Software knowledge management using wikis : a plugin for weakly typed pages

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Weaki - A weakly-typed wiki for incremental software knowledge acquisition

O desenvolvimento de software pode ser visto como a última etapa de um processo de aquisição de conhecimento, durante o qual o conhecimento adquirido se acumula e evolui para um código fonte que cumpre um conjunto de condições previamente definidas pelos stakeholders. O conhecimento adquirido desta forma é armazenado sob a forma de artefactos de software, artefactos estes que têm dois aspectos diferentes: a estrutura e o conteúdo, que são muito difíceis de alterar em separado um do outro.Para gerir o conhecimento adquirido e a complexidade do processo de aquisição existem métodos, práticas e ferramentas que são de maneira geral usados ​​para facilitar a aquisição de conhecimentos e o seu processamento. Entre essas ferramentas, um dos mais populares são as wikis.Wikis proporcionam uma boa plataforma para gerir o conhecimento para além de suportarem trabalho colaborativo. No entanto para além do que as wikis já fornecem, seria útil se estas tivessem suporte para outros aspectos, tais como o reconhecimento de estruturas de conhecimento e suporte para a sua evolução à medida que conhecimento é adquirido e as mudanças que sofre ao longo do tempo.O principal objetivo deste trabalho é desenvolver uma extensão para um wiki já existente, adicionando funcionalidades para apoiar o reconhecimento da estruturas da informação, assim como na inferência dessas estruturas pelo conteúdo, com o objetivo de auxiliar no desenvolvimento de artefactos de documentação de software, ao permitir um aumento gradual na formalização da sua estrutura e do seu conteúdo. A utilidade da extensão da wiki foi validada através de uma experiência empírica envolvendo estudantes.Software development can be seen as the final stage in a process of knowledge acquisition, during which the acquired knowledge accumulates and evolves towards a source code that fulfills a set of conditions previously defined by the stakeholders. The knowledge acquired this way is stored in the form of software artifacts which have two different aspects: structure and content, that are very difficult to change separately from each other. To manage the acquired knowledge and the complexity of the acquisition process there are methods, practices and tools that are commonly used to facilitate the acquisition and processing of knowledge. Among these tools, one of the most popular are the wikis. Wikis provide a good platform to manage knowledge while also supporting collaborative work. However beyond what wikis already provide, it would be useful if they had other aspects such as the recognition of knowledge structures and the support for its evolutionary behaviour. The main goal of this work is to develop an extension to an existing wiki, by adding the functionalities to support structure recognition and type inference, with the goal of aiding in the development of software documentation artifacts, allowing for a gradual increase in the formalization of its structure and content. The usefulness of the wiki extension was validated through and empirical experience with students

Documentação colaborativa de software através de anotações contextuais.

A documentação de software, apesar de nos dias de hoje ainda ser considerada secundária em relação a outros artefactos resultantes do processo de desenvolvimento, desempenha um papel fundamental no uso eficaz e na compreensão do software. O processo de desenvolvimento de software tem sofrido evolução ao longo dos tempos, sendo hoje em dia geralmente uma atividade cada vez mais social, nomeadamente quando se olha para frameworks populares na web. Contudo, os mesmos princípios são aplicáveis a equipas mais pequenas e ágeis. Neste contexto, uma documentação minimalista, onde apenas se cria o conteúdo mínimo necessário e que vai evoluindo de acordo com as necessidades dos utilizadores, tem vindo a ser prática cada vez mais utilizada. A interação e comunicação entre leitores e autores, com o intuito de debater que alterações se devem fazer à documentação, é fulcral para essa evolução.O principal objetivo desta dissertação é mostrar que essa comunicação pode ser melhorada, nomeadamente com o uso de anotações contextuais na documentação. Para o alcançar, foi desenvolvida uma wiki, que irá servir de plataforma para a documentação colaborativa de software.A essa wiki foi adicionada a possibilidade de adicionar comentários a uma página e anotações a secções específicas, criando um ambiente propício à discussão entre leitores e autores.Finalmente, de modo a comprovar que a ferramenta desenvolvida cumpre o seu objetivo de melhorar a comunicação entre os vários intervenientes, esta será testada numa pequena equipa de desenvolvimento de software.Software documentation, despite still being considered secondary in relation to other artifacts that result from the development process, is fundamental in order to use and understand software in an efficient way. The software development process has been evolving over time, and is now an increasingly social activity, namely compared to other popular frameworks on the web. However, the same principles can be applied to small agile development teams. In this context, minimalist documentation, where only the bare minimum content is created, which will evolve according to the specific needs of the users, has been rising in popularity. The interaction and communication between both readers and authors, with the goal of debating what changes must be made to the documentation, is key to this evolution.The main goal of this work is to demonstrate that this communication can be the subject of improvement, namely with the use of contextual annotations in the documentation. In order to achieve this goal, a wiki has been developed, which will serve as platform for collaborative software documentation. Then, the possibility to add comments to a certain page and annotations to specific portions of that page was added to the wiki, thus creating a friendly environment to discussion between readers and authors.Finally, in order to verify that the developed tool fulfills its goal of improving communication and interaction between the various interveners, it will be tested in a small software development team

Wiki or Word? Evaluating Tools for Collaborative Writing and Editing

Businesses and other organizations are relying increasingly on virtual teams to perform a range of business activities. A key challenge in utilizing virtual teams is to support collaboration among team members who are separated by distance and/or time. In this paper we use a research model based on a combination of the Technology Acceptance Model (TAM) and the Task Technology Fit (TTF) model to examine two approaches to supporting students in collaboratively creating and editing a report for an introductory course in information systems. In our study, one group of students used MS Word with Track Changes turned on combined with emailing the document among students. A second group was provided access to a wiki where they created the report. Results show that students found the Word and email combination more useful and easier to use than the wiki environment in completing the project. Further, there was no perceived difference in the effort of collaboration between the two methods. This study raises questions about the widely held belief that web-based collaboration platforms are superior to emailing documents among collaborators

Personal Knowledge Models with Semantic Technologies

Conceptual Data Structures (CDS) is a unified meta-model for representing knowledge cues in varying degrees of granularity, structuredness, and formality. CDS consists of: (1) A simple, expressive data-model; (2) A relation ontology which unifies the relations found in cognitive models of personal knowledge management tools, e. g., documents, mind-maps, hypertext, or semantic wikis. (3) An interchange format for structured text. Implemented prototypes have been evaluated

Constructive Reasoning for Semantic Wikis

One of the main design goals of social software, such as wikis, is to support and facilitate interaction and collaboration. This dissertation explores challenges that arise from extending social software with advanced facilities such as reasoning and semantic annotations and presents tools in form of a conceptual model, structured tags, a rule language, and a set of novel forward chaining and reason maintenance methods for processing such rules that help to overcome the challenges. Wikis and semantic wikis were usually developed in an ad-hoc manner, without much thought about the underlying concepts. A conceptual model suitable for a semantic wiki that takes advanced features such as annotations and reasoning into account is proposed. Moreover, so called structured tags are proposed as a semi-formal knowledge representation step between informal and formal annotations. The focus of rule languages for the Semantic Web has been predominantly on expert users and on the interplay of rule languages and ontologies. KWRL, the KiWi Rule Language, is proposed as a rule language for a semantic wiki that is easily understandable for users as it is aware of the conceptual model of a wiki and as it is inconsistency-tolerant, and that can be efficiently evaluated as it builds upon Datalog concepts. The requirement for fast response times of interactive software translates in our work to bottom-up evaluation (materialization) of rules (views) ahead of time – that is when rules or data change, not when they are queried. Materialized views have to be updated when data or rules change. While incremental view maintenance was intensively studied in the past and literature on the subject is abundant, the existing methods have surprisingly many disadvantages – they do not provide all information desirable for explanation of derived information, they require evaluation of possibly substantially larger Datalog programs with negation, they recompute the whole extension of a predicate even if only a small part of it is affected by a change, they require adaptation for handling general rule changes. A particular contribution of this dissertation consists in a set of forward chaining and reason maintenance methods with a simple declarative description that are efficient and derive and maintain information necessary for reason maintenance and explanation. The reasoning methods and most of the reason maintenance methods are described in terms of a set of extended immediate consequence operators the properties of which are proven in the classical logical programming framework. In contrast to existing methods, the reason maintenance methods in this dissertation work by evaluating the original Datalog program – they do not introduce negation if it is not present in the input program – and only the affected part of a predicate’s extension is recomputed. Moreover, our methods directly handle changes in both data and rules; a rule change does not need to be handled as a special case. A framework of support graphs, a data structure inspired by justification graphs of classical reason maintenance, is proposed. Support graphs enable a unified description and a formal comparison of the various reasoning and reason maintenance methods and define a notion of a derivation such that the number of derivations of an atom is always finite even in the recursive Datalog case. A practical approach to implementing reasoning, reason maintenance, and explanation in the KiWi semantic platform is also investigated. It is shown how an implementation may benefit from using a graph database instead of or along with a relational database

Intelligence artificielle: Les défis actuels et l'action d'Inria - Livre blanc Inria

Livre blanc Inria N°01International audienceInria white papers look at major current challenges in informatics and mathematics and show actions conducted by our project-teams to address these challenges. This document is the first produced by the Strategic Technology Monitoring & Prospective Studies Unit. Thanks to a reactive observation system, this unit plays a lead role in supporting Inria to develop its strategic and scientific orientations. It also enables the institute to anticipate the impact of digital sciences on all social and economic domains. It has been coordinated by Bertrand Braunschweig with contributions from 45 researchers from Inria and from our partners. Special thanks to Peter Sturm for his precise and complete review.Les livres blancs d’Inria examinent les grands défis actuels du numérique et présentent les actions menées par noséquipes-projets pour résoudre ces défis. Ce document est le premier produit par la cellule veille et prospective d’Inria. Cette unité, par l’attention qu’elle porte aux évolutions scientifiques et technologiques, doit jouer un rôle majeur dans la détermination des orientations stratégiques et scientifiques d’Inria. Elle doit également permettre à l’Institut d’anticiper l’impact des sciences du numérique dans tous les domaines sociaux et économiques. Ce livre blanc a été coordonné par Bertrand Braunschweig avec des contributions de 45 chercheurs d’Inria et de ses partenaires. Un grand merci à Peter Sturm pour sa relecture précise et complète. Merci également au service STIP du centre de Saclay – Île-de-France pour la correction finale de la version française

Large-Scale Pattern-Based Information Extraction from the World Wide Web

Extracting information from text is the task of obtaining structured, machine-processable facts from information that is mentioned in an unstructured manner. It thus allows systems to automatically aggregate information for further analysis, efficient retrieval, automatic validation, or appropriate visualization. This work explores the potential of using textual patterns for Information Extraction from the World Wide Web