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Publicações

Publicações por HumanISE

2022

Patterns for Documenting Open Source Frameworks

Autores
Santos, J; Correia, FF;

Publicação
CoRR

Abstract

2022

More Software Analytics Patterns: Broad-Spectrum Diagnostic and Embedded Improvements

Autores
Oliveira, D; Fidalgo, J; Choma, J; Guerra, EM; Correia, FF;

Publicação
CoRR

Abstract

2022

An Evaluation of Graph Databases and Object-Graph Mappers in CIDOC CRM-Compliant Digital Archives

Autores
Costa, L; Freitas, N; da Silva, JR;

Publicação
ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE

Abstract
The Portuguese General Directorate for Book, Archives and Libraries (DGLAB) has selected CIDOC CRM as the basis for its next-generation digital archive management software. Given the ontological foundations of the Conceptual Reference Model (CRM), a graph database or a triplestore was seen as the best candidate to represent a CRM-based data model for the new software. We thus decided to compare several of these databases, based on their maturity, features, performance in standard tasks and, most importantly, the Object-Graph Mappers (OGM) available to interact with each database in an object-oriented way. Our conclusions are drawn not only from a systematic review of related works but from an experimental scenario. For our experiment, we designed a simple CRM-compliant graph designed to test the ability of each OGM/database combination to tackle the so-called diamond-problem in Object-Oriented Programming (OOP) to ensure that property instances follow domain and range constraints. Our results show that (1) ontological consistency enforcement in graph databases and triplestores is much harder to achieve than in a relational database, making them more suited to an analytical rather than a transactional role; (2) OGMs are still rather immature solutions; and (3) neomodel, an OGM for the Neo4j graph database, is the most mature solution in the study as it satisfies all requirements, although it is also the least performing.

2022

Foreword to the special section on Recent Advances in Graphics and Interaction

Autores
Rodrigues, N; Mendes, D; Santos, LP; Bouatouch, K;

Publicação
COMPUTERS & GRAPHICS-UK

Abstract

2022

Designing Animated Transitions for Dynamic Streaming Big Data

Autores
Moreira, J; Castanheira, F; Mendes, D; Goncalves, D;

Publicação
PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (IVAPP), VOL 3

Abstract
Visualizations for Streaming Big Data need to handle high volumes of information in real-time, making it challenging to convey significant data changes without confusing users. A simple first approach would be switching from the current visual idiom to another, highlighting a significant change. Unfortunately, there are no guidelines to design effective transitions between two visual idioms in Streaming Big Data. Therefore, we created a tree of animation concepts to serve as a starting point for designing such animated transitions. The concepts represent several ways in which a visual idiom can be transformed into another. We chose three visual idioms to test our idea and arranged several concepts to apply at each possible pairing (six possibilities). For each pairing, we tested the accuracy of people's perceptions. Finally, we conducted a user study with 100 participants, where each participant answered various questions about transitions between two visual idioms shown in several videos. We concluded that to conceive appropriate animated transitions for Streaming Big Data (which also applies just for Data Streaming) that allow users to understand the changes in incoming data, varying how the proposed concepts are applied is not enough, highlighting the need for future research to address this challenge.

2022

Foreword RAGI

Autores
Silva, PA; Magalhaes, LG; Mendes, D; Giachetti, A;

Publicação
COMPUTERS & GRAPHICS-UK

Abstract

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