Who’s Who – A Linked Data Visualisation Tool for Mobile Environments

Cano, Amparo Elizabeth; Dadzie, Aba-Sah; Hartmann, Melanie

doi:10.1007/978-3-642-21064-8_33

Cited by 7 publications

(2 citation statements)

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“…15 Regarding device-specific systems, DBpedia Mobile [14] is a location-aware mobile application for exploring and visualizing DBpedia resources. Who's Who [24] is an application for exploring and visualizing information focusing on several issues that appear in the mobile environment. For example, the application considers the usability and data processing challenges related to the small display size and limited resources of the mobile devices.…”

Section: Domain Vocabulary and Device-specificmentioning

confidence: 99%

A hierarchical aggregation framework for efficient multilevel visual exploration and analysis

Bikakis

Papastefanatos

Skourla

et al. 2016

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Abstract. Data exploration and visualization systems are of great importance in the Big Data era, in which the volume and heterogeneity of available information make it difficult for humans to manually explore and analyse data. Most traditional systems operate in an offline way, limited to accessing preprocessed (static) sets of data. They also restrict themselves to dealing with small dataset sizes, which can be easily handled with conventional techniques. However, the Big Data era has realized the availability of a great amount and variety of big datasets that are dynamic in nature; most of them offer API or query endpoints for online access, or the data is received in a stream fashion. Therefore, modern systems must address the challenge of on-the-fly scalable visualizations over large dynamic sets of data, offering efficient exploration techniques, as well as mechanisms for information abstraction and summarization. Further, they must take into account different user-defined exploration scenarios and user preferences. In this work, we present a generic model for personalized multilevel exploration and analysis over large dynamic sets of numeric and temporal data. Our model is built on top of a lightweight tree-based structure which can be efficiently constructed on-the-fly for a given set of data. This tree structure aggregates input objects into a hierarchical multiscale model. We define two versions of this structure, that adopt different data organization approaches, well-suited to exploration and analysis context. In the proposed structure, statistical computations can be efficiently performed on-the-fly. Considering different exploration scenarios over large datasets, the proposed model enables efficient multilevel exploration, offering incremental construction and prefetching via user interaction, and dynamic adaptation of the hierarchies based on user preferences. A thorough theoretical analysis is presented, illustrating the efficiency of the proposed methods. The presented model is realized in a web-based prototype tool, called SynopsViz that offers multilevel visual exploration and analysis over Linked Data datasets. Finally, we provide a performance evaluation and a empirical user study employing real datasets.

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Section: Domain Vocabulary and Device-specificmentioning

confidence: 99%

A hierarchical aggregation framework for efficient multilevel visual exploration and analysis

Bikakis

Papastefanatos

Skourla

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Regarding device-specific systems, DBpedia Mobile [18] is a location-aware mobile application for exploring and visualizing DBpedia resources. Who's Who [32] is an application for exploring and visualizing information focusing on several issues that appear in the mobile environment. For example, the application considers the usability and data processing challenges related to the small display size and limited resources of the mobile devices.…”

Section: Domain Vocabulary and Device-specific Visualization Systemsmentioning

confidence: 99%

Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art

Bikakis,

Sellis

2016

Preprint

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Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the modern exploration and visualization systems. Considering these challenges, we present how state-of-the-art approaches from the Database and Information Visualization communities attempt to handle them. Finally, we survey the systems developed by Semantic Web community in the context of the Web of Linked Data, and discuss to which extent these satisfy the contemporary requirements.

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