Data Integration, Semantic Data Representation and Decision Support for Situational Awareness in Protection of Critical Assets

2014 ◽  
Author(s):  
Atta Badii ◽  
Marco Tiemann ◽  
Daniel Thiemert
Keyword(s):  
Decision Support ◽  
Data Integration ◽  
Situational Awareness ◽  
Data Representation ◽  
Semantic Data

Towards Semantic Data Integration in Resource-Limited Settings for Decision Support on Gait-Related Diseases

2021 ◽  
pp. 236-256
Author(s):  
Olawande Daramola ◽  
Thomas Moser
Keyword(s):  
Decision Support ◽  
Data Integration ◽  
Multiple Sources ◽  
Resource Limited Settings ◽  
Common People ◽  
Semantic Data ◽  
Resource Limited ◽  
Semantic Data Integration ◽  
The Status ◽  
Ict Infrastructure

Resource-limited settings (RLS) are characterised by lack of access to adequate resources such as ICT infrastructure, qualified medical personnel, healthcare facilities, and affordable healthcare for common people. The potential for the application of AI and clinical decision support systems in RLS are limited due to these challenges. Towards the improvement of the status quo, this chapter presents the conceptual design of a framework for the semantic integration of health data from multiple sources to facilitate decision support for the diagnosis and treatment of gait-related diseases in RLS. The authors describe how the framework can leverage ontologies and knowledge graphs for semantic data integration to achieve this. The plausibility of the proposed framework and the general imperatives for its practical realisation are also presented.

scholarly journals Consistency and Modularity in Mediated Service-Based Data Integration Solutions

2010 ◽  
pp. 98-113
Author(s):  
Yaoling Zhu ◽  
Claus Pahl
Keyword(s):  
Information Systems ◽  
Data Integration ◽  
Web Service ◽  
Data Transformation ◽  
Data Representation ◽  
Data Models ◽  
Information System Architecture ◽  
Semantic Data ◽  
Service Oriented ◽  
High Degree

A major aim of the Web service platform is the integration of existing software and information systems. Data integration is a central aspect in this context. Traditional techniques for information and data transformation are, however, not sufficient to provide flexible and automatable data integration solutions for Web service-enabled information systems. The difficulties arise from a high degree of complexity in data structures in many applications and from the additional problem of heterogeneity of data representation in applications that often cross organisational boundaries. The authors present an integration technique that embeds a declarative data transformation technique based on semantic data models as a mediator service into a Web service-oriented information system architecture. Automation through consistency-oriented semantic data models and flexibility through modular declarative data transformations are the key enablers of the approach.

scholarly journals Towards a Semantic Data Harmonization Federated Infrastructure

2021 ◽  
Author(s):  
Catalina Martinez-Costa ◽  
Francisco Abad-Navarro
Keyword(s):  
Data Integration ◽  
Data Sharing ◽  
Medical Informatics ◽  
Data Representation ◽  
Heterogeneous Data ◽  
Common Data Model ◽  
Snomed Ct ◽  
Data Harmonization ◽  
Semantic Data ◽  
Upper Level

Data integration is an increasing need in medical informatics projects like the EU Precise4Q project, in which multidisciplinary semantically and syntactically heterogeneous data across several institutions needs to be integrated. Besides, data sharing agreements often allow a virtual data integration only, because data cannot leave the source repository. We propose a data harmonization infrastructure in which data is virtually integrated by sharing a semantically rich common data representation that allows their homogeneous querying. This common data model integrates content from well-known biomedical ontologies like SNOMED CT by using the BTL2 upper level ontology, and is imported into a graph database. We successfully integrated three datasets and made some test queries showing the feasibility of the approach.

scholarly journals Consistency and Modularity in Mediated Service-Based Data Integration Solutions

2011 ◽  
pp. 997-1012
Author(s):  
Yaoling Zhu ◽  
Claus Pahl
Keyword(s):  
Information Systems ◽  
Data Integration ◽  
Web Service ◽  
Data Transformation ◽  
Data Representation ◽  
Data Models ◽  
Information System Architecture ◽  
Semantic Data ◽  
Service Oriented ◽  
High Degree

A major aim of the Web service platform is the integration of existing software and information systems. Data integration is a central aspect in this context. Traditional techniques for information and data transformation are, however, not sufficient to provide flexible and automatable data integration solutions for Web service-enabled information systems. The difficulties arise from a high degree of complexity in data structures in many applications and from the additional problem of heterogeneity of data representation in applications that often cross organisational boundaries. The authors present an integration technique that embeds a declarative data transformation technique based on semantic data models as a mediator service into a Web service-oriented information system architecture. Automation through consistency-oriented semantic data models and flexibility through modular declarative data transformations are the key enablers of the approach.

Context-Driven Proactive Decision Support for Hybrid Teams

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 41-57
Author(s):  
Manisha Mishra ◽  
Pujitha Mannaru ◽  
David Sidoti ◽  
Adam Bienkowski ◽  
Lingyi Zhang ◽  
...  
Keyword(s):  
Decision Support ◽  
Situational Awareness ◽  
Feature Space ◽  
Human Interaction ◽  
Superior Performance ◽  
Uncertain Environments ◽  
Cognitive States ◽  
Contextual Elements ◽  
Human Operators ◽  
Smart Machine

A synergy between AI and the Internet of Things (IoT) will significantly improve sense-making, situational awareness, proactivity, and collaboration. However, the key challenge is to identify the underlying context within which humans interact with smart machines. Knowledge of the context facilitates proactive allocation among members of a human–smart machine (agent) collective that balances auto­nomy with human interaction, without displacing humans from their supervisory role of ensuring that the system goals are achievable. In this article, we address four research questions as a means of advancing toward proactive autonomy: how to represent the interdependencies among the key elements of a hybrid team; how to rapidly identify and characterize critical contextual elements that require adaptation over time; how to allocate system tasks among machines and agents for superior performance; and how to enhance the performance of machine counterparts to provide intelligent and proactive courses of action while considering the cognitive states of human operators. The answers to these four questions help us to illustrate the integration of AI and IoT applied to the maritime domain, where we define context as an evolving multidimensional feature space for heterogeneous search, routing, and resource allocation in uncertain environments via proactive decision support systems.

scholarly journals Assessing a Decision Support Tool for SOC Analysts

2021 ◽  
Author(s):  
Jassim Happa ◽  
Ioannis Agrafiotis ◽  
Martin Helmhout ◽  
Thomas Bashford-Rogers ◽  
Michael Goldsmith ◽  
...  
Keyword(s):  
Decision Support ◽  
Mixed Method ◽  
User Study ◽  
Situational Awareness ◽  
Decision Support Tool ◽  
Lessons Learned ◽  
Visualization Tool ◽  
Support Tool ◽  
Response Strategies ◽  
Method Approach

In recent years, many tools have been developed to understand attacks that make use of visualization, but few examples aims to predict real-world consequences. We have developed a visualization tool that aims to improve decision support during attacks. Our tool visualizes propagation of risks from IDS and AV-alert data by relating sensor alerts to Business Process (BP) tasks and machine assets: an important capability gap present in many Security Operation Centres (SOCs) today. In this paper we present a user study in which we evaluate the tool's usability and ability to deliver situational awareness to the analyst. Ten analysts from seven SOCs performed carefully designed tasks related to understanding risks and prioritising recovery decisions. The study was conducted in laboratory conditions, with simulated attacks, and used a mixed-method approach to collect data from questionnaires, eyetracking and voice-recorded interviews. The findings suggest that providing analysts with situational awareness relating to business priorities can help them prioritise response strategies. Finally, we provide an in-depth discussion on the wider questions related to user studies in similar conditions as well as lessons learned from our user study and developing a visualization tool of this type.

CIM Dictionaries: An Evolutionary Approach to CIM Data Integration

1991 ◽  
Author(s):  
Uwe Weissflog
Keyword(s):  
Data Integration ◽  
Added Value ◽  
Heterogeneous Environments ◽  
Semantic Data ◽  
Application Systems ◽  
Homogeneous Set ◽  
Semantic Data Model ◽  
Additional Service ◽  
Product Definition

Abstract This paper provides an overview of methods and ideas to achieve data integration in CIM. It describes a dictionary approach allowing participating applications to define their common constructs gradually as an additional service across application systems. Because of the importance of product definition data, the role of PDES/STEP as part of this dictionary approach is also described. The technical concepts of the dictionary, such as schema mapping, semantic data model, user methods and the required additions within participating applications are explained. Problems related to data integrity, data redundancy, performance and binding of dissimilar software components are discussed as well as the deficiencies related to today’s data modelling capabilities. The added value an active dictionary can provide to a CIM environment consisting of established applications in heterogeneous environments, where migration into one standardized homogeneous set of CIM applications is not likely, is also explained.

scholarly journals TOWARDS LIMITING SEMANTIC DATA LOSS IN 4D URBAN DATA SEMANTIC GRAPH GENERATION

2021 ◽  
Vol VIII-4/W2-2021 ◽  
pp. 37-44
Author(s):  
D. Vinasco-Alvarez ◽  
J. Samuel ◽  
S. Servigne ◽  
G. Gesquière
Keyword(s):  
Data Integration ◽  
Urban Landscape ◽  
Temporal Data ◽  
Data Loss ◽  
Large Area ◽  
Semantic Graph ◽  
Semantic Data ◽  
Spatio Temporal ◽  
City Models ◽  
Urban Data

Abstract. To enrich urban digital twins and better understand city evolution, the integration of heterogeneous, spatio-temporal data has become a large area of research in the enrichment of 3D and 4D (3D + Time) semantic city models. These models, which can represent the 3D geospatial data of a city and their evolving semantic relations, may require data-driven integration approaches to provide temporal and concurrent views of the urban landscape. However, data integration often requires the transformation or conversion of data into a single shared data format, which can be prone to semantic data loss. To combat this, this paper proposes a model-centric ontology-based data integration approach towards limiting semantic data loss in 4D semantic urban data transformations to semantic graph formats. By integrating the underlying conceptual models of urban data standards, a unified spatio-temporal data model can be created as a network of ontologies. Transformation tools can use this model to map datasets to interoperable semantic graph formats of 4D city models. This paper will firstly illustrate how this approach facilitates the integration of rich 3D geospatial, spatio-temporal urban data and semantic web standards with a focus on limiting semantic data loss. Secondly, this paper will demonstrate how semantic graphs based on these models can be implemented for spatial and temporal queries toward 4D semantic city model enrichment.

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