Towards concept identification using a knowledge-intensive approach

This paper presents a method for identifying concepts in microposts and classifying them into a predefined set of categories. The method relies on the DBpedia knowledge base to identify the types of the concepts detected in the messages. For those concepts that are not classified in the ontology we infer their types via the ontology properties which characterise the type.

Innovation in consulting firms: an area to explore

Services are the most representative sector in developed economies due to their contribution to GDP and employment. Consulting firms are classified as part of the Knowledge Intensive Business Services (KIBS) and provide professional services to all types of organizations. Consulting firms usually innovate with their customers and suppliers in a nurturing environment for value co-creation. This environment is project-based, process-oriented and with intensive knowledge exchange among all stakeholders. Based on literature review, it has been found that despite the existence of frameworks for service innovation, none of them have specifically focused on consulting firms. Further implications on this issue are addressed for both academics and practitioners.

Semantic Service Discovery Techniques for the composable web

This PhD thesis contributes to the problem of resource and service discovery in the context of the composable web. In the current web, mashup technologies allow developers reusing services and contents to build new web applications. However, developers face a problem of information flood when searching for appropriate services or resources for their combination. To contribute to overcoming this problem, a framework is defined for the discovery of services and resources. In this framework, three levels are defined for performing discovery at content, discovery and agente levels. The content level involves the information available in web resources. The web follows the Representational Stateless Transfer (REST) architectural style, in which resources are returned as representations from servers to clients. These representations usually employ the HyperText Markup Language (HTML), which, along with Content Style Sheets (CSS), describes the markup employed to render representations in a web browser. Although the use of SemanticWeb standards such as Resource Description Framework (RDF) make this architecture suitable for automatic processes to use the information present in web resources, these standards are too often not employed, so automation must rely on processing HTML. This process, often referred as Screen Scraping in the literature, is the content discovery according to the proposed framework. At this level, discovery rules indicate how the different pieces of data in resources’ representations are mapped onto semantic entities. By processing discovery rules on web resources, semantically described contents can be obtained out of them. The service level involves the operations that can be performed on the web. The current web allows users to perform different tasks such as search, blogging, e-commerce, or social networking. To describe the possible services in RESTful architectures, a high-level feature-oriented service methodology is proposed at this level. This lightweight description framework allows defining service discovery rules to identify operations in interactions with REST resources. The discovery is thus performed by applying discovery rules to contents discovered in REST interactions, in a novel process called service probing. Also, service discovery can be performed by modelling services as contents, i.e., by retrieving Application Programming Interface (API) documentation and API listings in service registries such as ProgrammableWeb. For this, a unified model for composable components in Mashup-Driven Development (MDD) has been defined after the analysis of service repositories from the web. The agent level involves the orchestration of the discovery of services and contents. At this level, agent rules allow to specify behaviours for crawling and executing services, which results in the fulfilment of a high-level goal. Agent rules are plans that allow introspecting the discovered data and services from the web and the knowledge present in service and content discovery rules to anticipate the contents and services to be found on specific resources from the web. By the definition of plans, an agent can be configured to target specific resources. The discovery framework has been evaluated on different scenarios, each one covering different levels of the framework. Contenidos a la Carta project deals with the mashing-up of news from electronic newspapers, and the framework was used for the discovery and extraction of pieces of news from the web. Similarly, in Resulta and VulneraNET projects the discovery of ideas and security knowledge in the web is covered, respectively. The service level is covered in the OMELETTE project, where mashup components such as services and widgets are discovered from component repositories from the web. The agent level is applied to the crawling of services and news in these scenarios, highlighting how the semantic description of rules and extracted data can provide complex behaviours and orchestrations of tasks in the web. The main contributions of the thesis are the unified framework for discovery, which allows configuring agents to perform automated tasks. Also, a scraping ontology has been defined for the construction of mappings for scraping web resources. A novel first-order logic rule induction algorithm is defined for the automated construction and maintenance of these mappings out of the visual information in web resources. Additionally, a common unified model for the discovery of services is defined, which allows sharing service descriptions. Future work comprises the further extension of service probing, resource ranking, the extension of the Scraping Ontology, extensions of the agent model, and contructing a base of discovery rules. Resumen La presente tesis doctoral contribuye al problema de descubrimiento de servicios y recursos en el contexto de la web combinable. En la web actual, las tecnologías de combinación de aplicaciones permiten a los desarrolladores reutilizar servicios y contenidos para construir nuevas aplicaciones web. Pese a todo, los desarrolladores afrontan un problema de saturación de información a la hora de buscar servicios o recursos apropiados para su combinación. Para contribuir a la solución de este problema, se propone un marco de trabajo para el descubrimiento de servicios y recursos. En este marco, se definen tres capas sobre las que se realiza descubrimiento a nivel de contenido, servicio y agente. El nivel de contenido involucra a la información disponible en recursos web. La web sigue el estilo arquitectónico Representational Stateless Transfer (REST), en el que los recursos son devueltos como representaciones por parte de los servidores a los clientes. Estas representaciones normalmente emplean el lenguaje de marcado HyperText Markup Language (HTML), que, unido al estándar Content Style Sheets (CSS), describe el marcado empleado para mostrar representaciones en un navegador web. Aunque el uso de estándares de la web semántica como Resource Description Framework (RDF) hace apta esta arquitectura para su uso por procesos automatizados, estos estándares no son empleados en muchas ocasiones, por lo que cualquier automatización debe basarse en el procesado del marcado HTML. Este proceso, normalmente conocido como Screen Scraping en la literatura, es el descubrimiento de contenidos en el marco de trabajo propuesto. En este nivel, un conjunto de reglas de descubrimiento indican cómo los diferentes datos en las representaciones de recursos se corresponden con entidades semánticas. Al procesar estas reglas sobre recursos web, pueden obtenerse contenidos descritos semánticamente. El nivel de servicio involucra las operaciones que pueden ser llevadas a cabo en la web. Actualmente, los usuarios de la web pueden realizar diversas tareas como búsqueda, blogging, comercio electrónico o redes sociales. Para describir los posibles servicios en arquitecturas REST, se propone en este nivel una metodología de alto nivel para descubrimiento de servicios orientada a funcionalidades. Este marco de descubrimiento ligero permite definir reglas de descubrimiento de servicios para identificar operaciones en interacciones con recursos REST. Este descubrimiento es por tanto llevado a cabo al aplicar las reglas de descubrimiento sobre contenidos descubiertos en interacciones REST, en un nuevo procedimiento llamado sondeo de servicios. Además, el descubrimiento de servicios puede ser llevado a cabo mediante el modelado de servicios como contenidos. Es decir, mediante la recuperación de documentación de Application Programming Interfaces (APIs) y listas de APIs en registros de servicios como ProgrammableWeb. Para ello, se ha definido un modelo unificado de componentes combinables para Mashup-Driven Development (MDD) tras el análisis de repositorios de servicios de la web. El nivel de agente involucra la orquestación del descubrimiento de servicios y contenidos. En este nivel, las reglas de nivel de agente permiten especificar comportamientos para el rastreo y ejecución de servicios, lo que permite la consecución de metas de mayor nivel. Las reglas de los agentes son planes que permiten la introspección sobre los datos y servicios descubiertos, así como sobre el conocimiento presente en las reglas de descubrimiento de servicios y contenidos para anticipar contenidos y servicios por encontrar en recursos específicos de la web. Mediante la definición de planes, un agente puede ser configurado para descubrir recursos específicos. El marco de descubrimiento ha sido evaluado sobre diferentes escenarios, cada uno cubriendo distintos niveles del marco. El proyecto Contenidos a la Carta trata de la combinación de noticias de periódicos digitales, y en él el framework se ha empleado para el descubrimiento y extracción de noticias de la web. De manera análoga, en los proyectos Resulta y VulneraNET se ha llevado a cabo un descubrimiento de ideas y de conocimientos de seguridad, respectivamente. El nivel de servicio se cubre en el proyecto OMELETTE, en el que componentes combinables como servicios y widgets se descubren en repositorios de componentes de la web. El nivel de agente se aplica al rastreo de servicios y noticias en estos escenarios, mostrando cómo la descripción semántica de reglas y datos extraídos permiten proporcionar comportamientos complejos y orquestaciones de tareas en la web. Las principales contribuciones de la tesis son el marco de trabajo unificado para descubrimiento, que permite configurar agentes para realizar tareas automatizadas. Además, una ontología de extracción ha sido definida para la construcción de correspondencias y extraer información de recursos web. Asimismo, un algoritmo para la inducción de reglas de lógica de primer orden se ha definido para la construcción y el mantenimiento de estas correspondencias a partir de la información visual de recursos web. Adicionalmente, se ha definido un modelo común y unificado para el descubrimiento de servicios que permite la compartición de descripciones de servicios. Como trabajos futuros se considera la extensión del sondeo de servicios, clasificación de recursos, extensión de la ontología de extracción y la construcción de una base de reglas de descubrimiento.

A Description Framework and Event-Driven Architecture for the Semantic Web and Semantic Grid

In this introductory chapter we put in context and give a brief outline of the work that we thoroughly present in the rest of the dissertation. We consider this work divided in two main parts. The first part is the Firenze Framework, a knowledge level description framework rich enough to express the semantics required for describing both semantic Web services and semantic Grid services. We start by defining what the Semantic Grid is and its relation with the Semantic Web; and the possibility of their convergence since both initiatives have become mainly service-oriented. We also introduce the main motivators of the creation of this framework, one is to provide a valid description framework that works at knowledge level; the other to provide a description framework that takes into account the characteristics of Grid services in order to be able to describe them properly. The other part of the dissertation is devoted to Vega, an event-driven architecture that, by means of proposed knowledge level description framework, is able to achieve high scale provisioning of knowledge-intensive services. In this introductory chapter we portrait the anatomy of a generic event-driven architecture, and we briefly enumerate their main characteristics, which are the reason that make them our choice.

The role of a firm's absorptive capacity and the technology transfer process in clusters: How effective are technology centres in low-tech clusters?

This paper analyses how the internal resources of small- and medium-sized enterprises determine access (learning processes) to technology centres (TCs) or industrial research institutes (innovation infrastructure) in traditional low-tech clusters. These interactions basically represent traded (market-based) transactions, which constitute important sources of knowledge in clusters. The paper addresses the role of TCs in low-tech clusters, and uses semi-structured interviews with 80 firms in a manufacturing cluster. The results point out that producer–user interactions are the most frequent; thus, the higher the sector knowledge-intensive base, the more likely the utilization of the available research infrastructure becomes. Conversely, the sectors with less knowledge-intensive structures, i.e. less absorptive capacity (AC), present weak linkages to TCs, as they frequently prefer to interact with suppliers, who act as transceivers of knowledge. Therefore, not all the firms in a cluster can fully exploit the available research infrastructure, and their AC moderates this engagement. In addition, the existence of TCs is not sufficient since the active role of a firm's search strategies to undertake interactions and conduct openness to available sources of knowledge is also needed. The study has implications for policymakers and academia.

Data-Intensive architecture for scientific knowledge discovery

This paper presents a data-intensive architecture that demonstrates the ability to support applications from a wide range of application domains, and support the different types of users involved in defining, designing and executing data-intensive processing tasks. The prototype architecture is introduced, and the pivotal role of DISPEL as a canonical language is explained. The architecture promotes the exploration and exploitation of distributed and heterogeneous data and spans the complete knowledge discovery process, from data preparation, to analysis, to evaluation and reiteration. The architecture evaluation included large-scale applications from astronomy, cosmology, hydrology, functional genetics, imaging processing and seismology.

Identifying the core competence as a key requirement for business model innovation. The case of Airlines as a service industry

Core competencies form the basis of an organization’s skills and the basic element of a successful strategic execution. Identifying and strengthening the core competencies enhances flexibility thereby strategically positioning a firm for responding to competition in the dynamic marketplace and can be the difference in quality among firms that follow the same business model. A correct understanding of the concept of business models, employing the right core competencies, organizing them effectively and building the business model around the competencies that are constantly gained and assimilated can result in enhanced business performance and thus having implications for firms that want to innovate their business models. Flexibility can be the firm’s agility to shift focus in response to external factors such as changing markets, new technologies or competition and a firm’s success can be gauged by the ability it displays in this transition. Although industry transformations generally emanate from technological changes, recent examples suggests they may also be due to the introduction of new business models and nowhere is it more relevant than in the airline industry. An analysis of the business model flexibility of 17 Airlines from Asia, Europe and Oceania, that is done with core competence as the indicator reveals a picture of inconsistencies in the core competence strategy of certain airlines and the corresponding reduction in business performance. The performance variations are explained from a service oriented core competence strategy employed by airlines that ultimately enables them in having a flexible business model that not only increases business performance but also helps in reducing the uncertainties in the internal and external operating environments. This is more relevant in the case of airline industry, as the product (the air transportation of passengers) minus the service competence is all the same.

Caracterización de Sistemas intensivos en Software desde un punto de vista de innovación=Characterizing Software-intensive Systems from the innovation point of view

La innovación en Sistemas Intesivos en Software está alcanzando relevancia por múltiples razones: el software está presente en sectores como automóvil, teléfonos móviles o salud. Las empresas necesitan conocer aquellos factores que afectan a la innovación para incrementar las probabilidades de éxito en el desarrollo de sus productos y, la evaluación de productos sofware es un mecanismo potente para capturar este conocimiento. En consecuencia, las empresas necesitan evaluar sus productos desde la perpectiva de innovación para reducir la distancia entre los productos desarrollados y el mercado. Esto es incluso más relevante en el caso de los productos intensivos en software, donde el tiempo real, la oportunidad, complejidad, interoperabilidad, capacidad de respuesta y compartción de recursos son características críticas de los nuevos sistemas. La evaluación de la innovación de productos ya ha sido estudiada y se han definido algunos esquemas de evaluación pero no son específicos para Sistemas intensivos en Sofwtare; además, no se ha alcanzado consenso en los factores ni el procedimiento de evaluación. Por lo tanto, tiene sentido trabajar en la definición de un marco de evaluación de innovación enfocado a Sistemas intesivos en Software. Esta tesis identifica los elementos necesarios para construir in marco para la evaluación de de Sistemas intensivos en Software desde el punto de vista de la innovación. Se han identificado dos componentes como partes del marco de evaluación: un modelo de referencia y una herramienta adaptativa y personalizable para la realización de la evaluación y posicionamiento de la innovación. El modelo de referencia está compuesto por cuatro elementos principales que caracterizan la evaluación de innovación de productos: los conceptos, modelos de innovación, cuestionarios de evaluación y la evaluación de productos. El modelo de referencia aporta las bases para definir instancias de los modelos de evaluación de innovación de productos que pueden se evaluados y posicionados en la herramienta a través de cuestionarios y que de forma automatizada aporta los resultados de la evaluación y el posicionamiento respecto a la innovación de producto. El modelo de referencia ha sido rigurosamente construido aplicando modelado conceptual e integración de vistas junto con la aplicación de métodos cualitativos de investigación. La herramienta ha sido utilizada para evaluar productos como Skype a través de la instanciación del modelo de referencia. ABSTRACT Innovation in Software intensive Systems is becoming relevant for several reasons: software is present embedded in many sectors like automotive, robotics, mobile phones or heath care. Firms need to have knowledge about factors affecting the innovation to increase the probability of success in their product development and the assessment of innovation in software products is a powerful mechanism to capture this knowledge. Therefore, companies need to assess products from an innovation perspective to reduce the gap between their developed products and the market. This is even more relevant in the case of SiSs, where real time, timeliness, complexity, interoperability, reactivity, and resource sharing are critical features of a new system. Many authors have analysed product innovation assessment and some schemas have been developed but they are not specific to SiSs; in addition, there is no consensus about the factors or the procedures for performing an assessment. Therefore, it has sense to work in the definition of a customized software product innovation evaluation framework. This thesis identifies the elements needed to build a framework to assess software products from the innovation perspective. Two components have been identified as part of the framework to assess Software intensive Systems from the innovation perspective: a reference-model and an adaptive and customizable tool to perform the assessment and to position product innovation. The reference-model is composed by four main elements characterizing product innovation assessment: concepts, innovation models, assessment questionnaires and product assessment. The reference model provides the umbrella to define instances of product innovation assessment models that can be assessed and positioned through questionnaires in the proposed tool that also provides automation in the assessment and positioning of innovation. The reference-model has been rigorously built by applying conceptual modelling and view integration integrated with qualitative research methods. The tool has been used to assess products like Skype through models instantiated from the reference-model.