Methodological development

Book description: Human-Computer Interaction draws on the fields of computer science, psychology, cognitive science, and organisational and social sciences in order to understand how people use and experience interactive technology. Until now, researchers have been forced to return to the individual subjects to learn about research methods and how to adapt them to the particular challenges of HCI. This is the first book to provide a single resource through which a range of commonly used research methods in HCI are introduced. Chapters are authored by internationally leading HCI researchers who use examples from their own work to illustrate how the methods apply in an HCI context. Each chapter also contains key references to help researchers find out more about each method as it has been used in HCI. Topics covered include experimental design, use of eyetracking, qualitative research methods, cognitive modelling, how to develop new methodologies and writing up your research

Applying Effective Data Modelling Approaches for the Creation of a Participatory Archive Platform

The development of a participatory archive platform such as the one being carried out for the PIA research project requires a flexible infrastructure allowing genuine data curation and a robust underlying data model. A strong assumption to achieve this is to primarily leverage Linked Open Usable Data (LOUD) standards, such as IIIF, Linked Art or the Web Annotation Data Model, which help in the dissemination and reuse of cultural heritage resources as well as contributing that digital humanities initiatives become more sustainable

Type relationship graphs for exploring APIs

In the present day, the use of APIs, varying in complexity, size and design are pervasive, in the development of software. They are used to communicate, to log information, to draw charts and a myriad of other purposes. With this increasing importance in API usage, developers often struggle when using an API for the first time and are faced with various API discoverability problems. We propose an approach that aims to help mitigate the discoverability problems by providing code suggestions based on data extracted from structurally analyzing APIs for type relationships. The relationships are stored in a graph, which is used to navigate between the API types. The first steps when using an API are often one of the difficulties that developers face. For this reason, our approach provides API starting points to help the developer kick-start the use of the API. The next stage in API usage usually consists in using API types to access or create other API types. Our approach suggests possible type compositions based on the types available in the current development context. Depending on the API, the amount of extracted relationships can be overwhelming if directly suggested to the developer and for this reason a filtering mechanism and ranking heuristic were created, in order to provide more meaningful suggestions. Our approach was tested by analyzing 5 different APIs and simulating suggestions from the extracted data, comparing those suggestions to API usage examples. The results provide some evidence that our approach is a possible solution to the API discoverability problems and that the structural analysis to a given API can provide considerable amount of the information required to create and deliver suggestions to developers.Actualmente, o uso de APIs, com diferentes graus de complexidade, tamanho e estrutura, é inevitável no desenvolvimento de software. As APIs são usadas para comunicação, registar informação, desenhar gráficos entre uma miríade de outras funcionalidades. Com este aumento na importância do uso de APIs, os programadores são muitas vezes confrontados com vários problemas de usabilidade quando usam uma API pela primeira vez. Propomos uma abordagem que visa ajudar na mitigação destes problemas através de sugestões de código, obtidas a partir da informação proveniente de uma análise estrutural a APIs que tem como objectivo encontrar relações entre tipos. Estas relações são armazenadas em grafos que irão ser usados para navegar entre os diversos tipos da API. Os primeiros passos de um programador quando usa uma API são, numa boa parte das vezes, uma das fontes de dificuldade. Por esta razão, a nossa abordagem disponibiliza um conjunto de pontos iniciais da API, de forma a auxiliar o programador no uso inicial da mesma. A fase seguinte no uso de uma API normalmente consiste na utilização de tipos da API, de forma a aceder ou criar outros tipos da API. A nossa abordagem sugere possíveis composições de tipos com base na informação do contexto actual de desenvolvimento. Dependendo da API, a quantidade de relações extraídas pode ser avassaladora, se sugeridas directamente ao programador. Para conseguir oferecer sugestões significativas, foi criado um sistema de filtragem e uma heurística de ordenação. A nossa abordagem foi testada analisando 5 diferentes API e simulando sugestões através da informação extraída. Estas sugestões foram comparadas com exemplos de utilização destas APIs. Os resultados evidenciam que a nossa abordagem é uma solução possível para os problemas de usabilidade de APIs, e que a análise estrutural a uma API permite obter o conjunto de informação necessária para gerar e disponibilizar sugestões a programadore

The intersection of people, technology and local space. PPGIS and Web in practice for participatory planning

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesThis study concerns about the contributions of Web 2.0 tools to Public Participation Geographic Information System (PPGIS) and of PPGIS to participatory planning. Web 2.0 tools are increasingly occupying an important role in the universe of geographic information consciousness. Both Web 2.0 and PPGIS are about decentralization, public mapping, and local knowledge, encouraging throughout productive results. The project develops a Web 2.0 PPGIS mashup application through free, easy-to-use tools. It consists of a Web mapping service, with eligible GI layers, where users explore and comment. A database stores the contributions in a format supported by GIS. Finally, we set a first version at Canela – Brazil, to test the usefulness of the method on a real planning scenario. Results shown it is a valuable approach for engaging the public in participatory planning. It promotes communications among users and with decision makers in a more interactive and straightforward way. The Web 2.0 PPGIS is easy to set and understandable by nonexperts, and can be easily applied on other contexts

OntoPharma: ontology based clinical decision support system to reduce medication prescribing errors

Background: Clinical decision support systems (CDSS) have been shown to reduce medication errors. However, they are underused because of different challenges. One approach to improve CDSS is to use ontologies instead of relational databases. The primary aim was to design and develop OntoPharma, an ontology based CDSS to reduce medication prescribing errors. Secondary aim was to implement OntoPharma in a hospital setting. Methods: A four-step process was proposed. (1) Defining the ontology domain. The ontology scope was the medication domain. An advisory board selected four use cases: maximum dosage alert, drug-drug interaction checker, renal failure adjustment, and drug allergy checker. (2) Implementing the ontology in a formal representation. The implementation was conducted by Medical Informatics specialists and Clinical Pharmacists using Protégé-OWL. (3) Developing an ontology-driven alert module. Computerised Physician Order Entry (CPOE) integration was performed through a REST API. SPARQL was used to query ontologies. (4) Implementing OntoPharma in a hospital setting. Alerts generated between July 2020/ November 2021 were analysed. Results: The three ontologies developed included 34,938 classes, 16,672 individuals and 82 properties. The domains addressed by ontologies were identification data of medicinal products, appropriateness drug data, and local concepts from CPOE. When a medication prescribing error is identified an alert is shown. OntoPharma generated 823 alerts in 1046 patients. 401 (48.7%) of them were accepted. Conclusions: OntoPharma is an ontology based CDSS implemented in clinical practice which generates alerts when a prescribing medication error is identified. To gain user acceptance OntoPharma has been designed and developed by a multidisciplinary team. Compared to CDSS based on relational databases, OntoPharma represents medication knowledge in a more intuitive, extensible and maintainable manner

HiER 2015. Proceedings des 9. Hildesheimer Evaluierungs- und Retrievalworkshop

Die Digitalisierung formt unsere Informationsumwelten. Disruptive Technologien dringen verstärkt und immer schneller in unseren Alltag ein und verändern unser Informations- und Kommunikationsverhalten. Informationsmärkte wandeln sich. Der 9. Hildesheimer Evaluierungs- und Retrievalworkshop HIER 2015 thematisiert die Gestaltung und Evaluierung von Informationssystemen vor dem Hintergrund der sich beschleunigenden Digitalisierung. Im Fokus stehen die folgenden Themen: Digital Humanities, Internetsuche und Online Marketing, Information Seeking und nutzerzentrierte Entwicklung, E-Learning

Assessing Adaptive Learning Styles in Computer Science Through a Virtual World

abstract: Programming is quickly becoming as ubiquitous and essential a skill as general mathematics. However, many elementary and high school students are still not aware of what the computer science field entails. To make matters worse, students who are introduced to computer science are frequently being fed only part of what it is about rather than its entire construction. Consequently, they feel out of their depth when they approach college. Research has discovered that by teaching computer science and programming through a problem-driven approach and focusing on a combination of syntax and computational thinking, students can be prepared when entering higher levels of computer science education. This thesis describes the design, development, and early user testing of a theory-based virtual world for computer science instruction called System Dot. System Dot was designed to visually manifest programming instructions into interactable objects, giving players a way to see coding as tangible entities rather than text on a white screen. In order for System Dot to convey the true nature of computer science, a custom predictive recursive descent parser was embedded in the program to validate any user-generated solutions to pre-defined logical platforming puzzles. Steps were taken to adapt the virtual world to player behavior by creating a system to detect their learning style playing the game. Through a dynamic Bayesian network, System Dot aims to classify a player’s learning style based on the Felder-Sylverman Learning Style Model (FSLSM). Testers played through the first half of System Dot, which was enough to test out the Bayesian network and initial learning style classification. This classification was then compared to the assessment by Felder’s Index of Learning Styles Questionnaire (ILSQ). Lastly, this thesis will also discuss ways to use the results from the user testing to implement a personalized feedback system for the virtual world in the future and what has been learned through the learning style method.Dissertation/ThesisMasters Thesis Computer Science 201