scholarly journals A Framework for Visualizing Heterogeneous Construction Data Using Semantic Web Standards

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Mostafa Ali ◽  
Yasser Mohamed
Keyword(s):  
Ad Hoc ◽  
3D Visualization ◽  
Heterogeneous Data ◽  
Data Merging ◽  
Levels Of Detail ◽  
Heterogeneous Data Sources ◽  
Web Standards ◽  
Visualization Process ◽  
Merging Process ◽  
Different Sources

3D Visualization provides a mean for communicating different construction activities to diverse audiences. The scope, level of detail, and time resolution of the 3D visualization process are determined based on the targeted audiences. Developing the 3D visualization requires obtaining and merging heterogeneous data from different sources (such as BIM model and CPM schedule). The data merging process is usually carried out on ad hoc basis for a specific visualization case which limits the reusability of the process. This paper discusses a framework for automatic merging of heterogeneous data to create a visualization. The paper describes developing an ontology which captures concepts related to the visualization process. Then, heterogeneous data sources that are commonly used in construction are fed into the ontology which can be queried to produce different visualization scenarios. The potential of this approach has been demonstrated by providing multiple visualization scenarios that cover different audiences, levels of detail, and time resolutions.

scholarly journals A Description of Clinical Decision Support Framework Prediction in Heterogeneous Data Sources

2019 ◽  
Vol 8 (6S) ◽  
pp. 425-427
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Heterogeneous Data ◽  
Scientific Discipline ◽  
Work Environments ◽  
Data Sources ◽  
Heterogeneous Data Sources ◽  
Decision Support Framework ◽  
Different Sources

To keep pace with the updates in obliging scientific discipline, thriving recuperating knowledge is being assembled incessantly. Regardless, inferable from the not too appalling gathering of its categories and sources, therapeutic knowledge has over up being significantly hugger-mugger in numerous specialist's work environments that it currently wants Clinical call Support (CDS) system for its affiliation. To reasonably utilize the party flourishing knowledge, we tend to propose a CDS structure which will distort mixed thriving knowledge from totally different sources, for example, take a goose at workplace check works out as planned, important info of patients and action records into a joined depiction of options everything thought-about. Victimization the electronic roaring healing knowledge therefore created, multi-name delineation was accustomed endorse a layout of afflictions and so facilitate consultants in diagnosis or treating their patients' therapeutic problems a lot of competently. Once the ace sees the contamination of a patient, the running with organize is to contemplate the conceivable complexities of that disarray, which may impel a lot of infections

scholarly journals Towards Establishing Cross-Platform Interoperability for Sensors in Smart Cities

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 562 ◽  
Author(s):  
Kanishk Chaturvedi ◽  
Thomas Kolbe
Keyword(s):  
Data Storage ◽  
Smart City ◽  
Smart Cities ◽  
Heterogeneous Data ◽  
International Standards ◽  
Integration Strategy ◽  
Heterogeneous Data Sources ◽  
Cross Platform ◽  
Iot Platforms ◽  
Different Sources

Typically, smart city projects involve complex distributed systems having multiple stakeholders and diverse applications. These applications involve a multitude of sensor and IoT platforms for managing different types of timeseries observations. In many scenarios, timeseries data is the result of specific simulations and is stored in databases and even simple files. To make well-informed decisions, it is essential to have a proper data integration strategy, which must allow working with heterogeneous data sources and platforms in interoperable ways. In this paper, we present a new lightweight web service called InterSensor Service allowing to simply connect to multiple IoT platforms, simulation specific data, databases, and simple files and retrieving their observations without worrying about data storage and the multitude of different APIs. The service encodes these observations “on-the-fly” according to the standardized external interfaces such as the OGC Sensor Observation Service and OGC SensorThings API. In this way, the heterogeneous observations can be analyzed and visualized in a unified way. The service can be deployed not only by the users to connect to different sources but also by providers and stakeholders to simply add further interfaces to their platforms realizing interoperability according to international standards. We have developed a Java-based implementation of the InterSensor Service, which is being offered free as open source software. The service is already being used in smart city projects and one application for the district Queen Elizabeth Olympic Park in London is shown in this paper.

A relational data harmonization approach to XML

2009 ◽  
Vol 35 (5) ◽  
pp. 571-601 ◽  
Author(s):  
Timo Niemi ◽  
Turkka Näppilä ◽  
Kalervo Järvelin
Keyword(s):  
Information Needs ◽  
Ad Hoc ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Similar Data ◽  
Xml Data ◽  
Processing Style ◽  
Heterogeneous Data Sources ◽  
Autonomous Data Sources ◽  
Data Source

There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.

scholarly journals INTEGRATION OF QUERIES TO HETEROGENEOUS DATA SOURCES USING LINQ TECHNOLOGY

2018 ◽  
Vol 7 (3) ◽  
pp. 180-189
Author(s):  
Marian Rusek ◽  
Waldemar Karwowski ◽  
Jakub Maguza
Keyword(s):  
Object Oriented ◽  
Data Access ◽  
Database Systems ◽  
Query Languages ◽  
Heterogeneous Data ◽  
Heterogeneous Data Sources ◽  
Abstract Data ◽  
Relational Data Base ◽  
Uniform Manner ◽  
Different Sources

Nowadays, the data are available in a variety of formats such as relational data-base tables, xml files, rdf files or simply text files. Database systems have their own query languages and tools for the manipulation of data. On the other hand, most of todays applications are created in languages based on the object-oriented paradigm. From the level of the programming language it is important to use different sources of data in a uniform manner. The paper discusses the elements of the various query languages such as SQL XQuery or SPARQL. And then shows the capabilities of LINQ and its role in the creation of abstract data access layer. Then the possibilities of LINQ extension are discussed. As the example, design and implementation of LINQ provider for Allegro is presented.

A Semi-Automatic Approach For Global-Schema Construction in Data Integration Systems

2013 ◽  
Vol 4 (2) ◽  
pp. 35-53 ◽  
Author(s):  
C. Niang ◽  
B. Bouchou Markhoff ◽  
Y. Sam ◽  
M. Lo
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Heterogeneous Data Sources ◽  
Global Schema ◽  
Combining Data ◽  
Reference Ontology ◽  
Unified View ◽  
Human Effort ◽  
Different Sources

Data integration involves combining data residing in different sources and providing users with a unified view of these data through what is called a “global schema’’. The authors address here the problem of the construction of this global schema, with a minimum human effort, in the semantic Web context where data sources are annotated with ontologies. The authors aim to facilitate the task of building a common vocabulary (ontology) that will serve as a shared conceptual level for several heterogeneous data sources needing to share their data in a specific application domain. The authors propose a solution based on the use of a domain reference ontology (or “background knowledge’’) as a mediation support and some reasoning techniques in order to minimize human intervention. The work presented here is implemented as a prototype for Semi Automatic Global Ontology Building (SAGOB).

A Hybrid Siamese Neural Network for Natural Language Inference in Cyber-Physical Systems

2021 ◽  
Vol 21 (2) ◽  
pp. 1-25
Author(s):  
Pin Ni ◽  
Yuming Li ◽  
Gangmin Li ◽  
Victor Chang
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Short Term Memory ◽  
Physical World ◽  
Heterogeneous Data ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Language Data ◽  
Text Language ◽  
Different Sources

Cyber-Physical Systems (CPS), as a multi-dimensional complex system that connects the physical world and the cyber world, has a strong demand for processing large amounts of heterogeneous data. These tasks also include Natural Language Inference (NLI) tasks based on text from different sources. However, the current research on natural language processing in CPS does not involve exploration in this field. Therefore, this study proposes a Siamese Network structure that combines Stacked Residual Long Short-Term Memory (bidirectional) with the Attention mechanism and Capsule Network for the NLI module in CPS, which is used to infer the relationship between text/language data from different sources. This model is mainly used to implement NLI tasks and conduct a detailed evaluation in three main NLI benchmarks as the basic semantic understanding module in CPS. Comparative experiments prove that the proposed method achieves competitive performance, has a certain generalization ability, and can balance the performance and the number of trained parameters.

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