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In this paper, the authors introduce a novel mechanism for data management in a middleware for smart home control, where a relational database and semantic ontology storage are used at the same time in a Data Warehouse. An annotation system has been designed for instructing the storage format and location, registering new ontology concepts and most importantly, guaranteeing the Data Consistency between...
The paper proposes a data management platform with an open architecture for converting huge amount of various and cluttered data into Lean Data, which provides customer-expected service and can be then encapsulated as service packages to be used by different application developers. Ontology is used to provide a unified way for data flow description and semantic data storage to achieve a unified understanding...
A methodology for content filtering based on ontology similarity is presented, which uses Domain Ontology to describe the characteristic of knowledge of a specific domain. By analyzing the context of the Word of Concern (WoC), the justifiability and accuracy of filter is improved. Firstly, a content ontology based on Domain Ontology is defined, including WoCs and their context constrain rules. Secondly,...
Nowadays, the sharing of e-education resources has become a big concern, as it helps to save manpower, physical resources, time and space. In this paper, a novel method is proposed for semantically indexing the huge amount of resources that are integrated together by an e-education resources sharing platform. The platform system architecture is illustrated, and an ontology is created to provide a...
There are many new challenges in building Scientific Data Management System (SDMS), and the most initial and important one of them is designing a reasonably and effectively data architecture. The data architecture should focus on massive metadata, complex data flow, multi-classification data, various data productions and uniform query. Based on the applied projects, we present the classificatory criterions,...
This paper is the case study on scientific data cleaning, it proposes some new ideas or applies some hot technologies for scientific data cleaning. There are three challenges of scientific data cleaning tool: domain knowledge representation and usage, customized cleaning flow and building dynamically. We adopt knowledge based rule modeling, workflow based flow modeling and pluggable components based...
The polymorphic, diversified, multi-sources and multi-use scientific data is quite different from the other data, there are many new challenges in building Scientific Data Management and Analysis System (SDMAS), especial one is that the multi-use data requires alternate classifications and mappings between them. Based on the oceanographic data, we present the solutions of multi-classifications problems...
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