Reconciliation of temporal semantic heterogeneity in evolving information systems

The change in meaning of data over time poses significant challenges for the use of that data. These challenges exist in the use of an individual data source and are further compounded with the integration of multiple sources. In this paper, we identify three types of temporal semantic heterogeneity. We propose a solution based on extensions to the Context Interchange framework, which has mechanisms for capturing semantics using ontology and temporal context. It also provides a mediation service that automatically reconciles semantic conflicts. We show the feasibility of this approach with a prototype that implements a subset of the proposed extensions

Addressing the Challenges of Aggregational and Temporal Ontological Heterogeneity

In this paper, we first identify semantic heterogeneities that, when not resolved, often cause serious data quality problems. We discuss the especially challenging problems of temporal and aggregational ontological heterogeneity, which concerns how complex entities and their relationships are aggregated and reinterpreted over time. Then we illustrate how the COntext INterchange (COIN) technology can be used to capture data semantics and reconcile semantic heterogeneities in a scalable manner, thereby improving data quality.Singapore-MIT Alliance (SMA

Improving National and Homeland Security through a proposed Laboratory for Information Globalization and Harmonization Technologies (LIGHT)

A recent National Research Council study found that: "Although there are many private and public databases that contain information potentially relevant to counter terrorism programs, they lack the necessary context definitions (i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and timely information" [NRC02, p.304, emphasis added] That sentence succinctly describes the objectives of this project. Improved access and use of information are essential to better identify and anticipate threats, protect against and respond to threats, and enhance national and homeland security (NHS), as well as other national priority areas, such as Economic Prosperity and a Vibrant Civil Society (ECS) and Advances in Science and Engineering (ASE). This project focuses on the creation and contributions of a Laboratory for Information Globalization and Harmonization Technologies (LIGHT) with two interrelated goals: (1) Theory and Technologies: To research, design, develop, test, and implement theory and technologies for improving the reliability, quality, and responsiveness of automated mechanisms for reasoning and resolving semantic differences that hinder the rapid and effective integration (int) of systems and data (dmc) across multiple autonomous sources, and the use of that information by public and private agencies involved in national and homeland security and the other national priority areas involving complex and interdependent social systems (soc). This work builds on our research on the COntext INterchange (COIN) project, which focused on the integration of diverse distributed heterogeneous information sources using ontologies, databases, context mediation algorithms, and wrapper technologies to overcome information representational conflicts. The COIN approach makes it substantially easier and more transparent for individual receivers (e.g., applications, users) to access and exploit distributed sources. Receivers specify their desired context to reduce ambiguities in the interpretation of information coming from heterogeneous sources. This approach significantly reduces the overhead involved in the integration of multiple sources, improves data quality, increases the speed of integration, and simplifies maintenance in an environment of changing source and receiver context - which will lead to an effective and novel distributed information grid infrastructure. This research also builds on our Global System for Sustainable Development (GSSD), an Internet platform for information generation, provision, and integration of multiple domains, regions, languages, and epistemologies relevant to international relations and national security. (2) National Priority Studies: To experiment with and test the developed theory and technologies on practical problems of data integration in national priority areas. Particular focus will be on national and homeland security, including data sources about conflict and war, modes of instability and threat, international and regional demographic, economic, and military statistics, money flows, and contextualizing terrorism defense and response. Although LIGHT will leverage the results of our successful prior research projects, this will be the first research effort to simultaneously and effectively address ontological and temporal information conflicts as well as dramatically enhance information quality. Addressing problems of national priorities in such rapidly changing complex environments requires extraction of observations from disparate sources, using different interpretations, at different points in times, for different purposes, with different biases, and for a wide range of different uses and users. This research will focus on integrating information both over individual domains and across multiple domains. Another innovation is the concept and implementation of Collaborative Domain Spaces (CDS), within which applications in a common domain can share, analyze, modify, and develop information. Applications also can span multiple domains via Linked CDSs. The PIs have considerable experience with these research areas and the organization and management of such large scale international and diverse research projects. The PIs come from three different Schools at MIT: Management, Engineering, and Humanities, Arts & Social Sciences. The faculty and graduate students come from about a dozen nationalities and diverse ethnic, racial, and religious backgrounds. The currently identified external collaborators come from over 20 different organizations and many different countries, industrial as well as developing. Specific efforts are proposed to engage even more women, underrepresented minorities, and persons with disabilities. The anticipated results apply to any complex domain that relies on heterogeneous distributed data to address and resolve compelling problems. This initiative is supported by international collaborators from (a) scientific and research institutions, (b) business and industry, and (c) national and international agencies. Research products include: a System for Harmonized Information Processing (SHIP), a software platform, and diverse applications in research and education which are anticipated to significantly impact the way complex organizations, and society in general, understand and manage critical challenges in NHS, ECS, and ASE

Improving National and Homeland Security through a proposed Laboratory for nformation Globalization and Harmonization Technologies (LIGHT)

A recent National Research Council study found that: "Although there are many private and public databases that contain information potentially relevant to counter terrorism programs, they lack the necessary context definitions (i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and timely information" [NRC02, p.304, emphasis added] That sentence succinctly describes the objectives of this project. Improved access and use of information are essential to better identify and anticipate threats, protect against and respond to threats, and enhance national and homeland security (NHS), as well as other national priority areas, such as Economic Prosperity and a Vibrant Civil Society (ECS) and Advances in Science and Engineering (ASE). This project focuses on the creation and contributions of a Laboratory for Information Globalization and Harmonization Technologies (LIGHT) with two interrelated goals: (1) Theory and Technologies: To research, design, develop, test, and implement theory and technologies for improving the reliability, quality, and responsiveness of automated mechanisms for reasoning and resolving semantic differences that hinder the rapid and effective integration (int) of systems and data (dmc) across multiple autonomous sources, and the use of that information by public and private agencies involved in national and homeland security and the other national priority areas involving complex and interdependent social systems (soc). This work builds on our research on the COntext INterchange (COIN) project, which focused on the integration of diverse distributed heterogeneous information sources using ontologies, databases, context mediation algorithms, and wrapper technologies to overcome information representational conflicts. The COIN approach makes it substantially easier and more transparent for individual receivers (e.g., applications, users) to access and exploit distributed sources. Receivers specify their desired context to reduce ambiguities in the interpretation of information coming from heterogeneous sources. This approach significantly reduces the overhead involved in the integration of multiple sources, improves data quality, increases the speed of integration, and simplifies maintenance in an environment of changing source and receiver context - which will lead to an effective and novel distributed information grid infrastructure. This research also builds on our Global System for Sustainable Development (GSSD), an Internet platform for information generation, provision, and integration of multiple domains, regions, languages, and epistemologies relevant to international relations and national security. (2) National Priority Studies: To experiment with and test the developed theory and technologies on practical problems of data integration in national priority areas. Particular focus will be on national and homeland security, including data sources about conflict and war, modes of instability and threat, international and regional demographic, economic, and military statistics, money flows, and contextualizing terrorism defense and response. Although LIGHT will leverage the results of our successful prior research projects, this will be the first research effort to simultaneously and effectively address ontological and temporal information conflicts as well as dramatically enhance information quality. Addressing problems of national priorities in such rapidly changing complex environments requires extraction of observations from disparate sources, using different interpretations, at different points in times, for different purposes, with different biases, and for a wide range of different uses and users. This research will focus on integrating information both over individual domains and across multiple domains. Another innovation is the concept and implementation of Collaborative Domain Spaces (CDS), within which applications in a common domain can share, analyze, modify, and develop information. Applications also can span multiple domains via Linked CDSs. The PIs have considerable experience with these research areas and the organization and management of such large scale international and diverse research projects. The PIs come from three different Schools at MIT: Management, Engineering, and Humanities, Arts & Social Sciences. The faculty and graduate students come from about a dozen nationalities and diverse ethnic, racial, and religious backgrounds. The currently identified external collaborators come from over 20 different organizations and many different countries, industrial as well as developing. Specific efforts are proposed to engage even more women, underrepresented minorities, and persons with disabilities. The anticipated results apply to any complex domain that relies on heterogeneous distributed data to address and resolve compelling problems. This initiative is supported by international collaborators from (a) scientific and research institutions, (b) business and industry, and (c) national and international agencies. Research products include: a System for Harmonized Information Processing (SHIP), a software platform, and diverse applications in research and education which are anticipated to significantly impact the way complex organizations, and society in general, understand and manage critical challenges in NHS, ECS, and ASE

A spatiotemporal information management framework for product design and assembly process planning reconciliation

This paper introduces an innovative framework for product design and assembly process planning reconciliation. Nowadays, both product lifecycle phases are quasi concurrently performed in industry and this configuration has led to competitive gains in efficiency and flexibility by improving designers’ awareness and product quality. Despite these efforts, some limitations/barriers are still encountered regarding the lack of dynamical representation, information consistency and information flow continuity. It is due to the inherent nature of the information created and managed in both phases and the lack of interoperability between the related information systems. Product design and assembly process planning phases actually generate heterogeneous information, since the first one describes all information related to ‘‘what to be delivered’’ and the latter rationalises all information with regards to ‘‘how to be assembled’’. In other words, the integration of assembly planning issue in product design requires reconciliation means with appropriate relationships of the architectural product definition in space with its assembly sequence in terms of time. Therefore, the main objective is to provide a spatiotemporal information management framework based on a strong semantic and logical foundation in product lifecycle management (PLM) systems, increasing therefore actors’ awareness, flexibility and efficiency with a better abstraction of the physical reality and appropriate information management procedures. A case study is presented to illustrate the relevance of the proposed framework and its hub-based implementation within PLM systems

Framework for the Analysis of the Adaptability, Extensibility, and Scalability of Semantic Information Integration and the Context Mediation Approach

Technological advances such as Service Oriented Architecture (SOA) have increased the feasibility and importance of effectively integrating information from an ever widening number of systems within and across enterprises. A key difficulty of achieving this goal comes from the pervasive heterogeneity in all levels of information systems. A robust solution to this problem needs to be adaptable, extensible, and scalable. In this paper, we identify the deficiencies of traditional semantic integration approaches. The COntext INterchange (COIN) approach overcomes these deficiencies by declaratively representing data semantics and using a mediator to create the necessary conversion programs from a small number of conversion rules. The capabilities of COIN is demonstrated using an example with 150 data sources, where COIN can automatically generate the over 22,000 conversion programs needed to enable semantic interoperability using only six parametizable conversion rules. This paper presents a framework for evaluating adaptability, extensibility, and scalability of semantic integration approaches. The application of the framework is demonstrated with a systematic evaluation of COIN and other commonly practiced approaches.This work has been supported, in part, by MITRE Corp., the MIT-MUST project, the Singapore-MIT Alliance, and Suruga Bank

Information Integration for Counter Terrorism Activities: The Requirement for Context Mediation

The National Research Council has noted that although there are many private and public databases that contain information potentially relevant to counterterrorism programs, they lack the necessary context definitions (i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and timely information. In this paper we present examples of these problems and a technology developed at MIT, called context mediation, which provides a novel approach for addressing these problems

Using Semantic Web technologies in the development of data warehouses: A systematic mapping

The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This study was supported by the Universidad de La Frontera, Chile, PROY. DI15-0020. Universidad de la Frontera, Chile, Grant Numbers: DI15-0020 and DI17-0043