Implementation of an Ontology-based Data Access Application for Cross-domain Access of Energy Efficiency KPIs in Smart Factories

A smart factory is defined as a factory, which is composed of automated energy consumer machines and facilities that are integrated with IT technologies. Factories are considered as one of the highest energy consumers in 21st century. Increasing energy prices due to the limited nature of fossil energy sources and environmental legislation stresses on the importance of energy efficiency performance of smart factories. Many Manufacturers by taking the advantage of energy management systems are trying to improve energy efficiency of the factories. There are many factories which are applying different tools aiming to compute energy efficiency Key Performance Indicators (KPIs). In order to have an energy efficient factory and subsequently stronger energy management, these KPIs are needed to be usable, operational and easily accessible by the factory’s experts. Data relevant to the Energy efficiency KPIs are usually stored in Relational Databases (RDB). RDBs are working under Relational Database Management Systems (RDBMS). However, RDBMS has a rigid data structure and basically are built biased to serve the implementations and component installation strategies of the manufacturing process. Therefore, RDBs cannot meet the requirements to have a conceptual data model. Use of a proper ontology as a semantic model of the manufacturing domain, on top of RDBs seems to be a promising solution to overcome this problem. Ontologies are considered as a reliable tool for providing a shared conceptualization of the domain of interest. This facilitates the cross-domain access of KPIs in the factory. Retrieving data from RDBs through on ontology model is called Ontology-Based Data Access (OBDA). OBDA is based on correspondences between the relational database and ontology model. This research work results in development of OBDA application for energy efficiency KPIs. The designed OBDA for KPIs is applicable within a service-oriented manufacturing enterprise. The developed OBDA application was implemented in premises of Tampere University of Technology. The results of this implementation demonstrate ease of cross-domain access to energy efficiency KPIs. The research leading to these results was partially funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 600058

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches

NextGen Multi-Model Databases in Semantic Big Data Architectures

When semantic big data is managed in commercial settings, with time, the need may arise to integrate and interlink records from various data sources. In this vision paper, we discuss the potential of a new generation of multi-model database systems as data backends in such settings. Discussing a specific example scenario, we show how this family of database systems allows for agile and flexible schema management. We also identify open research challenges in generating sound triple-views from data stored in interlinked models, as a basis for SPARQL querying. We then conclude with a general overview of multi-model data management systems, to provide a wider scope of the problem domain

Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices

The escalating integration of network-enabled medical devices raises concerns for both practitioners and academics in terms of introducing new vulnerabilities and attack vectors. This prompts the idea that combining medical device data, security vulnerability enumerations, and attack-modeling data into a single database could enable security analysts to proactively identify potential security weaknesses in medical devices and formulate appropriate mitigation and remediation plans. This study introduces a novel extension to a relational database risk assessment framework by using the open-source tool OVAL to capture device states and compare them to security advisories that warn of threats and vulnerabilities, and where threats and vulnerabilities exist provide mitigation recommendations. The contribution of this research is a proof of concept evaluation that demonstrates the integration of OVAL and CAPEC attack patterns for analysis using a database-driven risk assessment framework

A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases

PhDData stored in individual autonomous databases often needs to be combined and interrelated. For example, in the Inland Water (IW) environment monitoring domain, the spatial and temporal variation of measurements of different water quality indicators stored in different databases are of interest. Data from multiple data sources is more complex to combine when there is a lack of metadata in a computation forin and when the syntax and semantics of the stored data models are heterogeneous. The main types of information retrieval (IR) requirements are query transparency and data harmonisation for data interoperability and support for multiple user views. A combined Semantic Web based and Agent based distributed system framework has been developed to support the above IR requirements. It has been implemented using the Jena ontology and JADE agent toolkits. The semantic part supports the interoperability of autonomous data sources by merging their intensional data, using a Global-As-View or GAV approach, into a global semantic model, represented in DAML+OIL and in OWL. This is used to mediate between different local database views. The agent part provides the semantic services to import, align and parse semantic metadata instances, to support data mediation and to reason about data mappings during alignment. The framework has applied to support information retrieval, interoperability and multi-lateral viewpoints for four European environmental agency databases. An extended GAV approach has been developed and applied to handle queries that can be reformulated over multiple user views of the stored data. This allows users to retrieve data in a conceptualisation that is better suited to them rather than to have to understand the entire detailed global view conceptualisation. User viewpoints are derived from the global ontology or existing viewpoints of it. This has the advantage that it reduces the number of potential conceptualisations and their associated mappings to be more computationally manageable. Whereas an ad hoc framework based upon conventional distributed programming language and a rule framework could be used to support user views and adaptation to user views, a more formal framework has the benefit in that it can support reasoning about the consistency, equivalence, containment and conflict resolution when traversing data models. A preliminary formulation of the formal model has been undertaken and is based upon extending a Datalog type algebra with hierarchical, attribute and instance value operators. These operators can be applied to support compositional mapping and consistency checking of data views. The multiple viewpoint system was implemented as a Java-based application consisting of two sub-systems, one for viewpoint adaptation and management, the other for query processing and query result adjustment

‘Enhanced Encryption and Fine-Grained Authorization for Database Systems

The aim of this research is to enhance fine-grained authorization and encryption so that database systems are equipped with the controls necessary to help enterprises adhere to zero-trust security more effectively. For fine-grained authorization, this thesis has extended database systems with three new concepts: Row permissions, column masks and trusted contexts. Row permissions and column masks provide data-centric security so the security policy cannot be bypassed as with database views, for example. They also coexist in harmony with the rest of the database core tenets so that enterprises are not forced to compromise neither security nor database functionality. Trusted contexts provide applications in multitiered environments with a secure and controlled manner to propagate user identities to the database and therefore enable such applications to delegate the security policy to the database system where it is enforced more effectively. Trusted contexts also protect against application bypass so the application credentials cannot be abused to make database changes outside the scope of the application’s business logic. For encryption, this thesis has introduced a holistic database encryption solution to address the limitations of traditional database encryption methods. It too coexists in harmony with the rest of the database core tenets so that enterprises are not forced to choose between security and performance as with column encryption, for example. Lastly, row permissions, column masks, trusted contexts and holistic database encryption have all been implemented IBM DB2, where they are relied upon by thousands of organizations from around the world to protect critical data and adhere to zero-trust security more effectively

Publishing a Scorecard for Evaluating the Use of Open-Access Journals Using Linked Data Technologies

Open access journals collect, preserve and publish scientific information in digital form, but it is still difficult not only for users but also for digital libraries to evaluate the usage and impact of this kind of publications. This problem can be tackled by introducing Key Performance Indicators (KPIs), allowing us to objectively measure the performance of the journals related to the objectives pursued. In addition, Linked Data technologies constitute an opportunity to enrich the information provided by KPIs, connecting them to relevant datasets across the web. This paper describes a process to develop and publish a scorecard on the semantic web based on the ISO 2789:2013 standard using Linked Data technologies in such a way that it can be linked to related datasets. Furthermore, methodological guidelines are presented with activities. The proposed process was applied to the open journal system of a university, including the definition of the KPIs linked to the institutional strategies, the extraction, cleaning and loading of data from the data sources into a data mart, the transforming of data into RDF (Resource Description Framework), and the publication of data by means of a SPARQL endpoint using the OpenLink Virtuoso application. Additionally, the RDF data cube vocabulary has been used to publish the multidimensional data on the web. The visualization was made using CubeViz a faceted browser to present the KPIs in interactive charts.This work has been partially supported by the Prometeo Project by SENESCYT, Ecuadorian Government

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches

A formal framework for model management

El Desarrollo de Software Dirigido por Modelos es una rama de la Ingeniería del Software en la que los artefactos software se representan como modelos para incrementar la productividad, calidady eficiencia económica en el proceso de desarrollo de software, donde un modelo proporciona una representación abstracta del código final de una aplicación. En este campo, la iniciativa Model-Driven Architecture (MDA), patrocinada por la OMG, está constituida por una familia de estándares industriales, entre los que se destacan: Meta-Object Facility (MOF), Unified Modeling Language (UML), Object Constraint Language (OCL), XML Metadata Interchange (XMI), y Query/Views/Transformations (QVT). Estos estándares proporcionan unas directrices comunes para herramientas basadas en modelos y para procesos de desarrollo de software dirigidos por modelos. Su objetivo consiste en mejorar la interoperabilidad entre marcos de trabajo ejecutables, en automatizar el proceso desarrollo de software de software y en proporcionar técnicas que eviten errores durante ese proceso. El estándar MOF describe un marco de trabajo genérico que permite definir la sintaxis abstracta de lenguajes de modelado. Este estándar persigue la definición de los conceptos básicos que son utilizados en procesos de desarrollo de software dirigidos por modelos: que es un modelo, que es un metamodelo, qué es reflexión en un marco de trabajo basado en MOF, etc. Sin embargo, la mayoría de estos conceptos carecen de una semántica formal en la versión actual del estándar MOF. Además, OCL se utiliza como un lenguage de definición de restricciones que permite añadir semántica a un metamodelo MOF. Desafortunadamente, la relación entre un metamodelo y sus restricciones OCL también carece de una semántica formal. Este hecho es debido, en parte, a que los metamodelos solo pueden ser definidos como dato en un marco de trabajo basado en MOF. El estándar MOF también proporciona las llamadas facilidades de reflexión de MOF (MOF ReflectiBoronat Moll, A. (2007). A formal framework for model management [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1964Palanci