This article introduces foundational components for decentralized B2B data sharing based on the solid protocol, emphasizing data sovereignty, security, and interoperability. These components are: (1) Authorization app (AuthApp) – facilitating granular control and compliance in access granting and revocation processes; (2) rights delegation proxy (RDP) – supporting controlled delegation of rights, enabling natural persons to act on behalf of organizations while ensuring privacy and traceability; (3) data provisioning proxy (DPP) – allowing seamless and secure data provisioning across organizations while masking the identity of upstream data sources to protect business interests. The components enable the creation of end-to-end, standards-based, flexible data value chains. We validate their applicability through a real-world financial services use case involving loan processing, which illustrates data sharing and protection challenges in B2B ecosystems.

The Internet of Things has created the need for scalable, distributed detection of complex events across organizational boundaries. We present a RESTful architecture that enables distributed detection of complex events on streams of Linked Data. Our approach transforms declarative event patterns expressed in a DatalogMTL-based temporal logic formalism into a network of stream containers and reasoning agents that can operate across organizational boundaries. Key contributions include: (1) A modular architecture based on the Linked Data Platform for federated stream processing, (2) A method for transforming declarative patterns into executable components, (3) A formal model using Colored Stochastic Petri Nets to validate correctness and analyze performance, and (4) an implementation and experimental validation of our approach. Experimental results demonstrate that our system achieves high throughput through parallel processing while maintaining a predictable latency that scales linearly with program depth.

This work evaluates the capabilities of Large Language Models (LLMs) in semantic reasoning tasks. We construct a knowledge graph that represents a real-world Internet of Things (IoT) environment and define various reasoning rules for device identification use cases. We test the performance of three LLMs: Llama-3.1, Qwen-2.5, GPT4o, based on different levels of fine-grained rule descriptions in the input context and the increasing rule complexity. We use a rule-based reasoner, Apache Jena, to generate the ground truth data for each reasoning rule. The results show that while LLMs are effective in retrieving direct links in the knowledge graph, they struggle with highly customized, complex reasoning rules involving multiple triple patterns. This work provides an application and a baseline for using LLMs to enable semantic reasoning for device identification in IoT environments.

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 met.

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 collaboration.

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.

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.

Social Linked Data (Solid) origins from the idea of a decentralized social Web with separated data, identities, and applications. This demo provides a proof of concept to show the usability of the Solid specifications in an enterprise data exchange scenario. The loan request of a company via a tax accountant serves as the use case.

We provide a formal model based on extended state machines (EFSMs) with the addition of so-called admissibility functions to describe the state changes of an asset for interactions between HTTP agents and the asset by using the abstraction of properties, actions, and events. Furthermore, we describe the RESTful interface for assets that can be derived from EFSMs to offer assets’ interactions in a clearly defined way and based on established standards. We use the continuous example of a robot arm to explain our results and provide the complete interaction model for the robot arm.

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 requests 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 a better distribution of load and thus to better worldwide scalability. We give a general overview of the proposed architecture as well as the formal semantics of the overall system.

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.

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.

We have built a demonstrator for the communication infrastructure of a multi-agent system controlling a simplified shop floor. We use the concept of stigmergy which does not allow inter-agent communication but only between agents and the environment. Furthermore we keep the agents as simple as possible by using only simple-reflex agents. The environment is modelled as a RDF Knowledge Graph and communication takes place using HTTP request. We carried out experiments regarding the agent scalability and identified open questions.

Intelligent, autonomous agents are still not available in the Semantic Web at large scale today. Also the fields of Semantic Web and Multi-Agent Systems are not working together very closely although they could profit much from each other. Existing approaches merely use the Web as a transport layer and are not properly aligned to the architectural style of the Web. The Internet of Things, which would be very useful for agents to act upon Things in the real world, on the other side is very fragmented and not easily inter-operable. The Web of Things has emerged as an approach to use the (Semantic) Web as an application layer for Things. It is still unclear however, how agents on the WoT should look like. We propose that the Semantic Web is a suitable integration layer, both for agents and Things. We investigate how a Multi-Agent System in the Semantic Web of Things can be build by utilizing simple reflex agents and the communication paradigm of stigmergy. We map Things and artifacts to Web resources that are managed by a Web server and provide affordances to agents through hypermedia.