How does your model grow? An empirical investigation of the effects of ontological clarity and application domain size on query performance

Semantic data models provide a map of the components of an information system. The characteristics of these models affect their usefulness for various tasks (e.g., information retrieval). The quality of information retrieval has obvious important consequences, both economic and otherwise. Traditionally, data base designers have produced parsimonious logical data models. In spite of their increased size, ontologically clearer conceptual models have been shown to facilitate better performance for both problem solving and information retrieval tasks in experimental settings. The experiments producing evidence of enhanced performance for ontologically clearer models have, however, used application domains of modest size. Data models in organizational settings are likely to be substantially larger than those used in these experiments. This research used an experiment to investigate whether the benefits of improved information retrieval performance associated with ontologically clearer models are robust as the size of the application domains increase. The experiment used an application domain of approximately twice the size as tested in prior experiments. The results indicate that, relative to the users of the parsimonious implementation, end users of the ontologically clearer implementation made significantly more semantic errors, took significantly more time to compose their queries, and were significantly less confident in the accuracy of their queries.

Understanding conceptual schemas: exploring the role of application and IS domain knowledge

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.

Applications of graph transformation in tools for domain-specific modeling languages

The use of domain-specific languages (DSLs) has been proposed as an approach to cost-e ectively develop families of software systems in a restricted application domain. Domain-specific languages in combination with the accumulated knowledge and experience of previous implementations, can in turn be used to generate new applications with unique sets of requirements. For this reason, DSLs are considered to be an important approach for software reuse. However, the toolset supporting a particular domain-specific language is also domain-specific and is per definition not reusable. Therefore, creating and maintaining a DSL requires additional resources that could be even larger than the savings associated with using them. As a solution, di erent tool frameworks have been proposed to simplify and reduce the cost of developments of DSLs. Developers of tool support for DSLs need to instantiate, customize or configure the framework for a particular DSL. There are di erent approaches for this. An approach is to use an application programming interface (API) and to extend the basic framework using an imperative programming language. An example of a tools which is based on this approach is Eclipse GEF. Another approach is to configure the framework using declarative languages that are independent of the underlying framework implementation. We believe this second approach can bring important benefits as this brings focus to specifying what should the tool be like instead of writing a program specifying how the tool achieves this functionality. In this thesis we explore this second approach. We use graph transformation as the basic approach to customize a domain-specific modeling (DSM) tool framework. The contributions of this thesis includes a comparison of di erent approaches for defining, representing and interchanging software modeling languages and models and a tool architecture for an open domain-specific modeling framework that e ciently integrates several model transformation components and visual editors. We also present several specific algorithms and tool components for DSM framework. These include an approach for graph query based on region operators and the star operator and an approach for reconciling models and diagrams after executing model transformation programs. We exemplify our approach with two case studies MICAS and EFCO. In these studies we show how our experimental modeling tool framework has been used to define tool environments for domain-specific languages.

Touch ‘n’ sketch: pen and fingers on a multi-touch sketch application for tablet PC’s

In many creative and technical areas, professionals make use of paper sketches for developing and expressing concepts and models. Paper offers an almost constraint free environment where they have as much freedom to express themselves as they need. However, paper does have some disadvantages, such as size and not being able to manipulate the content (other than remove it or scratch it), which can be overcome by creating systems that can offer the same freedom people have from paper but none of the disadvantages and limitations. Only in recent years has the technology become massively available that allows doing precisely that, with the development in touch‐sensitive screens that also have the ability to interact with a stylus. In this project a prototype was created with the objective of finding a set of the most useful and usable interactions, which are composed of combinations of multi‐touch and pen. The project selected Computer Aided Software Engineering (CASE) tools as its application domain, because it addresses a solid and well‐defined discipline with still sufficient room for new developments. This was the result from the area research conducted to find an application domain, which involved analyzing sketching tools from several possible areas and domains. User studies were conducted using Model Driven Inquiry (MDI) to have a better understanding of the human sketch creation activities and concepts devised. Then the prototype was implemented, through which it was possible to execute user evaluations of the interaction concepts created. Results validated most interactions, in the face of limited testing only being possible at the time. Users had more problems using the pen, however handwriting and ink recognition were very effective, and users quickly learned the manipulations and gestures from the Natural User Interface (NUI).

The Moldable Inspector: a framework for domain-specific object inspection

Answering run-time questions in object-oriented systems involves reasoning about and exploring connections between multiple objects. Developer questions exercise various aspects of an object and require multiple kinds of interactions depending on the relationships between objects, the application domain and the differing developer needs. Nevertheless, traditional object inspectors, the essential tools often used to reason about objects, favor a generic view that focuses on the low-level details of the state of individual objects. This leads to an inefficient effort, increasing the time spent in the inspector. To improve the inspection process, we propose the Moldable Inspector, a novel approach for an extensible object inspector. The Moldable Inspector allows developers to look at objects using multiple interchangeable presentations and supports a workflow in which multiple levels of connecting objects can be seen together. Both these aspects can be tailored to the domain of the objects and the question at hand. We further exemplify how the proposed solution improves the inspection process, introduce a prototype implementation and discuss new directions for extending the Moldable Inspector.

Methodology for developing a Speech into Sign Language Translation System in a New Semantic Domain

This paper proposes a methodology for developing a speech into sign language translation system considering a user-centered strategy. This method-ology consists of four main steps: analysis of technical and user requirements, data collection, technology adaptation to the new domain, and finally, evalua-tion of the system. The two most demanding tasks are the sign generation and the translation rules generation. Many other aspects can be updated automatical-ly from a parallel corpus that includes sentences (in Spanish and LSE: Lengua de Signos Española) related to the application domain. In this paper, we explain how to apply this methodology in order to develop two translation systems in two specific domains: bus transport information and hotel reception.

Practical domain-specific debuggers using the Moldable Debugger framework

Understanding the run-time behavior of software systems can be a challenging activity. Debuggers are an essential category of tools used for this purpose as they give developers direct access to the running systems. Nevertheless, traditional debuggers rely on generic mechanisms to introspect and interact with the running systems, while developers reason about and formulate domain-specific questions using concepts and abstractions from their application domains. This mismatch creates an abstraction gap between the debugging needs and the debugging support leading to an inefficient and error-prone debugging effort, as developers need to recover concrete domain concepts using generic mechanisms. To reduce this gap, and increase the efficiency of the debugging process, we propose a framework for developing domain-specific debuggers, called the Moldable Debugger, that enables debugging at the level of the application domain. The Moldable Debugger is adapted to a domain by creating and combining domain-specific debugging operations with domain-specific debugging views, and adapts itself to a domain by selecting, at run time, appropriate debugging operations and views. To ensure the proposed model has practical applicability (i.e., can be used in practice to build real debuggers), we discuss, from both a performance and usability point of view, three implementation strategies. We further motivate the need for domain-specific debugging, identify a set of key requirements and show how our approach improves debugging by adapting the debugger to several domains.

Suporte a testes automáticos em aplicações web geradas com a OutSystems Platform

Dissertação de natureza científica para obtenção do grau de Mestre em Engenharia Informática e de Computadores

ENCOURAGE architecture: support for heterogeneous smart grids

Our society relies on energy for most of its activities. One application domain inciding heavily on the energy budget regards the energy consumption in residential and non-residential buildings. The ever increasing needs for energy, resulting from the industrialization of developing countries and from the limited scalability of the traditional technologies for energy production, raises both problems and opportunities. The problems are related to the devastating effects of the greenhouse gases produced by the burning of oil and gas for energy production, and from the dependence of whole countries on companies providing gas and oil. The opportunities are mostly technological, since novel markets are opening for both energy production via renewable sources, and for innovations that can rationalize energy usage. An enticing research effort can be the mixing of these two aspects, by leveraging on ICT technologies to rationalize energy production, acquisition, and consumption. The ENCOURAGE project aims to develop embedded intelligence and integration technologies that will directly optimize energy use in buildings and enable active participation in the future smart grid environment.The primary application domains targeted by the ENCOURAGE project are non-residential buildings (e.g.: campuses) and residential buildings (e.g.: neighborhoods). The goal of the project is to achieve 20% of energy savings through the improved interoperability between various types of energy generation, consumption and storage devices; interbuilding energy exchange; and systematic performance monitoring.

Plataforma de negociação de componentes multimédia

O objectivo da tese é demonstrar a adequação do paradigma dos mercados electrónicos baseados em agentes para transaccionar objectos multimédia em função do perfil dos espectadores. Esta dissertação descreve o projecto realizado no âmbito da plataforma de personalização de conteúdos em construção. O domínio de aplicação adoptado foi a personalização dos intervalos publicitários difundidos pelos distribuidores de conteúdos multimédia, i.e., pretende-se gerar em tempo útil o alinhamento de anúncios publicitários que melhor se adeqúe ao perfil de um espectador ou de um grupo de espectadores. O projecto focou-se no estudo e selecção das tecnologias de suporte, na concepção da arquitectura e no desenvolvimento de um protótipo que permitisse realizar diversas experiências nomeadamente com diferentes estratégias e tipos de mercado. A arquitectura proposta para a plataforma consiste num sistema multiagente organizado em três camadas que disponibiliza interfaces do tipo serviço Web com o exterior. A camada de topo é constituída por agentes de interface com o exterior. Na camada intermédia encontram-se os agentes autónomos que modelam as entidades produtoras e consumidoras de componentes multimédia assim como a entidade reguladora do mercado. Estes agentes registam-se num serviço de registo próprio onde especificam os componentes multimédia que pretendem negociar. Na camada inferior realiza-se o mercado que é constituído por agentes delegados dos agentes da camada superior. O lançamento do mercado é efectuado através de uma interface e consiste na escolha do tipo de mercado e no tipo de itens a negociar. Este projecto centrou-se na realização da camada do mercado e da parte da camada intermédia de apoio às actividades de negociação no mercado. A negociação é efectuada em relação ao preço da transmissão do anúncio no intervalo em preenchimento. Foram implementados diferentes perfis de negociação com tácticas, incrementos e limites de variação de preço distintos. Em termos de protocolos de negociação, adoptou-se uma variante do Iterated Contract Net – o Fixed Iterated Contract Net. O protótipo resultante foi testado e depurado com sucesso.

An Approach To Publish a Data Warehouse Content as Linked Data

Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão

Framework-specific DSL para sensoriamento participado

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Sistema de apoio à racionalização da utilização de energia eléctrica

Esta dissertação descreve o sistema de apoio à racionalização da utilização de energia eléctrica desenvolvido no âmbito da unidade curricular de Tese/Dissertação. O domínio de aplicação enquadra-se no contexto da Directiva da União Europeia 2006/32/EC que declara ser necessário colocar à disposição dos consumidores a informação e os meios que promovam a redução do consumo e o aumento da eficiência energética individual. O objectivo é o desenvolvimento de uma solução que permita a representação gráfica do consumo/produção, a definição de tectos de consumo, a geração automática de alertas e alarmes, a comparação anónima com clientes com perfil idêntico por região e a previsão de consumo/produção no caso de clientes industriais. Trata-se de um sistema distribuído composto por front-end e back-end. O front-end é composto pelas aplicações de interface com o utilizador desenvolvidas para dispositivos móveis Android e navegadores Web. O back-end efectua o armazenamento e processamento de informação e encontra-se alojado numa plataforma de cloud computing – o Google App Engine – que disponibiliza uma interface padrão do tipo serviço Web. Esta opção assegura interoperabilidade, escalabilidade e robustez ao sistema. Descreve-se em detalhe a concepção, desenvolvimento e teste do protótipo realizado, incluindo: (i) as funcionalidades de gestão e análise de consumo e produção de energia implementadas; (ii) as estruturas de dados; (iii) a base de dados e o serviço Web; e (iv) os testes e a depuração efectuados. (iv) Por fim, apresenta-se o balanço deste projecto e efectuam-se sugestões de melhoria.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

How realistic is the mixed-criticality real-time system model?

23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France. Best Paper Award Nominee