iBLOB: Complex Object Management in Databases through Intelligent Binary Large Objects

Chen, Tao; Khan, Arif O.; Schneider, Markus; Viswanathan, Ganesh

doi:10.1007/978-3-642-16092-9_10

Cited by 5 publications

(7 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Figure 9 illustrates the proposed system architecture. A more detailed description of the TSS concept and the iBLOB concept, which are beyond the scope of this article, can be found in [10]. This research effort is ongoing work.…”

Section: Methodsmentioning

confidence: 99%

Spatial Plateau Algebra for implementing fuzzy spatial objects in databases and GIS: Spatial plateau data types and operations

Schneider

2014

Applied Soft Computing

Self Cite

View full text Add to dashboard Cite

Many geographical applications have to deal with spatial objects that reveal an intrinsically vague or fuzzy nature. A spatial object is fuzzy if locations exist that cannot be assigned completely to the object or to its complement. Spatial database systems and Geographical Information Systems (GIS) are currently unable to cope with this kind of data. Based on an available abstract data model of fuzzy spatial data types for fuzzy points, fuzzy lines, and fuzzy regions that leverages fuzzy set theory and fuzzy point set topology, this article proposes a Spatial Plateau Algebra that provides spatial plateau data types as an implementation of fuzzy spatial data types. Each spatial plateau object consists of a finite number of crisp counterparts that are all adjacent or disjoint to each other, are associated with different membership values, and hence form different plateaus. The formal framework and the implementation are based on well known, exact models and implementations of crisp spatial data types. Spatial plateau operations as geometric operations on spatial plateau objects are expressed as a combination of geometric operations on the underlying crisp spatial objects. This article offers a conceptually clean foundation for implementing a database extension for fuzzy spatial objects and their operations, and demonstrates the embedding of these new data types as attribute data types in a database schema as well as the incorporation of fuzzy spatial operations into a database query language.

show abstract

Section: Methodsmentioning

confidence: 99%

Spatial Plateau Algebra for implementing fuzzy spatial objects in databases and GIS: Spatial plateau data types and operations

Schneider

2014

Applied Soft Computing

Self Cite

View full text Add to dashboard Cite

show abstract

“…SDM is developed in the context of the ALMA project, an array to operate at mm/sub-mm wave lengths [23,24,26]. SDM inherits from the Measurement Set.…”

Section: Science Data Model(sdm)mentioning

confidence: 99%

A Survey on File Format for Data Storage in Radio Astronomy

Chen

Deng

Wang

et al. 2013

2013 6th International Conference on Intelligent Networks and Intelligent Systems

View full text Add to dashboard Cite

In this paper, we review the file formats for data storage in radio astronomy. As a standard format used in astronomy, Flexible Image Transport System (FITS) is discussed firstly. Random Group FITS File (UVFITS) and FITS Interferometry Data Interchange (FITS-IDI) based on FITS are highlighted. And VOTable promoted by the development of Virtual Observatory (VO) is also briefly reviewed. We all know that the Common Astronomy Software Applications package (CASA) is a science data analysis package for the Atacama Large Millimeter/submillimeter Array (ALMA). As the fundamental format of CASA, Measurement Set (MS) is emphatically reviewed. Also, a newScience Data Model (SDM) designed to be used in ALMA telescope during the observing process and offline in the ALMA science data archive is expected to play an important role in the format of radio astronomy data storage. In the end, we present a study about the imports and exports of the formats to show the advantage and disadvantage on storage space of each format. Meanwhile, a conclusion has been made.

show abstract

“…Further, we observe that two types of sub-objects can be distinguished called structured objects (SO) and base objects (BO) [13]. Structured objects consist of sub-objects, and base objects are the smallest units that have no further inner structure.…”

Section: Modeling Data Cubes With Complex Spatial Datamentioning

confidence: 99%

OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses

Viswanathan

Schneider

2011

Data Warehousing and Knowledge Discovery

Self Cite

View full text Add to dashboard Cite

Abstract. In recent years, there has been a large increase in the amount of spatial data obtained from remote sensing, GPS receivers, communication terminals and other domains. Data warehouses help in modeling and mining large amounts of data from heterogeneous sources over an extended period of time. However incorporating spatial data into data warehouses leads to several challenges in data modeling, management and the mining of spatial information. New multidimensional data types for spatial application objects require new OLAP formulations to support query and analysis operations on them. In this paper, we introduce a set of constructs called C 3 for defining data cubes. These include categorization, containment and cubing operations, which present a fundamentally new, user-centric strategy for the conceptual modeling of data cubes. We also present a novel region-hierarchy concept that builds spatially ordered sets of polygon objects and employs them as first class citizens in the data cube. Further, new OLAP constructs to help define, manipulate, query and analyze spatial data have also been presented. Overall, the aim of this paper is to leverage support for spatial data in OLAP cubes and pave the way for the development of a user-centric SOLAP system.

show abstract

iBLOB: Complex Object Management in Databases through Intelligent Binary Large Objects

Cited by 5 publications

References 7 publications

Spatial Plateau Algebra for implementing fuzzy spatial objects in databases and GIS: Spatial plateau data types and operations

Spatial Plateau Algebra for implementing fuzzy spatial objects in databases and GIS: Spatial plateau data types and operations

A Survey on File Format for Data Storage in Radio Astronomy

OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses

Contact Info

Product

Resources

About