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Interoperability is the key to implementing a wide range of energy systems applications. It involves the seamless cooperation of different methods and components. With smart energy systems, interoperability faces challenges due to integrating differ-ent approaches and technologies. This includes dealing with heterogeneous approaches with various communication proto-cols and data formats. However, it is essential for smart energy systems to carry out thorough interoperability tests. They are usually diverse, and challenging, thus requiring careful consideration of compatibility issues and complex integration scenari-os. Overcoming these challenges requires a systematic approach that includes thorough test planning, rigorous testing, and continuous test monitoring. Although numerous testing approaches exist, most are more developed at the component/device level than at the system level. Consequently, there are few approaches and related facilities to test the interoperability of smart energy approaches and solutions at the system level. This work analyses existing interoperability test concepts, identi-fies enablers and the potential for harmonisation of procedures, and proposes further developments of these approaches., Comment: 14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion (MED POWER 2024)

Sustainable Development Goals (SDGs) give the UN a road map for development with Agenda 2030 as a target. SDG3 "Good Health and Well-Being" ensures healthy lives and promotes well-being for all ages. Digital technologies can support SDG3. Burnout and even depression could be reduced by encouraging better preventive health. Due to the lack of patient knowledge and focus to take care of their health, it is necessary to help patients before it is too late. New trends such as positive psychology and mindfulness are highly encouraged in the USA. Digital Twins (DTs) can help with the continuous monitoring of emotion using physiological signals (e.g., collected via wearables). DTs facilitate monitoring and provide constant health insight to improve quality of life and well-being with better personalization. Healthcare DTs challenges are standardizing data formats, communication protocols, and data exchange mechanisms. As an example, ISO has the ISO/IEC JTC 1/SC 41 Internet of Things (IoT) and DTs Working Group, with standards such as "ISO/IEC 21823-3:2021 IoT - Interoperability for IoT Systems - Part 3 Semantic interoperability", "ISO/IEC CD 30178 - IoT - Data format, value and coding". To achieve those data integration and knowledge challenges, we designed the Mental Health Knowledge Graph (ontology and dataset) to boost mental health. As an example, explicit knowledge is described such as chocolate contains magnesium which is recommended for depression. The Knowledge Graph (KG) acquires knowledge from ontology-based mental health projects classified within the LOV4IoT ontology catalog (Emotion, Depression, and Mental Health). Furthermore, the KG is mapped to standards when possible. Standards from ETSI SmartM2M can be used such as SAREF4EHAW to represent medical devices and sensors, but also ITU/WHO, ISO, W3C, NIST, and IEEE standards relevant to mental health can be considered., Comment: 20 pages, Book chapter, Smart Technologies for Achieving Good Health and Well-Being: Towards Sustainable Development Goal, Taylor & Francis

Smart grid interoperability is the means to achieve the twin green and digital transition but re-mains heterogeneous and fragmented to date. This work presents the first ideas and corner-stones of an Interoperability Roadmap for the Energy Transition that is being developed by the Horizon Europe int:net project. This roadmap builds on four cornerstones that address open interoperability issues. These are a knowledge base to address the lack of convergence among existing initiatives, a maturity model and a network of testing and certification facilities to ad-dress the lack of practical tools for the industry, and a governance process to address the gap between standards-related approaches of Standards Development Organisations and Research and Innovation projects. A community of practice will be set up to ensure the continuity of the ongoing activities related to smart grid interoperability. To outlive the duration of the int:net project, the aim is to formalise the community of practice as a legal entity., Comment: 12. (Hybrid) Symposium Communications for Energy Systems (ComForEn 2023)

Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities. However, for dynamic real-world applications such as social networks, recommender systems, computational biology, relational knowledge representation has emerged as a challenging research problem where there is a need to represent the changing nodes, attributes, and edges over time. The evolution of search engine responses to user queries in the last few years is partly because of the role of KGs such as Google KG. KGs are significantly contributing to various AI applications from link prediction, entity relations prediction, node classification to recommendation and question answering systems. This article is an attempt to summarize the journey of KG for AI.

In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from sources such as satellite images, local sensors and social media content generated by local people. A bold obstacle to capturing, representing and integrating such heterogeneous and diverse information is lack of a proper ontology which properly conceptualizes this domain, aggregates and unifies datasets. Thus, in this paper, we introduce empathi ontology which conceptualizes the core concepts concerning with the domain of emergency managing and planning of hazard crises. Although empathi has a coarse-grained view, it considers the necessary concepts and relations being essential in this domain. This ontology is available at https://w3id.org/empathi/.

The Web of Things (WoT) is rapidly growing in popularity getting the interest of not only technologist and scientific communities but industrial, system integrators and solution providers. The key aspect of the WoT to succeed is the relatively, easy-to-build ecosystems nature inherited from the web and the capacity for building end-to-end solutions. At the WoT connecting physical devices such as sensors, RFID tags or any devices that can send data through the Internet using the Web is almost automatic. The WoT shared data can be used to build smarter solutions that offer business services in the form of IoT applications. In this chapter, we review the main WoT challenges, with particular interest on highlighting those that rely on combining heterogeneous IoT data for the design of smarter services and applications and that benefit from data interoperability. Semantic web technologies help for overcoming with such challenges by addressing, among other ones the following objectives: 1) semantically annotating and unifying heterogeneous data, 2) enriching semantic WoT datasets with external knowledge graphs, and 3) providing an analysis of data by means of reasoning mechanisms to infer meaningful information. To overcome the challenge of building interoperable semantics-based IoT applications, the Machine-to-Machine Measurement (M3) semantic engine has been designed to semantically annotate WoT data, build the logic of smarter services and deduce meaningful knowledge by linking it to the external knowledge graphs available on the web. M3 assists application and business developers in designing interoperable Semantic Web of Things applications. Contributions in the context of European semantic-based WoT projects are discussed and a particular use case within FIESTA-IoT project is presented., Comment: 22 pages

Semantic Web of Things (SWoT) applications focus on providing a wide-scale interoperability that allows the sharing of IoT devices across domains and the reusing of available knowledge on the web. However, the application development is difficult because developers have to do various tasks such as designing an application, annotating IoT data, interpreting data, and combining application domains. To address the above challenges, this paper demonstrates SWoTSuite, a toolkit for prototyping SWoT applications. It hides the use of semantic web technologies as much as possible to avoid the burden of designing SWoT applications that involves designing ontologies, annotating sensor data, and using reasoning mechanisms to enrich data. Taking inspiration from sharing and reuse approaches, SWoTSuite reuses data and vocabularies. It leverages existing technologies to build applications. We take a hello world naturopathy application as an example and demonstrate an application development process using SWoTSuite. The demo video is available at URL: http://tinyurl.com/zs9flrt., Comment: 8 pages

The Internet of Things (IoT) is experiencing fast adoption in the society, from industrial to home applications. The number of deployed sensors and connected devices to the Internet is changing our perspective and the way we understand the world. The development and generation of IoT applications is just starting and they will modify our physical and virtual lives, from how we control remotely appliances at home to how we deal with insurance companies in order to start insurance schemes via smart cards. This massive deployment of IoT devices represents a tremendous economic impact and at the same time offers multiple opportunities. However, the potential of IoT is underexploited and day by day this gap between devices and useful applications is getting bigger. Additionally, the physical and cyber worlds are largely disconnected, requiring a lot of manual efforts to integrate, find, and use information in a meaningful way. To build a connection between the physical and the virtual, we need a knowledge framework that allow bilateral understandings, devices producing data, information systems managing the data and applications transforming information into meaningful knowledge. The first column in this series in the previous issue of this magazine titled "Internet of Things to Smart IoT Through Semantic, Cognitive, and Perceptual Computing," reviews IoT growth and potential that have energized research and technology development, centered on aspects of Artificial Intelligence to build future intelligent system. This column steps back and demonstrates the benefits of using semantic web technologies to get meaningful knowledge from sensor data to design smart systems., Comment: 7 pages, 3 figure