A generic data model and query language for spatiotemporal OLAP cube analysis

Gómez, Leticia I.; Gómez, Silvia Alicia; Vaisman, Alejandro

doi:10.1145/2247596.2247632

Cited by 37 publications

(17 citation statements)

References 16 publications

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“…The MultiDim conceptual model, introduced by Malinowski and Zimányi [27], copes with spatial features and is extended in [36], to include complex geometric features (continuous fields), with a set of operations and an MD calculus supporting spatial data types. Gómez et al [15] propose an algebra and a general framework for OLAP cube analysis on discrete and continuous spatial data. Even though spatial data warehousing is thus widely studied, those studies are limited to traditional non-semantic spatial data warehouses and SO-LAP techniques.…”

Section: Related Workmentioning

confidence: 99%

“…In the cases where there is a spatial function f S (x) in the SOLAP operator, it is given in the BIND clause, which is technically a part of the WHERE clause and therefore added to the body of the WHERE clause in a graph pattern GP as GP = GP ∪ (BIND f S (x)). SPARQL 1.1 defines aggregate expressions 15 , such as SUM, MIN, MAX, AVG, etc.…”

Section: Generation Algorithmsmentioning

confidence: 99%

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A foundation for spatial data warehouses on the Semantic Web

Gür

Pedersen

Zimányi

et al. 2018

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Abstract. Large volumes of geospatial data are being published on the Semantic Web (SW), yielding a need for advanced analysis of such data. However, existing SW technologies only support advanced analytical concepts such as multidimensional (MD) data warehouses and Online Analytical Processing (OLAP) over non-spatial SW data. To remedy this need, this paper presents the QB4SOLAP vocabulary, which supports spatially enhanced MD data cubes over RDF data. The paper also defines a number of Spatial OLAP (SOLAP) operators over QB4SOLAP cubes and provides algorithms for generating spatially extended SPARQL queries from the SOLAP operators. The proposals are validated by applying them to a realistic use case.

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Section: Related Workmentioning

confidence: 99%

Section: Generation Algorithmsmentioning

confidence: 99%

A foundation for spatial data warehouses on the Semantic Web

Gür

Pedersen

Zimányi

et al. 2018

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“…The latter is based on empirical scientometric evidence in favor of the semantic role authors play in the process of information retrieval [10,11]. A common point with the proposed model, besides both relying on third order tensors, is that they are inspired by OLAP (Online Analytical Processing) cubes [48]. Regarding the tensor dimensions, it should be noted that, although the three dimensions are easy to visualize and handle, they are by no means a golden rule.…”

Section: Representationmentioning

confidence: 99%

Tensor-Based Semantically-Aware Topic Clustering of Biomedical Documents

et al. 2017

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Abstract:Biomedicine is a pillar of the collective, scientific effort of human self-discovery, as well as a major source of humanistic data codified primarily in biomedical documents. Despite their rigid structure, maintaining and updating a considerably-sized collection of such documents is a task of overwhelming complexity mandating efficient information retrieval for the purpose of the integration of clustering schemes. The latter should work natively with inherently multidimensional data and higher order interdependencies. Additionally, past experience indicates that clustering should be semantically enhanced. Tensor algebra is the key to extending the current term-document model to more dimensions. In this article, an alternative keyword-term-document strategy, based on scientometric observations that keywords typically possess more expressive power than ordinary text terms, whose algorithmic cornerstones are third order tensors and MeSH ontological functions, is proposed. This strategy has been compared against a baseline using two different biomedical datasets, the TREC (Text REtrieval Conference) genomics benchmark and a large custom set of cognitive science articles from PubMed.

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“…These models rely on a multi-dimensional representation of information, where the data can be perceived as a cube, where each "cell" of information contains a set of measures of interest, related with three information sources. This model is the one used by the paradigm known as OnLine Analytical Processing (OLAP), and graphical 3D interfaces, based on this method, can be created, focused on geographic and spatiotemporal data management systems [22]. Also this type of data modelling (OLAP data cube) has been successfully used to store and query real event data from sensors in smart buildings [23], where parameters such as temperature, humidity, luminescence and related events can be stored in a cubic cell that registers date, device and value related with the considered parameter.…”

Section: Previous Workmentioning

confidence: 99%

A Kinect-based 3D hand-gesture interface for 3D databases

Herrera-Acuña

Argyriou

Velastín

2014

J Multimodal User Interfaces

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Abstract. The use of natural interfaces improves significantly aspects related to human-computer interaction and consequently the productivity and the overall performance. In this paper we present a novel framework to interact with data elements presented in a 3D space. The system provides two mechanisms to interact using 2D and 3D gestures based on data provided by Kinect and on hand detection and gesture interpretation algorithms. The proposed architecture is analysed indicating that 3D interaction with information is possible, and provides advantages over a 2D interaction over the same problem. Finally, two sets of experiments were performed to evaluate 2D and 3D interaction styles based on natural interfaces focusing on traditional interaction with 3D databases.

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A generic data model and query language for spatiotemporal OLAP cube analysis

Cited by 37 publications

References 16 publications

A foundation for spatial data warehouses on the Semantic Web

A foundation for spatial data warehouses on the Semantic Web

Tensor-Based Semantically-Aware Topic Clustering of Biomedical Documents

A Kinect-based 3D hand-gesture interface for 3D databases

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