Knowledge Base Commons (KBCommons) v1.0: A multi OMICS' web-based data integration framework for biological discoveries

2018 ◽  
Author(s):  
Shuai Zeng ◽  
Zhen Lyu ◽  
Siva Ratna Kumari Narisetti ◽  
Dong Xu ◽  
Trupti Joshi
Keyword(s):  
Data Integration ◽  
Knowledge Base ◽  
Web Based ◽  
Integration Framework

WIF4InL: Web-based integration framework for Indoor location

2016 ◽  
Vol 12 (1) ◽  
pp. 49-65 ◽  
Author(s):  
Long Niu ◽  
Sachio Saiki ◽  
Shinsuke Matsumoto ◽  
Masahide Nakamura
Keyword(s):  
Application Programming Interface ◽  
Common Data Model ◽  
Loose Coupling ◽  
Web Based ◽  
Integration Framework ◽  
Content Type ◽  
Positioning Systems ◽  
Indoor Location ◽  
Location Data ◽  
Application Programming

Purpose The purpose of this paper is to establish an application platform that addresses expensive development cost and effort of indoor location-aware application (InL-Apps) problems caused by tightly coupling between InL-App and indoor positioning systems (IPSs). Design/methodology/approach To achieve this purpose, in this paper, the authors proposes a Web-based integration framework called Web-based Integration Framework for Indoor Location (WIF4InL). With a common data model, WIF4InL integrates indoor location data obtained from heterogeneous IPS. It then provides application-neutral application programming interface (API) for various InL-Apps. Findings The authors integrate two different IPS (RedPin and BluePin) using WIF4InL and conduct a comparative study which is based on sufficiency of essential capabilities of location-dependent queries among three systems: RedPin, BluePin and WIF4InL. WIF4InL supports more capabilities for the location-dependent queries. Through the data and operation integration, WIF4InL even enriches the existing proprietary IPS. Originality/value As WIF4InL allows the loose coupling between IPS and InL-Apps, it significantly improves reusability of indoor location information and operation.

Extending a Conventional Chatbot Knowledge Base to External Knowledge Source and Introducing User-Based Sessions for Diabetes Education

2019 ◽  
pp. 333-343
Author(s):  
Shafquat Hussain ◽  
Athula Ginige
Keyword(s):  
Knowledge Base ◽  
Local Knowledge ◽  
Health Informatics ◽  
Diabetes Management ◽  
Diabetes Education ◽  
Conversational Agents ◽  
Knowledge Source ◽  
Web Based ◽  
External Knowledge ◽  
User Query

Chatbots or conversational agents are computer programs that interact with users using natural language through artificial intelligence in a way that the user thinks he is having dialogue with a human. One of the main limits of chatbot technology is associated with the construction of its local knowledge base. A conventional chatbot knowledge base is typically hand constructed, which is a very time-consuming process and may take years to train a chatbot in a particular field of expertise. This chapter extends the knowledge base of a conventional chatbot beyond its local knowledge base to external knowledge source Wikipedia. This has been achieved by using Media Wiki API to retrieve information from Wikipedia when the chatbot's local knowledge base does not contain the answer to a user query. To make the conversation with the chatbot more meaningful with regards to the user's previous chat sessions, a user-specific session ability has been added to the chatbot architecture. An open source AIML web-based chatbot has been modified and programmed for use in the health informatics domain. The chatbot has been named VDMS – Virtual Diabetes Management System. It is intended to be used by the general community and diabetic patients for diabetes education and management.

scholarly journals Framework for a Symmetric Integration Approach

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 224
Author(s):  
Mihaela Muntean ◽  
Claudiu Brândaş ◽  
Tanita Cîrstea
Keyword(s):  
Data Integration ◽  
Open Data ◽  
Application Integration ◽  
Cloud Environment ◽  
Integration Framework ◽  
Symmetry Approach ◽  
Integration Approach ◽  
Implementation Aspects

An Application-to-Application integration framework in the cloud environment is proposed. The methodological demarche is developed using a data symmetry approach. Implementation aspects of integration considered the Open Data Protocol (OData) service as an integrator. An important issue in the cloud environment is to integrate and ensure the quality of transferred and processed data. An efficient way of ensuring the completeness and integrity of data transferred between different applications and systems is the symmetry of data integration. With these considerations, the integration of SAP Hybris Cloud for Customer with S/4 HANA Cloud was implemented.

Design and Implementation of Oilfield Heterogeneous Data Integration Model Based on Ontology

2014 ◽  
Vol 912-914 ◽  
pp. 1201-1204
Author(s):  
Gang Huang ◽  
Xiu Ying Wu ◽  
Man Yuan
Keyword(s):  
Data Integration ◽  
Heterogeneous Data ◽  
Data Sources ◽  
Semantic Heterogeneity ◽  
Integration Model ◽  
Integration Framework ◽  
Heterogeneous Data Integration ◽  
Semantic Level ◽  
Heterogeneous Data Sources ◽  
Semantic Difference

This paper provides an ontology-based distributed heterogeneous data integration framework (ODHDIF). The framework resolves the problem of semantic interoperability between heterogeneous data sources in semantic level. By metadatas specifying the distributed, heterogeneous data and by describing semantic information of data source , having "ontology" as a common semantic model, semantic match is established through ontology mapping between heterogeneous data sources and semantic difference institutions are shielded, so that semantic heterogeneity problem of the heterogeneous data sources can be effectively solved. It provides an effective technology measure for the interior information of enterprises to be shared in time accurately.

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