The Experts below are selected from a list of 132 Experts worldwide ranked by ideXlab platform

Michael J Carey - One of the best experts on this subject based on the ideXlab platform.

  • enterprise information integration successes challenges and controversies
    International Conference on Management of Data, 2005
    Co-Authors: Alon Halevy, Michael J Carey, Naveen Ashish, Dina Bitton, Denise L Draper, Jeff Pollock, Arnon Rosenthal, Vishal Sikka
    Abstract:

    The goal of EII systems is to provide uniform access to multiple data sources without having to first load them into a data warehouse. Since the late 1990's, several EII products have appeared in the marketplace and significant experience has been accumulated from fielding such systems. This collection of articles, by individuals who were involved in this industry in various ways, describes some of these experiences and points to the challenges ahead.

  • bea liquid data for weblogic xml based enterprise information integration
    International Conference on Data Engineering, 2004
    Co-Authors: Michael J Carey
    Abstract:

    This presentation provides a technical overview of BEA Liquid Data for WebLogic, a relatively new product from BEA Systems that provides enterprise information integration capabilities to enterprise applications that are built and deployed using the BEA WebLogic Platform. Liquid Data takes an XML-centric approach to tackling the long-standing problem of integrating data from disparate data sources and making that information easily accessible to applications. In particular, Liquid Data uses the forthcoming XQuery language standard as the basis for defining integrated views of enterprise data and querying over those views. We provide a brief overview of the Liquid Data product architecture and then discuss some of the query processing technology that lies at the heart of the product.

  • enterprise information integration xml to the rescue
    International Conference on Conceptual Modeling, 2003
    Co-Authors: Michael J Carey
    Abstract:

    The database field has been struggling with the data integration problem since the early 1980’s. We’ve named and renamed the problem – heterogeneous distributed databases, multi-databases, federated databases, mediator systems, and now enterprise information integration systems – but we haven’t actually solved the problem. Along the way, we’ve tried data model after data model– functional, relational, object-oriented, logical, semi-structured, you name it, we’ve tried it – and query language after query language to go with them – but we still haven’t solved the problem. A number of startups have died trying, and no major software vendor has managed to hit a home run in this area. What’s going on? Is the problem too hard? Should we just declare it impossible and give up?

Bijoy Majumdar - One of the best experts on this subject based on the ideXlab platform.

  • semantic web services in action enterprise information integration
    International Conference on Service Oriented Computing, 2007
    Co-Authors: Parachuri Deepti, Bijoy Majumdar
    Abstract:

    With the development and maturity of Service Oriented Architectures (SOA) to support business-to-business transactions, enterprises are using Web services to expose the public functionalities associated with internal systems and business processes. Semantic Web service infrastructure achieves automatic data integration to enable enterprises to collaborate and compete effectively in a dynamic global environment. In this paper, we deal with two important aspects of enterprise information integration, namely process integration and data convergence. This paper talks about solution strategies for global enterprise system which provides unified information and agile solution with greater ease and simplicity. Today's Web data lacks machine understandable semantics making it impossible to achieve data integration with the Web service. Hence, the semantic Web services in action to overcome the limitations of information finding, information extracting, information representing, information interpreting and information maintaining. This paper takes you through a case study simulating semantic Web paradigm (and semantic Web services) over a leasing business system. It also portrays the various advantages and explains the hurdles in accepting the semantic Web technology.

Mingwei Wang - One of the best experts on this subject based on the ideXlab platform.

  • a review of enterprise information integration from content level and system level perspectives
    International Journal of Advancements in Computing Technology, 2010
    Co-Authors: Jingtao Zhou, Haicheng Yang, Mingwei Wang, Rongxia Zhang, Min Shi
    Abstract:

    To gain insight into increasingly intricate business, and deal with highly complex problem situations, an enterprise needs a more generic, standardized, pervasive and scalable infrastructure to fully leverage the information from different data sources, applications, and environments at both system level and content level. Based on a discussion of basic problem of EII (enterprise information integration), this paper reviews a state of the art of existing enterprise information integration solutions from content level integration and system level integration perspectives. We evaluate existing approaches to content level integration by comparing the method used to describe and explain the data, and the topology structure of the data connected. We evaluate existing approaches to system level integration by in-depth discussion how the systems are coupled. Based on the results of our analysis we summarize the state-of-the-art in enterprise information integration and give the tendencies of further research.

  • a survey of semantic enterprise information integration
    International Conference on Information Sciences and Interaction Sciences, 2010
    Co-Authors: Jingtao Zhou, Haicheng Yang, Mingwei Wang, Rongxia Zhang, Tao Yue, Shusheng Zhang
    Abstract:

    Based on a discussion of data understanding hierarchy, this paper reviews a state of the art of existing enterprise information integration solutions from semantic perspective. We divide existing approaches into three categories: programming semantic-based integration, syntax schema-based integration, and declarative semantic-based integration, and evaluate the approaches in each category by comparing the method used to describe and explain the data, and the topology structure of the data connected. Based on the results of our analysis we summarize the state-of-the-art in semantic enterprise information integration and give the tendencies of further research.

  • enterprise information integration state of the art and technical challenges
    International Conference on Programming Languages for Manufacturing, 2006
    Co-Authors: Jingtao Zhou, Mingwei Wang, Han Zhao
    Abstract:

    To gain insight into increasingly intricate business, and deal with highly complex problem situations, an enterprise needs a more generic, standardized, pervasive and scalable infrastructure to fully leverage the information from different data sources, applications, and environments at both system and semantic level. In this context, we first discuss the state of the art of current approaches and solutions of EII (enterprise information integration). Then, we outline the grand challenges of EII from technical perspective based on the analysis of framework, range, scale and performance.

  • semantic integration of enterprise information challenges and basic principles
    Lecture Notes in Computer Science, 2006
    Co-Authors: Jingtao Zhou, Mingwei Wang
    Abstract:

    To overcome the challenges of EII (enterprise information integration), we propose SGII which is the first system undertaking research at the intersection of semantic grid and P2P data integration, exploiting their strengths in a common framework, and expanding their applicability in the area of EII. We first discuss how the P2P and semantic grid technologies can drive current EII systems to a new decentralized, flexible, scalable system based on a short survey of the state of the art of EII and its current challenges. Then, through a discussion of the fundamental formal architecture in general and its components in particular, we depict the basic integration principles from both P2P and semantic grid perspectives. The key contributions of this paper are a P2P semantic grid service oriented framework for EII, which mainly consists of three semantic grid services (data peer, semantic peer and application peer services); basic integration principles, which is compatible with OGSA-DAI infrastructure and P2P data integration paradigm; and added value over the state of the art of Ell.

  • sgii towards semantic grid based enterprise information integration
    Grid and Cooperative Computing, 2005
    Co-Authors: Jingtao Zhou, Shusheng Zhang, Han Zhao, Mingwei Wang
    Abstract:

    To fully leverage the information from different data sources and applications, an enterprise needs a generic, interoperable and flexible infrastructure to integrate and coordinate information across back-end data sources on semantic level. Through undertaking research at the intersection of the Semantic Web and Grid, the Semantic Grid expects to establish a semantic interconnection environment to effectively organize, share, cluster, fuse, and manage globally distributed versatile resources. In this context, we introduce SGII, an EII (enterprise information integration) infrastructure based on Semantic Grid vision to achieve adaptive and intelligence information sharing. A survey of existent solutions is made to provide evidence of the benefits from Semantic Grid in the context of integration and interoperation of enterprise information. A primary architecture for SGII is introduced based on the analysis of realizing the vision of an infrastructure for semantic information integration on grid.

Juan F Sequeda - One of the best experts on this subject based on the ideXlab platform.

  • semantic web based container monitoring system for the transportation industry
    International Semantic Web Conference, 2014
    Co-Authors: Pinar Gocebe, Oguz Dikenelli, Umut Kose, Juan F Sequeda
    Abstract:

    Goods are transported around the world in containers. Monitoring containers is a complex task. In this presentation, we will present a Container Monitoring System based on Semantic Web technologies. This system is currently being developed by Ege University, Bimar information Technology Services and Capsenta for ARKAS Holding, one of Turkey’s leading logistics and transportation companies. Our presentation consists of 1) introducing the challenges of monitoring containers in the transportation industry, 2) how existing technologies and solutions do not satisfy the needs, 3) why Semantic Web technologies can address the needs, 4) how we are using Semantic Web technologies including architectural design decisions and finally 5) describe lessons learned. Problem: Monitoring Containers in the Transportation Industry Logistics and Transportation Industry works as a complex system where different databases interact with each other dynamically. ARKAS Holding is one of Turkey's leading logistics and transportation companies. It operates in different fields such as sea, land, rail, air transportation, ship operations and port operations. The objective is to transport a container from a start location to an end location. One of the most important problems is monitoring containers. Each step of the container transportation process may be performed by a different company. Therefore, monitoring the container's lifecycle in real time is a challenging engineering task because these processes runs in parallel on different software systems. The end goal is to have managers and customers be able to track the container transportation process. Why Semantic Web technologies? In the last decade, Electronic Data Interchange (EDI) based standards (EDIFACT, RosettaNet, STEP, AnsiX12), XML standards and Service Oriented Architecture (SOA) approaches are used for solving the integration problems of logistics and transportation industry [1]. The standards provide common syntax for data representation and SOA provides an application integration infrastructure. However, these technologies are not sufficient to ultimately solve the integration challenges in large enterprise for the following reasons: ● In EDI-based standards, EDI messages are pushed among the organizations on a predefined time and these standards are not suitable for real-time applications [2]. ● In the SOA approaches, the most important problem is interoperability[3]. Unique identifiers in a database, are understood inside of a system but they may lose their meaning in another system. Finding the operation of a web service that will be called by an identifier is fixed in the software application logic. The resulting application logic is elaborate when considering the complexity of the logistics and transportation industry. In the recent years, Semantic Web standards and infrastructure are prevalently used to integrate enterprise information and business processes [4]. Semantic Web provides an integration environment which is more flexible, extensible and open to the exterior when necessary. The same identifiers (URIs) can be used across different data sources creating then a huge knowledge base. Software systems can use this knowledge base independently from each other. Semantic Web technologies decreases the dependence on the middle-tier technologies whose management is hard; so maintenance and management processes are become easier. For all these reasons, Semantic Web technologies comprises a new solution to the dynamic, distributed and complex nature of the logistics and transportation industry. In ARKAS, there are approximately 200 active integration projects being carried out domestically and internationally. Development cost of a new integration between operational systems to supply tracking data each other is ~25-30% and maintenance cost is ~10-15% of the total project cost. The integration of a new database is performed in approximately one month because of the data format identification and transformation process between the different technologies that are being used. The Project Ege University, Bimar information Technology Services and Capsenta are working together to develop a container monitoring system based on Semantic Web technologies 1 . The goal of using Semantic Web technologies is to decrease the cost of integration and dependencies between software systems. The first phase consists of integrating four internal relational databases of ARKAS on ports, agencies, land transport and warehouses. The second phase consists of integrating external relational databases from third-party companies such as a warehouse and land transportation companies. We are currently near the end of the first phase. How we use Semantic Web technologies In order to address the problem, we use a hybrid architecture consisting of a combination of Extract-Transform-Load (ETL), Wrapper, Warehouse and Federation. We have created OWL ontologies that describe ports, agencies and warehouses and R2RML mappings between the relational databases and the ontologies. ARKAS’ internal databases are ETLed to RDF using Capsenta’s Ultrawrap and warehoused in an RDF triplestore. The goal of having a centralized RDF triplestore is to have full control of the data in a single repository and perform analytics over the integrated data. External data sources are integrated into the system in a distributed manner. External relational databases are wrapped with Ultrawrap in order to provide a virtual RDF view. A query federator is used to integrate the external sources with the internal sources. A wrapper is ideal for the external sources because third-party companies are not willing to give up their data. In order to keep updates to the underlying relational databases consistent with the RDF data in the triplestore, we use data capture systems for relational databases. Current Lessons Learned ● Given the complexity of the transportation domain, creating ontologies for this domain is not straightforward. Existing ontologies do not satisfy our use case. ● Creation of R2RML mappings involves a domain expert and an ontology engineer. For example, it took 15 days to create the mappings for the port database. ● Deciding on the appropriate architecture according to the requirements is a complex process. ● Creating a simple core ontology and mapping it with suitable R2RML patterns are important tasks to provide a scalable architecture. ● Ongoing work is testing the scalability of the systems as a result of integrating new databases. References [1] Nurmilaakso, J.-M.: Adoption of e-business functions and migration from EDI-based to XMLbased e-business frameworks in supply chain integration. International Journal of Production Economics 113(2), 721-733 (2008) [2] Harleman, R. 2012. Improving the Logistic Sectors Efficiency using Service Oriented Architectures (SOA). In 17th Twente Student Conference on IT (2012) [3] The European Interoperability Framework, http://ec.europa.eu/isa/documents/isa_annex_ii_eif_en.pdf (2010) [4] Frischmuth, P., Klimek, J., Auer, S., Tramp, S., Unbehauen, J., Holzweisig, K., Marquardt, C.-M.: Linked Data in enterprise information integration. Semantic Web – Interoperability, Usability, Applicability. IOS Press Journal (2012) 1 This project is funded by the Republic of Turkey Ministry of Science, Industry and Technology.

Jingtao Zhou - One of the best experts on this subject based on the ideXlab platform.

  • a review of enterprise information integration from content level and system level perspectives
    International Journal of Advancements in Computing Technology, 2010
    Co-Authors: Jingtao Zhou, Haicheng Yang, Mingwei Wang, Rongxia Zhang, Min Shi
    Abstract:

    To gain insight into increasingly intricate business, and deal with highly complex problem situations, an enterprise needs a more generic, standardized, pervasive and scalable infrastructure to fully leverage the information from different data sources, applications, and environments at both system level and content level. Based on a discussion of basic problem of EII (enterprise information integration), this paper reviews a state of the art of existing enterprise information integration solutions from content level integration and system level integration perspectives. We evaluate existing approaches to content level integration by comparing the method used to describe and explain the data, and the topology structure of the data connected. We evaluate existing approaches to system level integration by in-depth discussion how the systems are coupled. Based on the results of our analysis we summarize the state-of-the-art in enterprise information integration and give the tendencies of further research.

  • a survey of semantic enterprise information integration
    International Conference on Information Sciences and Interaction Sciences, 2010
    Co-Authors: Jingtao Zhou, Haicheng Yang, Mingwei Wang, Rongxia Zhang, Tao Yue, Shusheng Zhang
    Abstract:

    Based on a discussion of data understanding hierarchy, this paper reviews a state of the art of existing enterprise information integration solutions from semantic perspective. We divide existing approaches into three categories: programming semantic-based integration, syntax schema-based integration, and declarative semantic-based integration, and evaluate the approaches in each category by comparing the method used to describe and explain the data, and the topology structure of the data connected. Based on the results of our analysis we summarize the state-of-the-art in semantic enterprise information integration and give the tendencies of further research.

  • enterprise information integration state of the art and technical challenges
    International Conference on Programming Languages for Manufacturing, 2006
    Co-Authors: Jingtao Zhou, Mingwei Wang, Han Zhao
    Abstract:

    To gain insight into increasingly intricate business, and deal with highly complex problem situations, an enterprise needs a more generic, standardized, pervasive and scalable infrastructure to fully leverage the information from different data sources, applications, and environments at both system and semantic level. In this context, we first discuss the state of the art of current approaches and solutions of EII (enterprise information integration). Then, we outline the grand challenges of EII from technical perspective based on the analysis of framework, range, scale and performance.

  • semantic integration of enterprise information challenges and basic principles
    Lecture Notes in Computer Science, 2006
    Co-Authors: Jingtao Zhou, Mingwei Wang
    Abstract:

    To overcome the challenges of EII (enterprise information integration), we propose SGII which is the first system undertaking research at the intersection of semantic grid and P2P data integration, exploiting their strengths in a common framework, and expanding their applicability in the area of EII. We first discuss how the P2P and semantic grid technologies can drive current EII systems to a new decentralized, flexible, scalable system based on a short survey of the state of the art of EII and its current challenges. Then, through a discussion of the fundamental formal architecture in general and its components in particular, we depict the basic integration principles from both P2P and semantic grid perspectives. The key contributions of this paper are a P2P semantic grid service oriented framework for EII, which mainly consists of three semantic grid services (data peer, semantic peer and application peer services); basic integration principles, which is compatible with OGSA-DAI infrastructure and P2P data integration paradigm; and added value over the state of the art of Ell.

  • sgii towards semantic grid based enterprise information integration
    Grid and Cooperative Computing, 2005
    Co-Authors: Jingtao Zhou, Shusheng Zhang, Han Zhao, Mingwei Wang
    Abstract:

    To fully leverage the information from different data sources and applications, an enterprise needs a generic, interoperable and flexible infrastructure to integrate and coordinate information across back-end data sources on semantic level. Through undertaking research at the intersection of the Semantic Web and Grid, the Semantic Grid expects to establish a semantic interconnection environment to effectively organize, share, cluster, fuse, and manage globally distributed versatile resources. In this context, we introduce SGII, an EII (enterprise information integration) infrastructure based on Semantic Grid vision to achieve adaptive and intelligence information sharing. A survey of existent solutions is made to provide evidence of the benefits from Semantic Grid in the context of integration and interoperation of enterprise information. A primary architecture for SGII is introduced based on the analysis of realizing the vision of an infrastructure for semantic information integration on grid.