, and Harth’s contribution “Theories of Meaning for the Internet of Things” (Chap. 3) is concerned with the representation of concepts in the context of the Internet of Things (IoT) from the perspective of artificial intelligence. They compare different representational frameworks from philosophy and computer science, taking a simple smart home setting as an application example. Overall, they consider four different approaches, namely model-theoretic semantics (which are based on first-order logic), possible world semantics (using modal logic), situation semantics, and cognitive and distributional semantics (i.e., spatial models of meaning). With the IoT application in mind, the authors assess whether these representational frameworks are able to represent intersubjectivity (i.e., multiple agents) and dynamics (i.e., changes in the state of the world) and to what extent they can be connected to perception. The authors conclude that none of the existing approaches is able to completely satisfy all three requirements. They propose to further investigate a combination between situational and distributional semantics as a promising avenue for future research.

Theories of Meaning for the Internet of Things - Färber, Michael; Svetashova, Yulia; Harth, Andreas (Concepts in Action - Representation, Learning, and Application, 2021)

The Rights Delegation Proxy: An Approach for Delegations in the Solid Dataspace - Schmid, Sebastian Josef; Schraudner, Daniel; Harth, Andreas (Proceedings of the Second International Workshop on Semantics in Dataspaces (SDS 2024) co-located with the 21st Extended Semantic Web Conference (ESWC 2024), 2024)

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

The Web and Linked Data as a Solid Foundation for Dataspaces - Meckler, Sascha; Dorsch, Rene; Henselmann, Daniel; Harth, Andreas (ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023, 2023)
The concepts for dataspaces range from database management systems to cross-company platforms for data and applications. In this short paper, we present the "Solid Data Space"(SDS), a concept for dataspaces that build on top of the (Semantic) Web and Social Linked Data (Solid). Existing Web technologies and Linked Data principles form the foundation for open, decentralized networks for sovereign data exchange between citizens, organizations and companies. Domain-specific dataspace implementations can extend the agreements for communication and collaboration to enable specific functionality. We compare the SDS with principles and components of the emerging International Data Spaces to identify similarities and point out technological differences.
Created from Fastlane, Scopus look-up
Keywords: Dataspace; International Data Spaces; Social Linked Data (Solid)

Towards a Data Driven Natural Language Interface for Industrial IoT Use Cases - Gui, Zhou; Harth, Andreas (Proceedings of the 2021 IEEE International Conference on Human-Machine Systems, ICHMS 2021, 2021)
The ubiquitous availability of sensors and smart devices makes IoT networks more and more complex to manage and control. A natural language interface (NLI) would allow users to interact with the devices via human language by translating the user command into a machine-interpretable meaning representation, often called logical forms.Despite the rapid development of conversational interfaces in smart home and personal intelligent assistant use cases, there are limited research and applications in industrial sensor and actuator networks, usually referred to as Industrial Internet of Things (IIoT). In this paper, we show an early phase design principle of a semantic representation to express IIoT device interactions and propose a data-focused workflow of IIoT automation system architecture.
CRIS-Team Scopus Importer:2021-11-19
Keywords: Industrial Internet of Things; Knowledge Graph; Natural Language Interface; Semantic Representation

Towards Modeling the Structure of Product Dependencies in Supply Networks to Identify Bottlenecks Among Suppliers - Henselmann, Daniel; Harth, Andreas (Proceedings of the Third International Workshop on Linked Data-driven Resilience Research (D2R2’24) co-located with European Semantic Web Conference 2024 (ESWC 2024), 2024)
This paper introduces an ontology-based approach to model supply networks aimed at identifying bottlenecks among suppliers. Considering concepts from existing ontologies, we develop a concise ontology to represent the structure of supply networks, focusing on products and their derivational dependencies. We compare our ontology to PRONTO, a heavyweight ontology with a similar scope, demonstrating its reduced complexity while retaining sufficient modeling capabilities. Reduced expressiveness in some product cases due to the abstraction of product variants is a limitation. Further work is needed on network metrics and measures to identify bottlenecks.<br
Keywords: supply network; bottlenecks; graph model; ontology

Towards Semantic Model Extensibility in Interoperable IoT Data Exchange Platforms - Svetashova, Yulia; Schmid, Stefan; Harth, Andreas (Interoperability and Open-Source Solutions for the Internet of Things (InterOSS-IoT 2018), 2018)

Towards Solid-Based B2B Data Value Chains - Both, Andreas; Yeboah, Dustin; Kastner, Thorsten; Schraudner, Daniel; Schmid, Sebastian Josef; Braun, Christoph; Harth, Andreas; Käfer, Tobias (Springer, 2025)
In the paper, we describe the data sharing within a data-driven B2B ecosystem using Solid technologies. Using a real-world use case, we describe our approach and implementation, as well as the (previously non-existent) referencing of a purpose ontology to fully express the intended use of shared data in a machine-readable and analyzable form. We follow the intention of establishing a safe, robust, and traceable linked-data-driven B2B ecosystem based on Solid, where high standards of data privacy and thriftiness have to be me
Keywords: Solid; Data Value Chains; Zero Trust; Data Sovereignty

Tutorial: Distributed Knowledge Graphs for the Web of Things - Käfer, Tobias; Harth, Andreas (ACM International Conference Proceeding Series, 2020)
Knowledge Graph technologies from the Semantic Web and Linked Data stack can help to address the interoperability problem on the Internet of Things and to realise the vision of an interlinked Web of Things. The tutorial covers methods and approaches that allow for data integration on the Internet of Things with a focus on dynamics, distribution, and control.
CRIS-Team Scopus Importer:2020-12-11

Tutorial: Linked Data Techniques for the Web of Things - Harth, Andreas; Kaefer, Tobias (PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON THE INTERNET OF THINGS (IOT'18), 2018)
CRIS-Team WoS Importer:2019-02-22

WireGraph - Entwicklung eines Lernspiels mit Prosumentenumgebung zur Förderung der fachlichen und digitalen Kompetenz von Wirtschaftsstudierenden - Fleiner, Christian; Grümmer, Julian; Zvekan, Goran; Harth, Andreas (INFORMATIK 2021 - Computer Science & Sustainability, 2021)
Die Europäische Kommission warnt davor, dass die Entwicklung der Digitalisierung unzureichend in der Hochschullehre beachtet wird. Vielen Absolventen:innen mangelt es an digitaler Kompetenz. Dem steht gegenüber, dass die digitalen Anforderungen auf dem Arbeitsmarkt stetig wachsen. Dies gilt auch für Berufe des Finanzbereichs. Um die Vermittlung von digitaler Kompetenz in die Lehre miteinzubinden, eignet sich das von der Europäischen Kommission vorgeschlagene Referenzmodell der digitalen Kompetenz. Es besteht allerdings ein großer Forschungsbedarf, wie das Referenzmodell explizit in die Lehre übertragen werden kann. In diesem Beitrag wird das Konzept des Lernspiels WireGraph vorgestellt, mit dem Studierende der Wirtschaftswissenschaften die Arbeit mit Wissensgraphen erlernen, um den Wirecard-Skandal aufzuarbeiten. Dazu wird eine Prosumentenumgebung gestellt, mit der der Kompetenzbereich Erstellung digitaler Inhalte des Referenzmodells vollständig und über alle Leistungsniveaus hinweg vermittelt wird. Dabei erlernen Studierende nicht nur die Grundlagen von RDF und SPARQL, sondern können diese auch gezielt für ihre Ideen und weiteres Fachwissen einsetzen.<br
CRIS-Team Scopus Importer:2024-12-16
Keywords: Audit; Big Data; DigComp; Digitalisierung; Educational Game; Interaktive Lehre; Linked Data; Prosument; Wissensgraph; Wirecard

WireGraph - Entwicklung eines Lernspiels mit Prosumentenumgebung zur Förderung der fachlichen und digitalen Kompetenz von Wirtschaftsstudierenden - Fleiner, Christian; Grümmer, Julian; Zvekan, Goran; Harth, Andreas (INFORMATIK 2021 Computer Science & Sustainability, 2021)
Die Europäische Kommission warnt davor, dass die Entwicklung der Digitalisierung unzureichend in der Hochschullehre beachtet wird. Vielen Absolventen:innen mangelt es an digitaler Kompetenz. Dem steht gegenüber, dass die digitalen Anforderungen auf dem Arbeitsmarkt stetig wachsen. Dies gilt auch für Berufe des Finanzbereichs. Um die Vermittlung von digitaler Kompetenz in die Lehre miteinzubinden, eignet sich das von der Europäischen Kommission vorgeschlagene Referenzmodell der digitalen Kompetenz. Es besteht allerdings ein großer Forschungsbedarf, wie das Referenzmodell explizit in die Lehre übertragen werden kann. In diesem Beitrag wird das Konzept des Lernspiels WireGraph vorgestellt, mit dem Studierende der Wirtschaftswissenschaften die Arbeit mit Wissensgraphen erlernen, um den Wirecard-Skandal aufzuarbeiten. Dazu wird eine Prosumentenumgebung gestellt, mit der der Kompetenzbereich Erstellung digitaler Inhalte des Referenzmodells vollständig und über alle Leistungsniveaus hinweg vermittelt wird. Dabei erlernen Studierende nicht nur die Grundlagen von RDF und SPARQL, sondern können diese auch gezielt für ihre Ideen und weiteres Fachwissen einsetzen.<br
Keywords: Audit; Big Data; DigComp; Digitalisierung; Educational Game; Interaktive Lehre; Linked Data; Prosument; Wissensgraph; Wirecard

WoT2Pod: An Architecture enabling an Edge-to-Cloud Continuum - Freund, Michael; Fries, Justus; Dorsch, Rene; Schiller, Peter; Harth, Andreas (The International Conference on the Internet of Things, 2023)
We present WoT2Pod, an architecture that provides a uniform API for data access and control of IoT devices at the edge and in the cloud, creating a seamless continuum between these environments. The uniform API is based on Resource Description Framework (RDF) graphs, Linked Data Platform (LDP) containers, and HTTP. The API is created by a middleware that uses the Web of Things to interact with devices, maps collected IoT data to RDF, provides the most recent data at the edge, and stores data for long-term storage and sharing with third parties in a Solid Pod in the cloud layer. We establish a formalism and derive equations for predicting la- tency, and use them to evaluate different polling and pushing-based methods for exchanging data between components. Our results underscore that interactions at the edge are consistently faster than those in the cloud, with data access 65% faster and device control 70% faster. We found that a strategy that relies entirely on pushing data provides the most optimal latency results.<br
Keywords: Internet of Things; Web of Things; Solid Project; Architecture