Study on Storage and Query System of Legal Documents

2014 ◽  
Vol 533 ◽  
pp. 452-455
Author(s):  
Liu Yang
Keyword(s):  
Information Integration ◽  
Data Centers ◽  
Integration System ◽  
Legal Documents ◽  
Global Schema ◽  
Data Source ◽  
Query System ◽  
Central Database ◽  
Global Data

There is a logically centralized level global data centers to meet the global schema database for centralized storage needs. This will not only ensure efficient query dataset brings advantages, without compromising the autonomy of each data source. Logically centralized layer needs to have at least a central database, data dump module. This paper studies storage and query system of legal documents based on the information integration system and its implementation methods, the application can be completed more intelligent reasoning queries.

SHRDIS: A Semantic-Based Heterogeneous Relational Data Integration System

2010 ◽  
Vol 121-122 ◽  
pp. 335-340
Author(s):  
Jin Peng Wang ◽  
Ya Fei Zhang ◽  
Jian Jiang Lu ◽  
Zhuang Miao
Keyword(s):  
Data Integration ◽  
Relational Databases ◽  
Research Field ◽  
Relational Data ◽  
New Paradigm ◽  
Integration System ◽  
Global Schema ◽  
Database Research ◽  
Data Integration System ◽  
Data Source

Integrating and querying data from heterogeneous sources is a hot research topic in database research field. The emergence of the Semantic Web brings new paradigm shift of computing in data integration research where data is heterogeneous and distributed. To solve the problem this paper proposes a semantic-based approach. A Semantic-based Heterogeneous Relational Data Integration System, called SHRDIS, is presented. In this system, ontology is used as the mediated schema for the representation of the data source semantics. SPARQL queries over global schema are rewritten into local SQL queries that can be executed on heterogeneous relational databases. The architecture and implementation of SHRDIS is illustrated in detail. The experiment results show that the SHRDIS system has nice performance and scalability.

A Global Data Model for Electric Power Data Centers

2019 ◽  
Author(s):  
ZhiQiang Wang ◽  
WanJian Bai ◽  
AiQiang Dong ◽  
FuHua Zhang ◽  
Bo Li
Keyword(s):  
Electric Power ◽  
Data Model ◽  
Data Centers ◽  
Global Data

THE USE OF CARIN LANGUAGE AND ALGORITHMS FOR INFORMATION INTEGRATION: THE PICSEL SYSTEM

2000 ◽  
Vol 09 (04) ◽  
pp. 383-401 ◽  
Author(s):  
FRANÇOIS GOASDOUÉ ◽  
VÉRONIQUE LATTÈS ◽  
MARIE-CHRISTINE ROUSSET
Keyword(s):  
Information Integration ◽  
Information Sources ◽  
Expressive Power ◽  
Real Case ◽  
Travel Agency ◽  
Integration System ◽  
The Core ◽  
Knowledge Based ◽  
Information Server ◽  
Logical Formalism

PICSEL is an information integration system over sources that are distributed and possibly heterogeneous. The approach which has been chosen in PICSEL is to define an information server as a knowledge-based mediator in which CARIN is used as the core logical formalism to represent both the domain of application and the contents of information sources relevant to that domain. In this paper, we describe the way the expressive power of the CARIN language is exploited in the PICSEL information integration system, while maintaining the decidability of query answering. We illustrate it on examples coming from the tourism domain, which is the first real case that we have to consider in PICSEL, in collaboration with the travel agency Degriftour. see

Extracting Funder and Grant Metadata from Journal Articles

2016 ◽  
Author(s):  
Mark Gross ◽  
Tammy Bilitzky ◽  
Richard Thorne
Keyword(s):  
Open Source ◽  
Recent Work ◽  
Source Distribution ◽  
Funding Source ◽  
Journal Articles ◽  
Legal Documents ◽  
The Past ◽  
Scientific Technical ◽  
Data Source

Scientific, Technical, and Medical (STM) journal articles are an explosively growing data source with constantly increasing requirements for complex metadata. Newly important has been the identification of funding and grant data. It has become critical that publishers know the sources of funding for journal articles so that they can meet the associated open source distribution obligations and so that funding organizations can track publications associated with their funding. Managing this information manually is costly and often inaccurate. Over the past few years, we have been working on enhancing techniques to extract various kinds of metadata automatically from scientific and legal documents. We report here on recent work to extract funding source and grant information from within STM journal articles.

scholarly journals Semantic IFC Data Model for Automatic Safety Risk Identification in Deep Excavation Projects

2021 ◽  
Vol 11 (21) ◽  
pp. 9958
Author(s):  
Yongcheng Zhang ◽  
Xuejiao Xing ◽  
Maxwell Fordjour Antwi-Afari
Keyword(s):  
Information Integration ◽  
Data Model ◽  
Risk Identification ◽  
Project Planning ◽  
Information Modeling ◽  
Deep Excavation ◽  
Safety Risk ◽  
Semantic Data ◽  
Construction Risk ◽  
Central Database

Safety risk identification throughout deep excavation construction is an information-intensive task, involving construction information scattered in project planning documentation and dynamic information obtained from different field sensors. However, inefficient information integration and exchange have been an important obstacle to the development of automatic safety risk identification in actual applications. This research aims to achieve the requirements for information integration and exchange by developing a semantic industry foundation classes (IFC) data model based on a central database of Building Information Modeling (BIM) in dynamic deep excavation process. Construction information required for risk identification in dynamic deep excavation is analyzed. The relationships among construction information are identified based on the semantic IFC data model, involved relationships (i.e., logical relationships and constraints among risk events, risk factors, construction parameters, and construction phases), and BIM elements. Furthermore, an automatic safety risk identification approach is presented based on the semantic data model, and it is tested through a construction risk identification prototype established under the BIM environment. Results illustrate the effectiveness of the BIM-based central database in accelerating automatic safety risk identification by linking BIM elements and required construction information corresponding to the dynamic construction process.

scholarly journals AN INTERACTIVE LOGISTICS CENTRE INFORMATION INTEGRATION SYSTEM USING VIRTUAL REALITY

2018 ◽  
Vol XLII-3 ◽  
pp. 523-526
Author(s):  
S. Hong ◽  
B. Mao
Keyword(s):  
Virtual Reality ◽  
Information Integration ◽  
Sensor Data ◽  
Virtual Reality Technology ◽  
Integration System ◽  
Logistics Industry ◽  
Emergency Situations ◽  
Supervision Training ◽  
Modern Cities ◽  
The One

The logistics industry plays a very important role in the operation of modern cities. Meanwhile, the development of logistics industry has derived various problems that are urgent to be solved, such as the safety of logistics products. This paper combines the study of logistics industry traceability and logistics centre environment safety supervision with virtual reality technology, creates an interactive logistics centre information integration system. The proposed system utilizes the immerse characteristic of virtual reality, to simulate the real logistics centre scene distinctly, which can make operation staff conduct safety supervision training at any time without regional restrictions. On the one hand, a large number of sensor data can be used to simulate a variety of disaster emergency situations. On the other hand, collecting personnel operation data, to analyse the improper operation, which can improve the training efficiency greatly.

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