Knowledge Model

Energy management systems in buildings and their district today use automation systems and artificial intelligence (AI) solutions for smart energy management, but they fail to achieve the desired results due to the lack of holistic and optimised decision-making. A reason for this is the silo-oriented approach to the decision-making failing to consider cross-domain data. Ontologies, as a new way of processing domain knowledge, have been increasingly applied to different domains using formal and explicit knowledge representation to conduct smart decision-making. In this PhD research, Real-time Multiscale Smart Energy Management and Optimisation (REMO) ontology was developed, as a cross-domain knowledge-base, which consequently can be used to support holistic real-time energy management in districts considering both demand and supply side optimisation. The ontology here, is also presented as the core of a proposed framework which facilitates the running of AI solutions and automation systems, aiming to minimise energy use, emissions, and costs, while maintaining comfort for users. The state of the art AI solutions for prediction and optimisation were concluded through authors involvement in European Union research projects. The AI techniques were independently validated through action research and achieved about 30 -40 % reduction in energy demand of the buildings, and 36% reduction in carbon emissions through optimisation of the generation mix in the district. The research here also concludes a smart way to capture the generic knowledge behind AI models in ontologies through rule axiom features, which also meant this knowledge can be used to replicate these AI models in future sites. Both semantic and syntactic validation were performed on the ontology before demonstrating how the ontology supports the various use cases of the framework for holistic energy management. Further development of the framework is recommended for the future which is needed for it to facilitate real-time energy management and optimisation in buildings and their district.

This deliverable concentrates on the results of task 2.2 of work package 2. It describes the SEAS Knowledge Model as a basis for semantic interoperability in the SEAS ecosystem. The SEAS Knowledge Model consists of an innovative Web ontology that is designed to: (i) meet the current best practices in terms of quality, metadata, and publication, (ii) reuse or align to existing standards, and (iii) cover the required expressivity for the SEAS use cases, while being extensible to other use cases and domains (gas, water, air, waste management).

This deliverable concentrates on the results of task 2.2 of work package 2. It describes the SEAS Knowledge Model as a basis for semantic interoperability in the SEAS ecosystem. The SEAS Knowledge Model consists of an innovative Web ontology that is designed to: (i) meet the current best practices in terms of quality, metadata, and publication, (ii) reuse or align to existing standards, and (iii) cover the required expressivity for the SEAS use cases, while being extensible to other use cases and domains (gas, water, air, waste management).

The purpose of this document is to provide a common semantic data models of all needs described in the business cases of the WP1-T1.1. This includes semantic knowledge about all relevant concepts and its relationships in each pilot. A common semantic data model allows heterogenous systems to share the same meaning of entities that enables them to interoperate.

Current research evidences an increase of use of Semantic Web technologies within city energy management solutions. Different ontologies have been developed in order to improve energy data interoperability. However, these ontologies represent different energy domains, with different level of detail and using different terminology. This heterogeneity leads to an interoperability problem that hinders the full adoption of these ontologies in real scenarios. This paper presents the OEMA (Ontology for Energy Management Applications) ontology network. This ontology is an attempt to unify existing heterogeneous ontologies that represent energy performance and contextual data. The paper describes the OEMA ontology network development process, which has included ontology reuse, ontology engineering and ontology integration activities. The paper also describes the main OEMA ontology network modules.

A method to build a dictionary of terms is developed, which is based on a processing of preliminary set of texts from the given domain. Building a set of frames is described, which determine the domain knowledge model, based on a resulting dictionary.Разработан метод построения словаря терминов, основанный на предварительной обработке множества текстов из заданной предметной области. Описано построение множества фреймов, определяющих модель знаний предметной области, на основе полученного словаря.Розроблений метод побудови словника термінів, що базується на попередній обробці множини текстів з заданої предметної області. Описана побудова множини фреймів, що визначають модель знань предметої області, на основі отриманого словника

This paper proposes an approach for supporting the analysis of collected energy consumption data in combination with structured system models to reveal correlations between energy usage and related properties of products, operations and equipment. The described method serves as a starting point for the creation of tailored simulation models for energy consumption forecasts that can be used in the planning phase of manufacturing systems. Therefore several energy-oriented simulation methods are introduced and discussed regarding their suitability for different use cases in manufacturing engineering.

The Polifonia Knowledge Graph (PKG) is one of the central contributions in the whole project, resulting from the integration of pilots' datasets and their interlinking with external resources. But while we develop the PKG, a key question to ask-which we address in this deliverable-is: how can we ensure that the PKG and the PON are of high quality? What kind of evidence can we show that the ontology modules and knowledge graphs in Polifonia are, indeed, adequately addressing the needs of the pilots? How can we automatically assess, through established-and novel-ontology evaluation techniques, that the Polifonia Ontology Network (PON) and PKG are providing valid answers to the relevant competency questions? Current approaches to address these in automated ontology evaluation, such as NeON Toolkit and TESTaLOD, are not entirely satisfactory: the former does offer iterative testing, but it only supports SPARQL-based competency question verification; and the latter provides Web-based testing supported based on the TestCase OWL metamodel, but only supports tests cases constructed by ontology testers. To address these gaps, this deliverable introduces XDTesting, a tool support for testing ontologies based on the XD methodology. The tool is developed as an automation in the GitHub platform and is comprised of numerous features that are in coherence with the testing methodology. Document History Version Release date Summary of changes Author(s)-Institution V0.1 30/03/2022 First draft released, outline Albert Meroño-Peñuela (KCL), Jacopo de Berardinis (KCL), Fiorela Ciroku (UNIBO) V0.2 23/05/2022 Prepared for internal review Albert Meroño (KCL), Jacopo de Berardinis (KCL), Fiorela Ciroku (UNIBO), Valentina Carriero (UNIBO) V0.3 20/06/2022 Amended with internal reviewer feedback Albert Meroño (KCL), Jacopo de Berardinis (KCL), Fiorela Ciroku (UNIBO) V0.4 21/06/2022 Final version preparation Albert Meroño (KCL), Jacopo de Berardinis (KCL) V1.0 30/06/2022 Final version submitted to EC Marta Clementi (UNIBO)

One of the Internet of Things promises is interoperability where data is shared and understood between things and applications. Such interoperability aims to achieve a common goal with better efficiency, optimization, and a better user experience. However, these things produces data in different formats and semantics making interoperability a real challenge still to be tackled. Linked data is currently positioned as a promising technology capable of addressing the heterogeneity challenge. In this paper, we present an efficient energy storage system which relies on a multi-system semantic representation of several data sources. Our approach analyzes data collected from external services such as weather and billing systems and our internal systems such as the building management system, power monitoring system, and data center system. The aim of the analyzed data coupled with our model enables efficient energy storage usage through forecasting and model predictive control for various ...

Rare diseases (RD) are those affecting at least 1 of 2.000 inhabitants. Many RD, induce disabling conditions and those school age affected children usually miss classes due to the complicated diagnostic procedures and the several medical treatments they need, thereafter. It is still unknown the exact number of students in this situation in Navarra (Spain), although according to data from the INE [16], there should be at least 1300 children with disabilities from which at least 372 children in school age could be RD affected. These students should be able to be identified in schools, as the vast majorities need help at some point, derived in some cases from cognitive deficiencies but in others, from their absence of classes due to health complications. Some Rare Disease Affected Students (RDAS) also suffer from bullying due to the ignorance of their peers or even teachers, towards their situation. In this paper, the use of Cmap Tools software, together with a planned intervention in each school from Navarre, attended by at least, one RDAS, is proposed for creating knowledge models based on the specific RD affecting children in Navarre. This way, a RD based Knowledge Model Net (RDKMN) could be built, together with affected and non affected students, and this meaningful knowledge could be useful for any school attended by children suffering the same disease in Spain or other European countries. This could become a powerful international inclusive and didactic tool, which could help normalizing RD and including RDAS in the educational field, creating inclusive schools, and therefore spreading the knowledge to the social field.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Rare diseases (RDs) are considered all diseases affecting to less than or equal to 5 in 10.000 citizens, criteria followed by most European Countries. Since most RDs incur disabling conditions, a few patients seldom reach adult life or attend class regularly. However, there are some less serious conditions which are compatible with a better quality of life during childhood and youth and which allow students attend classes in a more regular way. During this period and in these cases, we suggest the possibility of using the software Cmap Tools in order to create knowledge models, so that RD affected students who may miss classes due to their health status, can reach their fellows and follow their teachers' explanations without any particular curriculum adaptation. In the context of a natural science class addressing health and illnesses, we suggest the possibility of using concept maps and V diagrams as tools for getting meaningful and long life learning. Once they learn the basis for creating basic concept maps, RD affected students and their mates may learn some of the symptoms, difficulties of diagnostic, treatment possibilities, foundations and research groups of the most common RDs held in Navarra (Spain), through concept maps. We show an educative intervention in a primary school in Navarra in which one of the students is affected by Treacher Collins and through the presentation of her disease, the rest of the students will get to know the characteristics of this particular disease and will make them be more empathic with her and her immediate reality, making RDs sound less rare. In the other side, by means of this teaching-learning process, RD affected students feel the main characters and also more valuable for society, which increases their self-esteem. By promoting this type of activities, teachers will manage a creative tool which help them in both emotional and professional aspects, since they do not have to adapt the curriculum to a particular student because Knowledge models allow the continuation of the learning process. Finally, the use of Cmap Tools provides items to measure what students knew previously about a particular topic and also helps them appreciate how their cognitive structure has changed and developed regarding their previous knowledge, stimulating a meaningful and long life learning and avoiding conceptual misconceptions.

There are numerous situations where the digital representation of the environment appears critical for understanding and decision-making: threats on soils, water, seashores, risk of fires, pollutions are evident applications. If spatial cellular decomposition is evidence in the more common applications, there remains a large field for environment and activities modelling. The integration and composition of several information sources is perhaps the main difficulty with the need to deal with data interpretation and semantics inside concurrent simulators. Besides, the data on population, people's behaviours, people's perceptions are essential in environmental assessments, where the technical aspect is not counted as much as the common acceptance of impact technology. We provide a model for building environmental services with open data systems. A case study is given for getting information from the public about their relationship with freshwater and its scarcity in Jamaica.

This paper presents a novel approach to modelling and documenting design knowledge: to use parametric technology to explicitly store knowledge which exists in a group of people (such as a company), so that it can be reused over many projects and grow over time when more projects are designed. This approach has been applied and tested on a test case of common concrete viaducts. The outcome constitutes the first iteration of the development of a parametric viaduct design platform, aimed for architects and structural engineers. The motivation was to counter the fragmentation of the Architecture, Engineering & Construction (AEC) industry, where each discipline encapsulates different knowledge areas, which results in miscommunication and the loss of valuable information and time. The suggested methodology aims at combining the BIM principles [1] with the concepts of parametric and associative design, as well as visual programming [2] to develop a common design platform for the architect ...

Modern electric power distribution systems are data rich and include growing numbers of distributed energy resources and distribution automation. To take advantage of distribution automation and manage growing penetrations of distributed energy resources, distribution utilities need applications for planning and operations that use all available data and may incorporate distributed approaches to operations and control. The industry would benefit from distribution management applications based on a common platform that makes systems of each type interchangeable. This paper describes an approach to enabling cost-effective development and deployment of advanced applications for distribution system planning and operations based on development of an open-source, standardsbased platform for application development called GridAPPS-D, which leverages data abstractions for application development based on standards such as the distribution system common information model (CIM).

This deliverable concentrates on the results of task 2.2 of work package 2. It describes the SEAS Knowledge Model as a basis for semantic interoperability in the SEAS ecosystem. The SEAS Knowledge Model consists of an innovative Web ontology that is designed to: (i) meet the current best practices in terms of quality, metadata, and publication, (ii) reuse or align to existing standards, and (iii) cover the required expressivity for the SEAS use cases, while being extensible to other use cases and domains (gas, water, air, waste management).

This deliverable concentrates on the results of task 2.2 of work package 2. It describes the SEAS Knowledge Model as a basis for semantic interoperability in the SEAS ecosystem. The SEAS Knowledge Model consists of an innovative Web ontology that is designed to: (i) meet the current best practices in terms of quality, metadata, and publication, (ii) reuse or align to existing standards, and (iii) cover the required expressivity for the SEAS use cases, while being extensible to other use cases and domains (gas, water, air, waste management). This document is a snapshot of the situation at the end of the SEAS project. Up-to-date information can be found at the following websites: https://w3id.org/seas/ for the SEAS Knowledge Model, and contributing to it; https://w3id.org/pep/ for the Process Executor Platform ontology. Deliverable D2.2 SEAS Knowledge Model 2 19 December 2016 Version 1.0 Smart Energy Aware Systems ITEA2 – 12004

Cyber-Physical Systems (CPS) consist of distributed computation interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. Finding a common semantic among these diverse components that facilitates system synthesis, verification, and monitoring is a significant challenge of a CPS research program. In the emerging smart grid, for example, system state provides input into distributed computer algorithms that manage power and energy via local computation with messaging passing over a computer network collectively resulting in control signals to advanced power electronics. Computational correctness, network timing, and frequency response are all system aspects that conspire to impede design, verification, and monitoring. This paper seeks to unify the knowledge present in these diverse aspects through developing common semantics that span each aspect of a CPS. Specifically, a "smart grid" type system is considered. Power commands to various loads and alternative energy sources are stepped in response to cyber controllers that are networked. This paper shows the development of a physical invariant, based on the theory of Lyapunov-like functions, and a cyber invariant, the governs the correctness of a power dispatch algorithm, and couples the two to develop an overall system stability invariant. The invariant approach is tested with two scenarios. In the first case, the system is subjected to two commanded pulses beyond the stable limit, with the second perturbing pulse being of a magnitude greater than the first, which makes the system unstable. In the second case, the system is subjected to two commanded pulses beyond its stable limit but with a comparatively smaller magnitude of the perturbing second pulse, which allowed the system to remain stable. The measure of stability is an energy function which, under certain conditions, serves as a Lyapunov-like invariant that is used to prove stability.

The inability of current Internet-based learning systems to deal with different kinds of learners and the high cost of developing a new learning system are well known problems in elearning. To overcome these problems, we have designed a learning middleware suite, called the Collaborative and Sharable Learning (CoSL) system. CoSL is a tool set for building e-learning systems and for developing course materials for an e-learning environment. Given the geographic distribution of the components of a Web-based e-learning system, it is crucial to support fast communication between providers and consumers of e-learning course materials. In this paper, a high performance Publisher/Subscriber communication system has been designed for real-time communication between participants. CoSL allows us to build and manage global real-time learning systems in a distributed and heterogeneous environment.

— In this paper, we propose a domain metric knowledge model for Embodied Conversational Agents (ECAs) for human computer interaction. In our research, we have found that by incorporating Open-Domain and Domain-Specific knowledge, a new generation of ECAs will be able to demonstrate intelligence and to increase trust by the users. The proposed system is aimed at advancing the scholarly field of artificial intelligence and to offer assistance to queries on real-world issues. The experimental system we have developed aims to provide answers to questions on pandemic threat. The focus is on Bird Flu as the Domain-Specific knowledge together with the support of multiple open-domain knowledge bases. We also present a scheme for selecting specific websites as the input knowledge bases for our conversational system based on reputability, creditability, reliability and trustworthiness.

A great difficulty regarding the management of information systems is the fact that much of the knowledge available inside the organizations only can be found in a nonstructured form. As a consequence, one of the major problems faced by the industrial segment, including capital goods industries, is the low degree of interoperability (capacity that a system presents of sharing and interchanging information and applications). This problem is even more serious when considering the whole product lifecycle, where several pieces of software are involved to allow the organization of PLM (Product Lifecycle Management). One of the most promising approaches to address these issues is the structuring of formal ontologies. This paper presents the preliminary development of an ontology (called Ontologia PLM Project), that aims to ensure a transparent interoperability between systems used for the interchange of information through the whole product lifecycle. This project is focused on the capital goods industry and encompasses eight domains of application (DA). A group of specialists is responsible for analysing each DA. At the moment, the DA's have defined the set of related classes and are involved in inserting properties and restrictions. Finally, a small set of axioms has been implemented allowing verifying the preliminary behaviour of the proposed ontology.

We present a generic database schema enabling different contextual points of view on a heterogeneous mass of scientific data and information within a multidisciplinary research environment. We present a method with which scientific data can be stored in a self-defined set of entities and relations, so that it becomes possible to represent the context for each research question in its own conceptual ER schema within one single relational database and without changing any involved schema. Acknowledged ontologies as particular schemata, involving bibliographic, biographic, or artifact information, can be included. The intersection of the metaphorical sphere within texts, feature specialties of material artifacts, and geographical terms allows a congruent text-artifact-map-transformation. Examples shall illustrate the broadness of our approach.

Database management currently assumes a relative stability of database structures and supports user viewpoints through a number of views. New users must either adopt their data demand to existing views or issue a request for support of their demands. The support for the second option is not feasible whenever user communities often change or users agile change their viewpoints. Further applications continuously evolve. This evolution also results in change requests to database structures, to database views and to database features. We support evolution of databases and changes of user viewpoints by a generic database system, and automatic generation of generation of views. This approach supports modification of the database according to the special viewpoint of users. Queries issued by the user are transformed to generic database queries. Results that are computed for these queries are translated back to user-specific answers.

Modeling of semantics is one of the most di cult tasks in database design. Constraints are used to express database semantics. They are used di erently in database models. They express domain restrictions, specify relationships between components and state database behavior. The utilization depends on the richness of the type system used in the model. The relational model is using a simple type system and has a very large set of integrity constraints. Semantical models are using richer type systems which express also di erent types of integrity constraints. At the same time, the theory of integrity constraints is more complex. Object-oriented models use either a simple type system or type systems like the semantical models. The theory of integrity constraints is still under development. This overview tries to give a unifying framework on integrity constraints. 1

Database management currently assumes a relative stability of database structures and supports user viewpoints through a number of views. New users must either adopt their data demand to existing views or issue a request for support of their demands. The support for the second option is not feasible whenever user communities often change or users agile change their viewpoints. Further applications continuously evolve. This evolution also results in change requests to database structures, to database views and to database features. We support evolution of databases and changes of user viewpoints by a generic database system, and automatic generation of generation of views. This approach supports modification of the database according to the special viewpoint of users. Queries issued by the user are transformed to generic database queries. Results that are computed for these queries are translated back to user-specific answers.

Classical normalisation theory has a number of lacunas although it is commonly and widely accepted and it is the basis for database theory since the 80ies. Most textbooks and monographs still follow this approach despite the good number of open problems. Today, modern object-relational DBMS offer far better capabilities than the systems that have been built in the past based on the strict relational paradigm. Constraint maintenance has been oriented on transformation of structures to structures that are free of functional dependencies beside key constraints. The maintenance of coherence constraints such as two-type inclusion constraints has been neglected although this maintenance might be the most expensive one. In reality normalisation is local optimisation that exclusively considers functional dependency maintenance. We thus need a different normalisation approach. This paper develops an approach towards optimisation of schemata and global normalisation. This approach results in a denormalisation and object-relational database schemata. 1 Normalisation-The Good, The Bad, The Ugly Normalisation is considered to be one of the pearls of database theory. There is almost no database course that does not teach this part of a theory. The main results have been achieved during the 70ies, 80ies and early 90ies. Since then the theory is considered to be completed although new DBMS (database management systems) and new database paradigms have been developed since then. There are very few publications on object-relational structures. XML approaches have mainly be following this research paradigm.

The development of sustainable products is a full growth area due to current legislation, mainly in Europe and the United States. Electronics products have increasingly short life cycles, which imposes the need to exchange information more dynamically, accurately and timely, for preventing failures in the survey, interpretation and application of information during the stage of product development, ensuring compliance to existing regulatory frameworks. Products need to be designed based on structured information. Capturing the desires and needs of customers and turning them into requirements and design details for the purpose of compliance to the RoHS regulatory framework is a complex task due to the multitude of information, not always correlated. Hypothetically, the use of a single definition model that captures a spatial, behavioral and procedural description of the product can help reduce the current waste of resources and quality assurance in the development process. The present work aims to develop a product definition model for meeting the RoHS directive. This is done by proposing a formal ontology that potentially promotes interoperability of information systems that are used throughout the production chain in the electronics industry. The model is under development and is to be checked for suitability in the context of the Brazilian electronics industry.

Multi-model utilisation is a common practice in many sciences, e.g. computer science. Coherence and co-evolution of models is however still an open problem. Multi-model approaches suffer however from the impedance mismatch due to differences in modelling languages. The collaboration approach is based on preservation of local models and on explicit association of derived sub-models. Each discipline has developed its specific know-how in modelling and model deployment. Models evolve in dependence on the progress of the research work. If a model or one of its sub-models has been exchanged with a team member then this evolution must also be applied to models of the partner if those sub-models are used elsewhere. We develop a novel approach to multi-model development and utilisation, to common use and utilisation of models and modelling experience, to systematic assessment of models and systematic extraction of the potential and capacity of models for a research community, and to the co-evolution of model networks.

A great difficulty regarding the management of information systems is the fact that much of the knowledge available inside the organizations only can be found in a non-structured form. As a consequence, one of the major problems faced by the industrial segment, including capital goods industries, is the low degree of interoperability (capacity that a system presents of sharing and interchanging information and applications). This problem is even more serious when considering the whole product lifecycle, where several pieces of software are involved to allow the organization of PLM (Product Lifecycle Management). One of the most promising approaches to address these issues is the structuring of formal ontologies. This paper presents the preliminary development of an ontology (called Ontologia PLM Project), that aims to ensure a transparent interoperability between systems used for the interchange of information through the whole product lifecycle. This project is focused on the capital goods industry and encompasses eight domains of application (DA). A group of specialists is responsible for analysing each DA. At the moment, the DA's have defined the set of related classes and are involved in inserting properties and restrictions. Finally, a small set of axioms has been implemented allowing verifying the preliminary behaviour of the proposed ontology.

This paper describes our current work in the area of Museum Information Systems, namely for crafts and industry museums, where the main concern is to preserve and document not only material artefacts but also oral traditions, know-how, processes, cultural and social contexts, local history, sounds, tactile experiences and smells. Our case study is a Hat Industry Museum, which is being created in the North of Portugal, at the heart of what was, in the last century, the biggest hat-manufacturing center. As such, the Museum will be also a tribute to the social and economic life of a whole region. We propose and describe a conceptual approach and an information system for describing non-material heritage and its application to our case study.

In this paper a knowledge model for Mechatronic Product Development Based on ontology is put forward, which can support the description and reuse of design knowledge in mechatronic product development. Firstly the typical problems of design knowledge reuse in mechatronic product development are analyzed. Secondly a knowledge model for Mechatronic Product Development and its description based on ontology are given. Thirdly a simple example is introduced to illustrate the main ideas. Finally, the conclusions and future research goal are given.

We present a generic database schema enabling different contextual points of view on a heterogeneous mass of scientific data and information within a multidisciplinary research environment. We present a method with which scientific data can be stored in a self-defined set of entities and relations, so that it becomes possible to represent the context for each research question in its own conceptual ER schema within one single relational database and without changing any involved schema.
Acknowledged ontologies as particular schemata, involving bibliographic, biographic, or artifact information, can be included. The intersection of the metaphorical sphere within texts, feature specialties of material artifacts, and geographical terms allows a congruent text-artifact-map-transformation. Examples shall illustrate the broadness of our approach.

Database management currently assumes a relative stability
of database structures and supports user viewpoints through a number
of views. New users must either adopt their data demand to existing
views or issue a request for support of their demands. The support for
the second option is not feasible whenever user communities often change
or users agile change their viewpoints. Further applications continuously
evolve. This evolution also results in change requests to database structures,
to database views and to database features. We support evolution
of databases and changes of user viewpoints by a generic database system,
and automatic generation of generation of views. This approach
supports modification of the database according to the special viewpoint
of users. Queries issued by the user are transformed to generic database
queries. Results that are computed for these queries are translated back
to user-specific answers.