A knowledge hub to enhance the learning processes of an industrial cluster

Industrial clusters have been defined as ?networks of production of strongly interdependent firms (including specialised suppliers), knowledge producing agents (universities, research institutes, engineering companies), institutions (brokers, consultants), linked to each other in a value adding production chain? (OECD Focus Group, 1999). The industrial clusters distinctive mode of production is specialisation, based on a sophisticated division of labour, that leads to interlinked activities and need for cooperation, with the consequent emergence of communities of practice (CoPs). CoPs are here conceived as groups of people and/or organisations bound together by shared expertise and propensity towards a joint work (Wenger and Suyden, 1999). Cooperation needs closeness for just-in-time delivery, for communication, for the exchange of knowledge, especially in its tacit form. Indeed the knowledge exchanges between the CoPs specialised actors, in geographical proximity, lead to spillovers and synergies. In the digital economy landscape, the use of collaborative technologies, such as shared repositories, chat rooms and videoconferences can, when appropriately used, have a positive impact on the development of the CoP exchanges process of codified knowledge. On the other end, systems for the individuals profile management, e-learning platforms and intelligent agents can trigger also some socialisation mechanisms of tacit knowledge. In this perspective, we have set-up a model of a Knowledge Hub (KH), driven by the Information and Communication Technologies (ICT-driven), that enables the knowledge exchanges of a CoP. In order to present the model, the paper is organised in the following logical steps: - an overview of the most seminal and consolidated approaches to CoPs; - a description of the KH model, ICT-driven, conceived as a booster of the knowledge exchanges of a CoP, that adds to the economic benefits coming from geographical proximity, the advantages coming from organizational proximity, based on the ICTs; - a discussion of some preliminary results that we are obtaining during the implementation of the model.

Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives

Knowledge management technology for integrated decision support systems in process industries

Premi extraordinari doctorat curs 2011-2012, àmbit d’Enginyeria IndustrialNowadays, factors such as globalization of trade, market uncertainty and fierce competition involve dwindling error margins in enterprises. Two key aspects for achieve it are the viability and the competitiveness of enterprises, which highly depend on the effectiveness for taking their decisions related to their manufacturing characteristics, such as economic efficiency, product quality, flexibility or reliability. For this reason, companies have taken the task, for many years, of develop better management information systems in order to help the decision makers to exploit data and models, with the final objective of discussing and improving decision-making. In this sense, decision support systems must be improved in order to deal with the large amount of available data and the heterogeneity of existing modeling approaches along the hierarchical levels in the enterprise structure. Hence, this thesis proposes the application of ontologies as a decision support tool, since they are increasingly seen as a key semantic technology for addressing heterogeneities and mitigating the problems they create and for enabling data mining by semantics-driven the knowledge processing. The aim of this thesis is to contribute to the development of decision support tools for the enterprise process industry. As a decision support tool, must be capable of become a robust model which interacts among the different decision hierarchical levels, providing a unified framework of data and information levels integration. On the other hand, this thesis also aims the improvement in the development of the ontologies. Firstly, a detailed state of the art about the different production process systems, knowledge management base on ontologies, as well as decision support systems is carried out. Based on this review, the specific thesis objectives are posed. Next, a methodology is proposed for the development and use of ontologies, based on the analysis and adaptation of previously existing methodologies. Such methodology is based on the improvement cycle (PSDA), allowing a better way to design, construct and apply domain ontologies. The second part of this thesis is devoted to the application of the different parts of the previously proposed methodology for the development of an ontological framework in the process industry domain concerning the strategic, tactical and operational decision levels. Next, the description of the decision areas in which the ontological framework is applied is presented. Namely, in the process control decision level, the coordination control is considered. Regarding scheduling decisions level, mathematical optimization approaches are applied. Finally, the distributed hierarchical decision level considers the mathematical optimization for decentralized supply chain networks is adopted. These decision areas and the performance of the proposed framework interaction are studied along the different case studies presented in the thesis. On the whole, this thesis represents a step forward toward the integration among the enterprise hierarchical levels, the process and enterprise standardization and improved procedures for decision-making. The aforementioned achievements are boosted by the application of semantic models, which are currently increasingly used.En la actualidad, factores como la globalización del comercio, la incertidumbre del mercado y la feroz competencia implican la disminución de los márgenes de error en las empresas. Dos aspectos claves para lograrlo son la viabilidad y la competitividad de las enterprisesm, que dependen en gran medida la eficacia para la toma de sus decisiones relacionadas con sus características de fabricación, tales como eficiencia económica, la calidad del producto, la flexibilidad y fiabilidad. Por esta razón, las empresas han dado a la tarea, desde hace muchos años, de desarrollar mejores sistemas de gestión de la información con el fin de ayudar a los tomadores de decisiones de explotación de datos y modelos, con el objetivo final de la discusión y mejorar la toma de decisiones. En este sentido, los sistemas de apoyo a las decisiones deben ser mejorados con el fin de hacer frente a la gran cantidad de datos disponibles y la heterogeneidad de los métodos de modelización existentes a lo largo de los niveles jerárquicos en la estructura de la empresa. Por lo tanto, esta tesis se propone la aplicación de ontologías como herramienta de apoyo a la decisión, ya que son cada vez más como una tecnología clave semántica para hacer frente a las heterogeneidades y la mitigación de los problemas que crean y para permitir la extracción de datos por la semántica impulsado la elaboración del conocimiento. El objetivo de esta tesis es contribuir al desarrollo de herramientas de apoyo para la industria de procesos empresariales. Como una herramienta de apoyo a la decisión, debe ser capaz de convertirse en un modelo sólido que interactúa entre los diferentes niveles de decisión jerárquica, proporcionando un marco unificado de datos e integración de los niveles de información. Por otra parte, esta tesis también tiene como objetivo la mejora en el desarrollo del área de ingeniería ontológica. En primer lugar, un estado detallado de la técnica sobre los diferentes sistemas de procesos de producción, la base de la gestión del conocimiento en ontologías, así como los sistemas de soporte de decisiones se ha llevado a cabo. Basado en esa revision, los objetivos específicos de la tesis se plantean. A continuación, se propone una metodología para el desarrollo y uso de ontologías, con base en el análisis y adaptación de las metodologías ya existentes. Dicha metodología se basa en el ciclo de mejora (PSDA), lo que permite una mejor manera de diseñar, construir y aplicar las ontologías de dominio. La segunda parte de esta tesis se dedica a la aplicación de las diferentes partes de la metodología propuesta anteriormente para el desarrollo de un marco ontológico en el ámbito de la industria de procesos relativos a los niveles de decisiones estratégicas, tácticas y operativas. A continuación, la descripción de las áreas de decisión en la que se aplica el marco ontológico se presenta. Es decir, en el nivel de decision de proceso de control, el control de la coordinación se considera. En cuanto al nivel de decisiones de programación de la producción, los métodos matemáticos de optimización se aplican. Finalmente, el nivel jerárquico distribuido decisión considera la optimización matemática de las redes descentralizadas de la cadena de suministro que se adopte. Estas áreas de decisión y el desempeño de la interacción marco propuesto se estudian a lo largo de los diferentes casos de estudio presentados en la tesis. En general, esta tesis supone un paso hacia adelante en la integración entre los niveles jerárquicos de la empresa, el proceso y la estandarización de la empresa y mejorar los procedimientos de toma de decisiones. Los logros mencionados se potencian mediante la aplicación de modelos semánticos, que actualmente se utilizan cada vez más.Award-winningPostprint (published version

Modeling Dislocation Dynamics Data Using Semantic Web Technologies

Research in the field of Materials Science and Engineering focuses on the design, synthesis, properties, and performance of materials. An important class of materials that is widely investigated are crystalline materials, including metals and semiconductors. Crystalline material typically contains a distinct type of defect called "dislocation". This defect significantly affects various material properties, including strength, fracture toughness, and ductility. Researchers have devoted a significant effort in recent years to understanding dislocation behavior through experimental characterization techniques and simulations, e.g., dislocation dynamics simulations. This paper presents how data from dislocation dynamics simulations can be modeled using semantic web technologies through annotating data with ontologies. We extend the already existing Dislocation Ontology by adding missing concepts and aligning it with two other domain-related ontologies (i.e., the Elementary Multi-perspective Material Ontology and the Materials Design Ontology) allowing for representing the dislocation simulation data efficiently. Moreover, we show a real-world use case by representing the discrete dislocation dynamics data as a knowledge graph (DisLocKG) that illustrates the relationship between them. We also developed a SPARQL endpoint that brings extensive flexibility to query DisLocKG

A network of ontologies for the integration of planning and scheduling activities in batch process industries

In the last decades, the integration of informatics applications supporting planning, scheduling and control has been a serious concern of the industrial community. Many standards have been developed to tackle this issue by addressing the exchange of data between the scheduling function and its immediate lower and upper levels in the planning pyramid. However, a more comprehensive approach is required to tackle integration problems, since this matter entails much more than data exchange. So, this article presents an ontological framework that provides the foundations to reach an effective interoperability among the various applications linked to scheduling activities.Sociedad Argentina de Informática e Investigación Operativa (SADIO

A network of ontologies for the integration of planning and scheduling activities in batch process industries

In the last decades, the integration of informatics applications supporting planning, scheduling and control has been a serious concern of the industrial community. Many standards have been developed to tackle this issue by addressing the exchange of data between the scheduling function and its immediate lower and upper levels in the planning pyramid. However, a more comprehensive approach is required to tackle integration problems, since this matter entails much more than data exchange. So, this article presents an ontological framework that provides the foundations to reach an effective interoperability among the various applications linked to scheduling activities.Sociedad Argentina de Informática e Investigación Operativa (SADIO

The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions.

BACKGROUND: The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models. FINDINGS: We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described. CONCLUSIONS: RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are