High Performance Dynamic Graph Model for Consistent Data Integration

Since large amount of geospatial data are produced by various sources, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. We mainly adopt four kinds of geospatial data sources to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).

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Semantic Web and Geospatial Unique Features Based Geospatial Data Integration

Geospatial Intelligence ◽

10.4018/978-1-5225-8054-6.ch011 ◽

2019 ◽

pp. 230-253

Author(s):

Ying Zhang ◽

Chaopeng Li ◽

Na Chen ◽

Shaowen Liu ◽

Liming Du ◽

...

Keyword(s):

Semantic Web ◽

Data Integration ◽

High Performance ◽

Data Access ◽

Heterogeneous Data ◽

Geospatial Data ◽

Data Sources ◽

Modeling Process ◽

Translation Function ◽

Data Source

Since large amount of geospatial data are produced by various sources and stored in incompatible formats, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. First, we provide a uniform integration paradigm for users to retrieve geospatial data. Then, we align the retrieved geospatial data in the modeling process to eliminate heterogeneity with the help of Karma. Our main contribution focuses on addressing the third problem. Previous work has been done by defining a set of semantic rules for performing the linking process. However, the geospatial data has some specific geospatial relationships, which is significant for linking but cannot be solved by the Semantic Web techniques directly. We take advantage of such unique features about geospatial data to implement the linking process. In addition, the previous work will meet a complicated problem when the geospatial data sources are in different languages. In contrast, our proposed linking algorithms are endowed with translation function, which can save the translating cost among all the geospatial sources with different languages. Finally, the geospatial data is integrated by eliminating data redundancy and combining the complementary properties from the linked records. We mainly adopt four kinds of geospatial data sources, namely, OpenStreetMap(OSM), Wikmapia, USGS and EPA, to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).

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Semantic-Based Geospatial Data Integration With Unique Features

Innovations, Developments, and Applications of Semantic Web and Information Systems - Advances in Web Technologies and Engineering ◽

10.4018/978-1-5225-5042-6.ch015 ◽

2018 ◽

pp. 393-416

Author(s):

Ying Zhang ◽

Chaopeng Li ◽

Na Chen ◽

Shaowen Liu ◽

Liming Du ◽

...

Keyword(s):

Data Integration ◽

High Performance ◽

Data Access ◽

Heterogeneous Data ◽

Geospatial Data ◽

Experimental Results ◽

Data Sources ◽

Data Format ◽

Access Protocols ◽

Data Source

Since large amount of geospatial data are produced by various sources, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. We mainly adopt four kinds of geospatial data sources to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).

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Graph Entropy Associated with Multilevel Atomic Excitation

Proceedings ◽

10.3390/ecea-5-06675 ◽

2020 ◽

Vol 46 (1) ◽

pp. 9

Author(s):

Abu Mohamed Alhasan

Keyword(s):

Hyperfine Structure ◽

Transition Matrix ◽

Graph Model ◽

Connectivity Matrix ◽

Dynamic Graph ◽

Short Pulses ◽

Atomic Excitation ◽

Energy Concept ◽

Metal Atoms ◽

Spatiotemporal Behavior

A graph-model is presented to describe multilevel atomic structure. As an example, we take the double Λ configuration in alkali-metal atoms with hyperfine structure and nuclear spin I = 3 / 2 , as a graph with four vertices. Links are treated as coherence. We introduce the transition matrix which describes the connectivity matrix in static graph-model. In general, the transition matrix describes spatiotemporal behavior of the dynamic graph-model. Furthermore, it describes multiple connections and self-looping of vertices. The atomic excitation is made by short pulses, in order that the hyperfine structure is well resolved. Entropy associated with the proposed dynamic graph-model is used to identify transitions as well as local stabilization in the system without invoking the energy concept of the propagated pulses.

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Transportation, Germs, Culture: A Dynamic Graph Model of 2019-nCoV Spread

10.20944/preprints202002.0063.v1 ◽

2020 ◽

Author(s):

Xiaofei Yang ◽

Tun Xu ◽

Peng Jia ◽

Han Xia ◽

Li Guo ◽

...

Keyword(s):

Graph Model ◽

Emergency Situation ◽

Contributing Factors ◽

Dynamic Graph ◽

Model And Simulation ◽

Health Authorities ◽

Public Health Authorities ◽

Precise Prediction ◽

Novel Coronavirus ◽

Major Factors

Since the outbreak of 2019 novel coronavirus (2019-nCoV) at the hardest-hit city of Wuhan, the fast-moving spread has killed over three hundred people and infected more than ten thousands in China1. There are more than one hundred cases outside of China, affecting a dozen of countries globally2. The genome sequence of 2019-nCoV has been reported and fast diagnostic kits, effective treatment as well as preventive vaccines are rapidly being developed3. Initial fast-growing confirmed cases triggered lock-down of Wuhan as well as nearby cities in Hubei Province. Mathematical models have been proposed by scientists around the world to project the numbers of infected cases in the coming days 4,5. However, major factors such as transportation and cultural customs have not been weighed enough. Our model is not set out for precise prediction of the number of infected cases, rather, it is meant for a glance of the dynamics under a public epidemic emergency situation and of different contributing factors. We hope that our model and simulation would provide more insights and perspective information to public health authorities around the globe for better informed prevention and containment solution.

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