Exploring and visualizing the ”Alma” of XML documents

In this paper we introduce eXVisXML, a visual tool to explore documents annotated with the mark-up language XML, in order to easily perform over them tasks as knowledge extraction or document engineering. eXVisXML was designed mainly for two kind of users. Those who want to analyze an annotated document to explore the information contained, for them a visual inspection tool can be of great help, and a slicing functionality can be an efective complement. The other target group is composed by document engineers who might be interested in assessing the quality of the annotation created. This can be achieved through the measurements of some parameters that will allow to compare the elements and attributes of the DTD/Schema against those efectively used in the document instances. Both functionalities and the way they were delineated and implemented will be discussed along the paper.FC

XML: aplicações e tecnologias associadas: 6th National Conference

This volume contains the papers presented at the Sixth Portuguese XML Conference, called XATA (XML, Aplicações e Tecnologias Associadas), held in Évora, Portugal, 14-15 February, 2008. The conference followed on from a successful series held throughout Portugal in the last years: XATA2003 was held in Braga, XATA2004 was held in Porto, XATA2005 was held in Braga, XATA2006 was held in Portalegre and XATA2007 was held in Lisboa. Dued to research evaluation criteria that are being used to evaluate researchers and research centers national conferences are becoming deserted. Many did not manage to gather enough submissions to proceed in this scenario. XATA made it through. However with a large decrease in the number of submissions. In this edition a special meeting will join the steering committee with some interested attendees to discuss XATA's future: internationalization, conference model, ... We think XATA is important in the national context. It has succeeded in gathering and identifying a comunity that shares the same research interests and has promoted some colaborations. We want to keep "the wheel spinning"... This edition has its program distributed by first day's afternoon and next day's morning. This way we are facilitating travel arrangements and we will have one night to meet

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Supporting the sensemaking process in visual analytics

Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. It involves interactive exploration of data using visualizations and automated data analysis to gain insight, and to ultimately make better decisions. It aims to support the sensemaking process in which information is collected, organized and analyzed to form new knowledge and inform further action. Interactive visual exploration of the data can lead to many discoveries in terms of relations, patterns, outliers and so on. It is difficult for the human working memory to keep track of all findings during a visual analysis. Also, synthesis of many different findings and relations between those findings increase the information overload and thereby hinders the sensemaking process further. The central theme of this dissertation is How to support users in their sensemaking process during interactive exploration of data? To support the sensemaking process in visual analytics, we mainly focus on how to support users to capture, reuse, review, share, and present the key aspects of interest concerning the analysis process and the findings during interactive exploration of data. For this, we have developed generic models and tools that enable users to capture findings with provenance, and construct arguments; and to review, revise and share their visual analysis. First, we present a sensemaking framework for visual analytics that contains three linked views: a data view, a navigation view and a knowledge view for supporting the sense-making process. The data view offers interactive data visualization tools. The navigation view automatically captures the interaction history using a semantically rich action model and provides an overview of the analysis structure. The knowledge view is a basic graphics editor that helps users to record findings with provenance and to organize findings into claims using diagramming techniques. Users can exploit automatically captured interaction history and manually recorded findings to review and revise their visual analysis. Thus, the analysis process can be archived and shared with others for collaborative visual analysis. Secondly, we enable analysts to capture data selections as semantic zones during an analysis, and to reuse these zones on different subsets of data. We present a Select & Slice table that helps analysts to capture, manipulate, and reuse these zones more explicitly during exploratory data analysis. Users can reuse zones, combine zones, and compare and trace items of interest across different semantic zones and data slices. Finally, exploration overviews and searching techniques based on keywords, content similarity, and context helped analysts to develop awareness over the key aspects of the exploration concerning the analysis process and findings. On one hand, they can proactively search analysis processes and findings for reviewing purposes. On the other hand, they can use the system to discover implicit connections between findings and the current line of inquiry, and recommend these related findings during an interactive data exploration. We implemented the models and tools described in this dissertation in Aruvi and HARVEST. Using Aruvi and HARVEST, we studied the implications of these models on a user’s sensemaking process. We adopted the short-term and long-term case studies approach to study support offered by these tools for the sensemaking process. The observations of the case studies were used to evaluate the models

A series of case studies to enhance the social utility of RSS

RSS (really simple syndication, rich site summary or RDF site summary) is a dialect of XML that provides a method of syndicating on-line content, where postings consist of frequently updated news items, blog entries and multimedia. RSS feeds, produced by organisations or individuals, are often aggregated, and delivered to users for consumption via readers. The semi-structured format of RSS also allows the delivery/exchange of machine-readable content between different platforms and systems. Articles on web pages frequently include icons that represent social media services which facilitate social data. Amongst these, RSS feeds deliver data which is typically presented in the journalistic style of headline, story and snapshot(s). Consequently, applications and academic research have employed RSS on this basis. Therefore, within the context of social media, the question arises: can the social function, i.e. utility, of RSS be enhanced by producing from it data which is actionable and effective? This thesis is based upon the hypothesis that the fluctuations in the keyword frequencies present in RSS can be mined to produce actionable and effective data, to enhance the technology's social utility. To this end, we present a series of laboratory-based case studies which demonstrate two novel and logically consistent RSS-mining paradigms. Our first paradigm allows users to define mining rules to mine data from feeds. The second paradigm employs a semi-automated classification of feeds and correlates this with sentiment. We visualise the outputs produced by the case studies for these paradigms, where they can benefit users in real-world scenarios, varying from statistics and trend analysis to mining financial and sporting data. The contributions of this thesis to web engineering and text mining are the demonstration of the proof of concept of our paradigms, through the integration of an array of open-source, third-party products into a coherent and innovative, alpha-version prototype software implemented in a Java JSP/servlet-based web application architecture

Improving program comprehension tools for domain specific languages

Dissertação de Mestrado em InformáticaSince the dawn of times, curiosity and necessity to improve the quality of their life, led humans to find means to understand everything surrounding them, aiming at improving it. Whereas the creating abilities of some was growing, the capacity to comprehend of others follow their steps. Disassembling physical objects to comprehend the connections between the pieces in order to understand how they work together is a common human behavior. With the computers arrival, humans felt the necessity of applying the same techniques (disassemble to comprehend) to their programs. Traditionally, these programs are written resorting to general-purpose programming languages. Hence, techniques and artifacts, used to aid on program comprehension, were built to facilitate the work of software programmers on maintaining and improving programs that were developed by others. Generally, these generic languages deal with concepts at a level that the human brain can hardly understand. So understanding programs written in this languages is an hard task, because the distance between the concepts at the program level and the concepts at the problem level is too big. Thus, as in politics, justice, medicine, etc. groups of words are regularly used facilitating the comprehension between people, also in programming, languages that address a specific domain were created. These programming languages raise the abstraction of the program domain, shortening the gap to the concepts of the problem domain. Tools and techniques for program comprehension commonly address the program domain and they took little advantage of the problem domain. In this master’s thesis, the hypothesis that it is easier to comprehend a program when the underlying problem and program domains are known and a bridge between them is established, is assumed. Then, a program comprehension technique for domain specific languages, is conceived, proposed and discussed. The main objective is to take advantage from the large knowledge about the problem domain inherent to the domain specific language, and to improve traditional program comprehension tools that only dealt, until then, with the program domain. This will create connections between both program and problem domains. The final result will show, visually, what happens internally at the program domain level, synchronized with what happens externally, at problem level.Desde o início dos tempos a curiosidade e a necessidade de melhorar a qualidade de vida impeliram o humano a arranjar meios para compreender o que o rodeia com o objectivo de melhorar. À medida que a habilidade de uns foi aumentando, a capacidade de compreensão de outros seguiu-lhe os passos. Desmontar algo físico de modo a compreender as ligações entre as peças e assim perceber como funcionam num todo, é um acto bastante normal dos humanos. Com o advento dos computadores e os programas para ele codificados, o homem sentiu a necessidade de aplicar as mesmas técnicas (desmontar para compreender) ao código desses programas. Tradicionalmente, a codificação de tais programas é feita usando linguagens genéricas de programação. Desde logo técnicas e artefactos que ajudam na compreensão desses programas (nessas linguagens) foram produzidas para auxiliar o trabalho de engenheiros de software que necessitam de manter ou alterar programas previamente construídos por outros. De um modo geral estas linguagens mais genéricas lidam com conceitos a um nível bastante abaixo daquele que o cérebro humano, facilmente, consegue captar. Previsivelmente, compreender programas neste tipo de linguagens é uma tarefa complexa pois a distância entre os conceitos ao nível do programa e os conceitos ao nível do problema (que o programa aborda) é bastante grande. Deste modo, tal como no dia-a-dia foram surgindo nichos como a política, a justiça, a informática, etc. onde grupos de palavras são usadas com maior regularidade para facilitar a compreensão entre as pessoas, também na programação foram surgindo linguagens que focam em domínios específicos, aumentando a abstracção em relação ao nível do programa, aproximando este do nível dos conceitos subjacentes ao problema. Ferramentas e técnicas de compreensão de programas abordam, geralmente, o domínio do programa, tirando pouco partido do domínio do problema. Na presente tese assume-se a hipótese de que será mais fácil compreender um programa quando os domínios do problema e do programa são conhecidos, e entre eles é estabelecida uma ponte de ligação; e parte-se em busca de uma técnica de compreensão de programas para linguagens de domínio específico, baseada em técnicas já conhecidas para linguagens de carácter geral. O objectivo prende-se com aproveitar o conhecimento sobre o domínio do problema e melhorar as ferramentas de compreensão de programas existentes para as linguagens genéricas, de forma a estabelecer ligações entre domínio do programa e domínio do problema. O resultado será mostrar, visualmente, o que acontece internamente ao nível do programa, sincronizadamente com o que acontece externamente ao nível do problema

The People Inside

Our collection begins with an example of computer vision that cuts through time and bureaucratic opacity to help us meet real people from the past. Buried in thousands of files in the National Archives of Australia is evidence of the exclusionary “White Australia” policies of the nineteenth and twentieth centuries, which were intended to limit and discourage immigration by non-Europeans. Tim Sherratt and Kate Bagnall decided to see what would happen if they used a form of face-detection software made ubiquitous by modern surveillance systems and applied it to a security system of a century ago. What we get is a new way to see the government documents, not as a source of statistics but, Sherratt and Bagnall argue, as powerful evidence of the people affected by racism