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- Browsing multidimensional visual entitiesPublication . Aniceto, Miguel; Moura Pires, João; Datia, Nuno; Afonso, Ana PaulaThe field of Information Visualization seeks to identify the general principles of visualization, and makes use of these principles to propose new forms of visualization for specific types of data. Included in these different data types, it was identified a data type which was not thoroughly explored. The notion of entities where each entity is composed by different attributes, and one of these attributes is composed by one picture which invokes a strong feeling of familiarity to the user. The information that we are attempting to visualize is the most basic type of data structure, a table, where the number of entities to visualize should be higher than we can humanely count, yet smaller than a few thousands. In the field of visualization we identified a niche where the main focus is the image, and despite that it has a vast number of applicable scenarios, it hadn't been properly explored. One of the major attempts at doing so, was by Microsoft Live Labs and it demonstrated limitations that will be addressed by our approach. In order to evaluate the proposed forms of visualization they will be applied and evaluated with the Deloitte Portugal organizational case-study.
- Visual analytics for spatiotemporal eventsPublication . Silva, Ricardo Almeida; Moura Pires, João; Datia, Nuno; Santos, Maribel Yasmina; Martins, Bruno; Birra, FernandoCrimes, forest fires, accidents, infectious diseases, or human interactions with mobile devices (e.g., tweets) are being logged as spatiotemporal events. For each event, its geographic location, time and related attributes are known with high levels of detail (LoDs). The LoD plays a crucial role when analyzing data, as it can highlight useful patterns or insights and enhance the user’ perception of phenomena. For this reason, modeling phenomena at different LoDs is needed to increase the analytical value of the data, as there is no exclusive LOD at which the data can be analyzed. Current practices work mainly on a single LoD of the phenomena, driven by the analysts’ perception, ignoring that identifying the suitable LoDs is a key issue for pointing relevant patterns. This article presents a Visual Analytics approach called VAST, that allows users to simultaneously inspect a phenomenon at different LoDs, helping them to see in what LoDs do interesting patterns emerge, or in what LoDs the perception of the phenomenon is different. In this way, the analysis of vast amounts of spatiotemporal events is assisted, guiding the user in this process. The use of several synthetic and real datasets supported the evaluation and validation of VAST, suggesting LoDs with different interesting spatiotemporal patterns and pointing the type of expected patterns.
- AA-Maps: attenuation and accumulation maps for spatio-temporal event visualisationPublication . Albino, Catarina; Moura Pires, João; Datia, Nuno; Silva, Ricardo Almeida; Santos, Maribel YasminaSome phenomena, such as crimes in a city, fires occurred in a country and road accidents can be interpreted as sets of spatio-temporal events. A spatio-temporal event is described by a geographic location, a time instant and other characterising attributes. The cartographic visualisation of spatio-temporal events remains unresolved, due to the challenges related with portraying multiple dimensions simultaneously: the spatial, the temporal and the semantic (zero or more dimensions) phenomenon's components. In this context, this article presents the Attenuation and Accumulation Maps (AA-Maps). The main idea of this visualisation analytic approach consists in showing in a map, the resulting effect of combining attenuation and accumulation, from a temporal reference of observation, given a spatio-temporal Level of Detail (LoD). Imagine the footprints of people crossing a garden in various directions. They leave different traces that summarize the cumulative effect of the footprints on the grass, which is attenuated as time goes by. AA-Maps support different combinations of attenuation and accumulation functions. In addition, this method also enables analysis with different Levels of Detail (LoD), both spatial and temporal. This allows distinct analytic perspectives of the phenomenon while promoting the search for the most suitable parametrization for its characteristics.
- Integrated electromyography visualization with multi temporal resolutionPublication . Cardoso, Pedro; Datia, Nuno; Pós-de-Mina Pato, MatildeFor the analysis and comparison of electromyography (EMG) signals from different patients, standardization techniques are used to calculate the integrated EMG signal (iEMG), useful to evaluate the level of activity of different muscles. The iEMG corresponds to the area under the rectified curve (AUC). Currently, monitoring and follow-up of these patients is done in regular health exams where the evolution of patients is assessed. The monitoring includes performing multiple clinical trials. The goal of this paper is to help medical staff assessing the evolution of amyotrophic lateral sclerosis (ALS) disease by analyzing the collected data. The signal, described by the electromyogram, can be measured applying conductive elements or electrodes to the skin surface. The electrical activity of skeletal muscles is continuously measured for at least 24 hours. In this work we used an appropriate data model to store data generated by EMGs, optimized for analytical processing. We implemented aWeb API in order to provide access to the model data in an agnostic way, both to database management systems and data consumers. We implemented a web application to visualize data through the use of several interactive charts. Usability testing helped to validate the solution, confirming the ease of use of the web application and the fulfillment of all the proposed goals. The telemonitoring ALS patients doesn't change mortality but reduces the need for hospitalization and costs for patient.
- Time and space for segmenting personal photo setsPublication . Datia, Nuno; Moura Pires, João; Correia, NunoA personal collection of photos shows large variability in the depicted items, making difficult a fully automated solution to cope with sensory and semantic gaps. Emotions and non-visual contextual information can be very important to address those problems. Manual annotations are key, but their time-consuming nature alienate users from doing them. One solution is to lower the annotation effort, building solutions on top of algorithms that prepare a context separation, making possible the reuse of annotations. In this paper we present a segmentation algorithm that uses spatio-temporal information to segment personal photo collections. The algorithm is assessed in a user study, using the participants own photos. The results show users make none or few changes to the proposed segmentations, indicating an acceptance of the algorithm outcome.
- Visualising hidden spatiotemporal patterns at multiple levels of detailPublication . Silva, Ricardo Almeida; Moura Pires, João; Datia, Nuno; Santos, Maribel Yasmina; Martins, Bruno; Birra, FernandoCrimes, forest fires, accidents, infectious diseases, human interactions with mobile devices (e.g., tweets) are being logged as spatiotemporal events. For each event, its geographic location, time and related attributes are known with high levels of detail (LoDs). The LoD plays a crucial role when analyzing data, enhancing the user's perception of phenomena. From one LoD to another, some patterns can be easily perceived or different patterns may be detected. Modeling phenomena at different LoDs is needed, as there is no exclusive LoD at which data can be analyzed. Current practices work mainly on a single LoD, driven by the analysts perception, ignoring the fact that the identification of the suitable LoDs is a key issue for pointing relevant patterns. This paper presents a Visual Analytics approach called VAST, that allows users to simultaneously inspect a phenomenon at different LoDs, helping them to see in what LoDs patterns emerge or in what LoDs the perception of the phenomenon is different. In this way, the analysis of vast amounts of spatiotemporal events is assisted, guiding the user in this process. The use of several synthetic and real datasets allowed the evaluation of VAST, which was able to suggest LoDs with different interesting spatiotemporal patterns and the type of expected patterns.