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Database Integration: the Key to Data Interoperability

Publications associées (71)

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Time- and Space-Efficient Spatial Data Analytics

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Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

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IEEE2019

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Independent modeling of various modules of an information system (IS), and consequently database subschemas, may result in formal or semantic conflicts between the modules being modeled. Such conflicts may cause collisions between the integrated database s ...

2019

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Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and ele ...

PERGAMON-ELSEVIER SCIENCE LTD2019

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We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...

2019

Privacy - Preserving Data Exchange and Aggregation in Healthcare

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A simple task of storing a database or transferring it to a different point via a communication channel turns far more complex as the size of the database grows large. Limited bandwidth available for transmission plays a central role in this predicament. I ...

EPFL2018

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We study user interaction with touchscreens based on swipe gestures for personal authentication. This approach has been analyzed only recently in the last few years in a series of disconnected and limited works. We summarize those recent efforts and then c ...

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Just-in-time Analytics Over Heterogeneous Data and Hardware

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Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the same time, data variety increases continuously across multiple axes. First, data comes in mu ...

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CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning

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Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. At the same time, the existing tools that att ...

Assoc Computing Machinery2017