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Common metadata to manage heterogeneous data from a variety of data sources Management of data permission and user authorization Unified user interfaces to explore data User assistance to recall memories from a mixture of heterogeneous data.
Common metadata to manage heterogeneous data from a variety of data sources.
This paper presents BIODB, an ontology-enhanced information system to manage heterogeneous data.
Given the number of stakeholders involved in a city, obtaining (and managing) such detailed information for each urban feature is however often a rather complex and resource-demanding task, as it requires to gather, harmonise, integrate, and eventually manage heterogeneous data for a large quantity of objects for the whole city.
The two-step cluster method is a scalable cluster analysis algorithm designed to manage heterogeneous data sets.
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Since data sources from applications and devices are characterized by multiple types of heterogeneities, such as communication protocols, blinding methods, and developing environments, the difficulty in managing heterogeneous data sources is highly raised.
In recent years, the biology community has expended considerable effort to confront the challenges of managing heterogeneous data in a structured and organized way and as a result developed information management systems for both raw and processed data.
However, complex systems scientists are unable to collect the huge databases necessary to plan and manage heterogeneous multilevel socio-technical systems these data are collected by public and private agencies according to perceived policy needs.
OpenNebula [9] is an open-source cloud computing toolkit for managing heterogeneous distributed data centre infrastructures.
The wide range of CSP support makes it feasible to manage heterogeneous resources across diverse clouds.
Moreover, a Grid approach has been considered and implemented in order to manage distributed, heterogeneous data and information, improve security policies and facilitate collaborative work.
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