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Dataspaces

Known as: Data Spaces, Data space, Dataspace 
Dataspaces are an abstraction in data management that aim to overcome some of the problems encountered in data integration system. The aim is to… 
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Related topics

Related topics

8 relations
Conceptual graphData miningNeuromancerSemantic integration

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2015
Highly Cited
2015
Autoencoding beyond pixels using a learned similarity metric
We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a… 
Highly Cited
2010
Highly Cited
2010
DataSpaces: an interaction and coordination framework for coupled simulation workflows
Emerging high-performance distributed computing environments are enabling new end-to-end formulations in science and engineering… 
Highly Cited
2006
Highly Cited
2006
Principles of dataspace systems
The most acute information management challenges today stem from organizations relying on a large number of diverse, interrelated… 
Highly Cited
2003
Highly Cited
2003
Pervasive Computing: A Paradigm for the 21st Century
Pervasive computing promises to make life simpler via digital environments that sense, adapt, and respond to human needs. Yet we… 
Highly Cited
2002
Highly Cited
2002
Solving Fredholm integrals of the first kind with tensor product structure in 2 and 2.5 dimensions
We present an efficient algorithm to solve a class of two- and 2.5-dimensional (2-D and 2.5-D) Fredholm integrals of the first… 
Highly Cited
2002
Highly Cited
2002
Diffusion kernels on graphs and other discrete structures
The application of kernel-based learning algorithms has, so far, largely been confined to real-valued data and a few special data… 
Highly Cited
1999
Highly Cited
1999
Fast algorithms for projected clustering
The clustering problem is well known in the database literature for its numerous applications in problems such as customer… 
Highly Cited
1998
Highly Cited
1998
GTM: The Generative Topographic Mapping
Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of… 
Highly Cited
1997
Highly Cited
1997
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
A new access method, called M-tree, is proposed to organize and search large data sets from a generic “metric space”, i.e. where… 
Highly Cited
1977
Highly Cited
1977
DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION
Landsat-1 and -2 multispectral scanner (MSS) data from six overpass dates (April 2, May 17, June 4, July 10, October 17, and… 
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