Plataforma de gestão M2M

Mestrado em Engenharia de Computadores e TelemáticaThe Internet of Things is still a fast growing area and topic of interest. New solutions and implementations keep emerging, both in service oriented solutions or device oriented solutions with M2M communications, therefore promoting the creation of new business models. Thus, as a natural evolution, came the possibility to abstract sensor management from service creation. Allowing a delegation of sensor management from the sensor providers, to focus on content creation through services. However, this delegation brings new concerns regarding access control. Consequently, this dissertation proposes a possible solution to this problem, enclosed in a service oriented platform interconnected with an ETSI M2M solution. Promoting interoperability between sensors and allowing a great elasticity in service creation.A Internet das Coisas continua a ser uma área em grande crescimento e de grande interesse. Estão constantemente a surgir novas soluções e inplementações, tanto ao nível dos serviços como ao nível das comunicações Máquina-a-Máquina, promovendo assim o aparecimento de novos modelos de negócio. Desta forma surgiu naturalmente a possibilidade de abstrair a gestão de sensores da criação de serviços. Permitindo assim, uma delagação da gestão por parte de empresas detentoras de sensores, para se focarem no conteúdo com a criação de serviços. Contudo esta divisão acarreta algumas preocupações de segurança quanto ao controlo de acesso. Nesse sentido, esta dissertação propõe uma possível solução para o mesmo, englobada numa plataforma orientada ao serviços interligada com uma solução ETSI M2M. Promovendo a interoperabilidade entre sensores e permitindo assim uma grande elasticidade na criação de serviços

Complex Event Processing with XChangeEQ

The emergence of event-driven architectures, automation of business processes, drastic cost-reductions in sensor technology, and a growing need to monitor IT systems (as well as other systems) due to legal, contractual, or operational considerations lead to an increasing generation of events. This development is accompanied by a growing demand for managing and processing events in an automated and systematic way. Complex Event Processing (CEP) encompasses the (automatable) tasks involved in making sense of all events in a system by deriving higher-level knowledge from lower-level events while the events occur, i.e., in a timely, online fashion and permanently. At the core of CEP are queries which monitor streams of "simple" events for so-called complex events, that is, events or situations that manifest themselves in certain combinations of several events occurring (or not occurring) over time and that cannot be detected from looking only at single events. Querying events is fundamentally different from traditional querying and reasoning with database or Web data, since event queries are standing queries that are evaluated permanently over time against incoming streams of event data. In order to express complex events that are of interest to a particular application or user in a convenient, concise, cost-effective and maintainable manner, special purpose Event Query Languages (EQLs) are needed. This thesis investigates practical and theoretical issues related to querying complex events, covering the spectrum from language design over declarative semantics to operational semantics for incremental query evaluation. Its central topic is the development of the high-level event query language XChangeEQ. In contrast to previous data stream and event query languages, XChangeEQ's language design recognizes the four querying dimensions of data extractions, event composition, temporal relationships, and, for non-monotonic queries involving negation or aggregation, event accumulation. XChangeEQ deals with complex structured data in event messages, thus addressing the need to query events communicated in XML formats over the Web. It supports deductive rules as an abstraction and reasoning mechanism for events. To achieve a full coverage of the four querying dimensions, it builds upon a separation of concerns of the four querying dimensions, which makes it easy-to-use and highly expressive. A recurrent theme in the formal foundations of XChangeEQ is that, despite the fundamental differences between traditional database queries and event queries, many well-known results from databases and logic programming are, with some importance changes, applicable to event queries. Declarative semantics for XChangeEQ are given as a (Tarski-style) model theory with accompanying fixpoint theory. This approach accounts well for (1) data in events and (2) deductive rules defining new events from existing ones, two aspects often neglected in previous work of semantics of EQLs. For the evaluation of event queries, this work introduces operational semantics based on an extended and tailored form of relational algebra and query plans with materialization points. Materialization points account for storing and maintaining information about those received events that are relevant for, i.e., can contribute to, future query answers, as well as for an incremental evaluation that avoids recomputing certain intermediate results. Efficient state maintenance in incremental evaluation is approached by "differentiating" algebra expressions, i.e., by deriving expressions for computing only the changes to materialization points. Knowing how long an event is relevant is a prerequisite for performing garbage collection during event query evaluation and also of central importance for developing cost-based query planners. To this end, this thesis introduces a notion of relevance of events (to a given query plan) and develops methods for determining temporal relevance, a particularly useful form based on time-related information

Intermediary XML schemas

The methodology of intermediary XML schemas is introduced and its application to complex metadata environments is explored. Intermediary schemas are designed to mediate to other ‘referent’ schemas: instances conforming to these are not generally intended for dissemination but must usually be realized by XSLT transformations for delivery. In some cases, these schemas may also generate instances conforming to themselves. Three subsidiary methods of this methodology are introduced. The first is application-specific schemas that act as intermediaries to established schemas which are problematic by virtue of their over-complexity or flexibility. The second employs the METS packaging standard as a template for navigating instances of a complex schema by defining an abstract map of its instances. The third employs the METS structural map to define templates or conceptual models from which instances of metadata for complex applications may be realized by XSLT transformations. The first method is placed in the context of earlier approaches to semantic interoperability such as crosswalks, switching across, derivation and application profiles. The second is discussed in the context of such methods for mapping complex objects as OAI-ORE and the Fedora Content Model Architecture. The third is examined in relation to earlier approaches to templating within XML architectures. The relevance of these methods to contemporary research is discussed in three areas: digital ecosystems, archival description and Linked Open Data in digital asset management and preservation. Their relevance to future research is discussed in the form of suggested enhancements to each, a possible synthesis of the second and third to overcome possible problems of interoperability presented by the first, and their potential role in future developments in digital preservation. This methodology offers an original approach to resolving issues of interoperability and the management of complex metadata environments; it significantly extends earlier techniques and does so entirely within XML architectures

Reinventing the Social Scientist and Humanist in the Era of Big Data

This book explores the big data evolution by interrogating the notion that big data is a disruptive innovation that appears to be challenging existing epistemologies in the humanities and social sciences. Exploring various (controversial) facets of big data such as ethics, data power, and data justice, the book attempts to clarify the trajectory of the epistemology of (big) data-driven science in the humanities and social sciences

Resource discovery in heterogeneous digital content environments

The concept of 'resource discovery' is central to our understanding of how users explore, navigate, locate and retrieve information resources. This submission for a PhD by Published Works examines a series of 11 related works which explore topics pertaining to resource discovery, each demonstrating heterogeneity in their digital discovery context. The assembled works are prefaced by nine chapters which seek to review and critically analyse the contribution of each work, as well as provide contextualization within the wider body of research literature. A series of conceptual sub-themes is used to organize and structure the works and the accompanying critical commentary. The thesis first begins by examining issues in distributed discovery contexts by studying collection level metadata (CLM), its application in 'information landscaping' techniques, and its relationship to the efficacy of federated item-level search tools. This research narrative continues but expands in the later works and commentary to consider the application of Knowledge Organization Systems (KOS), particularly within Semantic Web and machine interface contexts, with investigations of semantically aware terminology services in distributed discovery. The necessary modelling of data structures to support resource discovery - and its associated functionalities within digital libraries and repositories - is then considered within the novel context of technology-supported curriculum design repositories, where questions of human-computer interaction (HCI) are also examined. The final works studied as part of the thesis are those which investigate and evaluate the efficacy of open repositories in exposing knowledge commons to resource discovery via web search agents. Through the analysis of the collected works it is possible to identify a unifying theory of resource discovery, with the proposed concept of (meta)data alignment described and presented with a visual model. This analysis assists in the identification of a number of research topics worthy of further research; but it also highlights an incremental transition by the present author, from using research to inform the development of technologies designed to support or facilitate resource discovery, particularly at a 'meta' level, to the application of specific technologies to address resource discovery issues in a local context. Despite this variation the research narrative has remained focussed on topics surrounding resource discovery in heterogeneous digital content environments and is noted as having generated a coherent body of work. Separate chapters are used to consider the methodological approaches adopted in each work and the contribution made to research knowledge and professional practice.The concept of 'resource discovery' is central to our understanding of how users explore, navigate, locate and retrieve information resources. This submission for a PhD by Published Works examines a series of 11 related works which explore topics pertaining to resource discovery, each demonstrating heterogeneity in their digital discovery context. The assembled works are prefaced by nine chapters which seek to review and critically analyse the contribution of each work, as well as provide contextualization within the wider body of research literature. A series of conceptual sub-themes is used to organize and structure the works and the accompanying critical commentary. The thesis first begins by examining issues in distributed discovery contexts by studying collection level metadata (CLM), its application in 'information landscaping' techniques, and its relationship to the efficacy of federated item-level search tools. This research narrative continues but expands in the later works and commentary to consider the application of Knowledge Organization Systems (KOS), particularly within Semantic Web and machine interface contexts, with investigations of semantically aware terminology services in distributed discovery. The necessary modelling of data structures to support resource discovery - and its associated functionalities within digital libraries and repositories - is then considered within the novel context of technology-supported curriculum design repositories, where questions of human-computer interaction (HCI) are also examined. The final works studied as part of the thesis are those which investigate and evaluate the efficacy of open repositories in exposing knowledge commons to resource discovery via web search agents. Through the analysis of the collected works it is possible to identify a unifying theory of resource discovery, with the proposed concept of (meta)data alignment described and presented with a visual model. This analysis assists in the identification of a number of research topics worthy of further research; but it also highlights an incremental transition by the present author, from using research to inform the development of technologies designed to support or facilitate resource discovery, particularly at a 'meta' level, to the application of specific technologies to address resource discovery issues in a local context. Despite this variation the research narrative has remained focussed on topics surrounding resource discovery in heterogeneous digital content environments and is noted as having generated a coherent body of work. Separate chapters are used to consider the methodological approaches adopted in each work and the contribution made to research knowledge and professional practice

The impact of semantic knowledge management system on firms' innovation and competitiveness

D.B.A ThesisIn the knowledge economy, knowledge is increasingly becoming the primary factor of production and foundational component of innovation. Firms must improve their capabilities of handling knowledge in line with its recent explosive growth to stay competitive. This research addresses the effects semantic technology-based knowledge management system (Semantic KMS) can have on firms’ performance. Based on existing literature, a conceptual model covering Semantic KMS, KM, innovation, and competitiveness was designed to test the validity of the hypotheses. A total of 640 survey questionnaires were sent to the companies that practice KM actively. 178 usable responses were received. Pearson’s correlation, exploratory and confirmatory factor analyses and structural equation modeling were used to analyze the data. The results indicate that Semantic KMS is positively related to the KM effectiveness. Organizational KM is positively linked to innovation and competitiveness directly. In the context of KM, innovation's effect on competitiveness is not convincing. Moreover, the study could not identify that KM has any strong relationship with organizational competitiveness mediated through innovation. Being one of the first significant studies of Semantic KMS and its impact, the study adds to the growing literature on the use of semantic technology in various fields. It develops a new theoretical model which has never been tested before. The study used data collected from single respondent of each firm in a snapshot and did not consider feedback effects. It examined Semantic KMS as a holistic system, but in many cases, companies only deploy certain KM related tools supported by semantic technology. A different research approach could investigate the impacts of those tools on relevant business processes. This study demonstrates that deployment of semantic technology is beneficial for companies and allows them to take advantage of the use of advanced technologies in their KM quest. It brings significant benefits to the firm thanks to improved capabilities of the new KMS in knowledge discovery, aggregation, use, and sharing. The study also confirms that for a successful KM initiative, KM processes need to be optimized and supported by KMS. Semantic technology is a set of advanced tools used lately in many information systems. This study is one of the first in-depth research about their impacts on KMS. It will guide KM managers in their decision-making process when they consider developing or integrating newKMS tools. For academics, this research highlights the importance of investigating KM from the new technology perspective.

B!SON: A Tool for Open Access Journal Recommendation

Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)