Geological hazard assessment of the coastal area of Rome (Central Italy) from multi-source data integration

2022 ◽  
pp. 106527
Author(s):  
Roberta Maffucci ◽  
Giancarlo Ciotoli ◽  
Andrea Pietrosante ◽  
Gian Paolo Cavinato ◽  
Salvatore Milli ◽  
...  
Keyword(s):  
Data Integration ◽  
Hazard Assessment ◽  
Coastal Area ◽  
Central Italy ◽  
Geological Hazard ◽  
Source Data

Research on Multi-Source Data Integration Based on Ontology and Karma Modeling

2019 ◽  
Vol 15 (2) ◽  
pp. 69-87 ◽  
Author(s):  
Hongyan Yun ◽  
Ying He ◽  
Li Lin ◽  
Xiaohong Wang
Keyword(s):  
Data Integration ◽  
Armed Conflict ◽  
Domain Knowledge ◽  
Heterogeneous Data ◽  
Regional Conflict ◽  
Ontology Modeling ◽  
Source Data ◽  
Event Ontology ◽  
Query System ◽  
Rdf Data

The purpose of data integration is that integrates multi-source heterogeneous data. Ontology solves semantic describing of multi-source heterogeneous data. The authors propose a practical approach based on ontology modeling and an information toolkit named Karma modeling for fast data integration, and demonstrate an application example in detail. Armed Conflict Location & Event Data Project (ACLED) is a publicly available conflict event dataset designed for disaggregated conflict analysis and crisis mapping. The authors analyzed the ACLED dataset and domain knowledge to build an Armed Conflict Event ontology, then constructed Karma models to integrate ACLED datasets and publish RDF data. Through SPARQL query to check the correctness of published RDF data. Authors design and developed an ACLED Query System based on Jena API, Canvas JS, and Baidu API, etc. technologies, which provides convenience for governments and researches to analyze regional conflict events and crisis early warning, and it verifies the validity of constructed ontology and the correctness of Karma modeling.

scholarly journals IR-TEx: An Open Source Data Integration Tool for Big Data Transcriptomics Designed for the Malaria Vector Anopheles gambiae

10.3791/60721 ◽  
2020 ◽  
Author(s):  
Victoria A. Ingham ◽  
Andrew Bennett ◽  
Duo Peng ◽  
Simon C. Wagstaff ◽  
Hilary Ranson
Keyword(s):  
Big Data ◽  
Data Integration ◽  
Anopheles Gambiae ◽  
Open Source ◽  
Malaria Vector ◽  
Open Source Data ◽  
Source Data

A Method of Data Integration Based on Cloud

2013 ◽  
Vol 433-435 ◽  
pp. 1876-1879 ◽  
Author(s):  
Guo Ling Liu ◽  
Chun Hua Yang
Keyword(s):  
Data Integration ◽  
Service Platform ◽  
Integration Platform ◽  
Source Data ◽  
Integration Service

This work studied the situation of today’s data integration. To better solve the complexity and diversity in data integration, we propose a new idea of data integration service platform based on SaaS. The model architecture of data integration and its work principles are introduced. In the platform source data and result data are two interface.in the form of service. In the data integration platform, data are filtered and combined. the data are produced by the users’ requirements. Users call SaaS service to get the data that they wanted. Finally we analyze the model’s characters. This model of platform is more intelligent, efficient and personalized in solving complicate data integration.

Environmental geology problems in the Tyrrhenian coastal area of Santa Marinella, province of Rome, central Italy

1997 ◽  
Vol 32 (1) ◽  
pp. 1-8 ◽  
Author(s):  
U. Chiocchini ◽  
G. Gisotti ◽  
A. Macioce ◽  
F. Manna ◽  
A. Bolasco ◽  
...  
Keyword(s):  
Coastal Area ◽  
Central Italy ◽  
Environmental Geology

Indoor Location Algorithm Based on Kalman Filter and Multi-Source Data Integration

2016 ◽  
Vol 9 (4) ◽  
pp. 45-54
Author(s):  
Zhang Ya-qiong ◽  
Li Zhao-xing ◽  
Li Xin ◽  
Lv Zhihan-han
Keyword(s):  
Kalman Filter ◽  
Data Integration ◽  
Indoor Location ◽  
Source Data ◽  
Location Algorithm

Data Warehouse Oriented Data Integration System Design and Implementation

2013 ◽  
Vol 321-324 ◽  
pp. 2532-2538
Author(s):  
Xiao Guo Wang ◽  
Jian Shen ◽  
Chuan Sun
Keyword(s):  
Data Integration ◽  
Data Warehouse ◽  
Heterogeneous Data ◽  
Information Process ◽  
Efficient Tool ◽  
Integration System ◽  
Related Information ◽  
Source Data ◽  
Data Integration System ◽  
Database Technology

Considering the difficulty of information collection and integration due to the rapid growth of information, we need an efficient tool to do these jobs. A proposal is be put forward to build a data integration system to collect the source data and preprocess the heterogeneous data and then convert/extract data to the data warehouse. Through experiment and analysis, this paper designed an information process flow and implemented the data integration system, based on B/S framework with the database technology, to deal with the college related information.

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