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Over the last decade Cultural Heritage (CH) organizations have been exploring new ways to make their content available and browsable using the Semantic Web and Linked Open Data (LOD). The objective of the present study was to introduce a framework to ...

This paper presents an analysis of different interaction techniques used in interactive data visualisations to support end-users in visual analytics tasks. Our selection of interaction techniques is based on prior work and consists of the ...

• We present an analysis of seven interaction techniques as used for data analytics.
• Interaction technique significantly impacts correctness and participant confidence.
• Enabling users to conceal information increases performance and ...

This application paper introduces a transformative solution to address the labour-intensive manual report generation, data searching & report revision process in government entities. Traditional methods of data extraction, analysis, and graph creation for ...

Data storytelling (DS) is rapidly gaining attention as an approach that integrates data, visuals, and narratives to create data stories that can help a particular audience to comprehend the key messages underscored by the data with enhanced efficiency ...

Nous présentons une étude de conception d’un outil d’analyse de données de performances d’escalade de difficulté créé en collaboration avec la Fédération Française Montagne Escalade (FFME). Son but est de faciliter l’exploration d’un jeu de données pour ...

Tenders are powerful means of investment of public funds and represent a strategic development resource. Thus, improving the efficiency of procuring entities and developing evaluation models turn out to be essential to facilitate e-procurement ...

• A Decision Support System integrating structured/unstructured data about tenders.
• Semantic search engine for tenders documentation to allow information retrieval.
• Search engine based on OIE (Open Information Extraction) techniques.

$\chi$iplot is an HTML5-based system for interactive exploration of data and machine learning models. A key aspect is interaction, not only for the interactive plots but also between plots. Even though $\chi$iplot is not restricted to any single application ...$$$$

In the context of process monitoring and predictive maintenance, an adapted visualisation of sensor data is essential in order to help the domain experts to make the right maintenance decision. The large volume and diversity of data leads us to ...

With the development and application of technologies such as 5G and big data artificial intelligence, humanity has entered the era of digital intelligence convergence (BD + AI), which has enabled the future of education and learning to move into a ...

Digital libraries often contain many heterogeneous documents and cover a variety of topics. Computer generated virtual maps of such collections can help to get an overview and explore the data. The position of each document from the corpus on this ...

Malicious software, known as malware, is a perpetual game of cat and mouse between malicious software developers and security professionals. Recent years have seen many high profile cyber attacks, including the WannaCry and NotPetya ransomware ...

Network neuroscience investigates brain functioning through the prism of connectivity, and graph theory has been the main framework to understand brain networks. Recently, an alternative framework has gained attention: topological data analysis. ...

Projection pursuit is used to find interesting low-dimensional projections of high-dimensional data by optimizing an index over all possible projections. Most indexes have been developed to detect departure from known distributions, such as ...

Digital publication platforms and social media have opened possibilities for cultural heritage institutions to share their content online, in particular favouring audiovisual content. To better valorise large-scale digital collections and increase ...

This paper investigates the utility of unsupervised machine learning and data visualisation for tracking changes in user activity over time. This is done through analysing unlabelled data generated from passive and ambient smart home sensors, such ...

Scientific researchers are facing a rapidly growing volume of literatures nowadays. While these publications offer rich and valuable information, the scale of the datasets makes it difficult for the researchers to manage and search for desired ...

The paper aims to visualise the world happiness scores that are reported by the United Nations. Relationship between factors that affect happiness of a country is being identified by performing a clustering analysis on the happiness score. This ...

T-distributed stochastic neighbour embedding (t-SNE) is a widely used data visualisation technique. It differs from its predecessor SNE by the low-dimensional similarity kernel: the Gaussian kernel was replaced by the heavy-tailed Cauchy kernel, ...$$$$$\mathrm{}$$\mathrm{}$

Energy efficiency play an important role in addressing the issue of inadequacy of electrical consumption. In Malaysia, residential users have been identified as one of major contributor towards high electricity consumption. Due to this issue, government ...

This study investigates the feasibility of a tool that allows digital forensics (DF) investigators to efficiently triage device datasets during the collection phase of an investigation. This tool utilises data visualisation techniques to display ...