Structural integration: Concepts and case study

When integrating the views of a large telecomunications application database at Bellcore, it was found that some pairs of view objects had significant structural similarities but differed semantically.⁺ This observation motivated the design of the structural integration methodology described in this article. Currently existing view and schema integration methodologies are based on semantic considerations. They allow integration only if two objects agree in their semantic and structural aspects. Structural integration permits the integration of objects even if they differ semantically. This article introduces structural integration for the case of full structural correspondence. We further develop an important special case, namely structural integration for classes with attribute partial correspondence. We use a subschema of the telecommunications application to demonstrate the applicability of structural integration to situations involving the complexities of real-world databases and applications. Algorithms for checking full structural correspondence of classes and databases are presented. Structural integration has several advantages, including the identification of shared common structures that are important for sharing of data and methods.This research has been supported partially by grants from the Center for Manufacturing Systems at New Jersey Institute of Technology and from Bellcore     

基于本体的Web数据语义集成体系结构的研究

目前在web环境下的异构数据集成研究,已经利用XML解决了结构的异构问题,但是未能有效解决语义的异构问题.引入本体提出利用本体解决语义异构的方法,给出一个本体驱动的web数据集成的体系结构,可以较好地解决语义异构问题.     

Building a global normalized ontology for integrating geographic data sources

Nowadays, the proliferation of geographic information systems has caused great interest in integration. However, an integration process is not as simple as joining several systems, since any effort at information sharing runs into the problem of semantic heterogeneity, which requires the identification and representation of all semantics useful in performing schema integration. On several research lines, including research on geographic information system integration, ontologies have been introduced to facilitate knowledge sharing among various agents. Particularly, one of the aspects of ontology sharing is performing some sort of mapping between ontology constructs. Further, some research suggests that we should also be able to combine ontologies where the product of this combination will be, at the very least, the intersection of the two given ontologies. However, few approaches built integrations upon standard and normalized information, which might improve accuracy of mappings and therefore commitment and understandability of the integration. In this work, we propose a novel system (called GeoMergeP) to integrate geographic sources by formalizing their information as normalized ontologies. Our integral merging process—including structural, syntactic and semantic aspects—assists users in finding the more suitable correspondences. The system has been empirically tested in the context of projects of the Italian Institute for Environmental Protection and Research (ISPRA, ex APAT), providing a consistent and complete integration of their sources.     

Model independent assertions for integration of heterogeneous schemas

Due to the proliferation of database applications, the integration of existing databases into a distributed or federated system is one of the major challenges in responding to enterprises' information requirements. Some proposed integration techniques aim at providing database administrators (DBAs) with a view definition language they can use to build the desired integrated schema. These techniques leave to the DBA the responsibility of appropriately restructuring schema elements from existing local schemas and of solving inter-schema conflicts. This paper investigates theassertion-based approach, in which the DBA's action is limited to pointing out corresponding elements in the schemas and to defining the nature of the correspondence in between. This methodology is capable of: ensuring better integration by taking into account additional semantic information (assertions about links); automatically solving structural conflicts; building the integrated schema without requiring conforming of initial schemas; applying integration rules to a variety of data models; and performing view as well as database integration. This paper presents the basic ideas underlying our approach and focuses on resolution of structural conflicts.     

基于知识库分割的多知识库整合方法

知识库是集团企业云制造平台中知识服务的重要基础,知识库的质量直接决定着知识服务的质量。目前单一分散的知识库不能提供统一的知识资源全局视图,不利于知识资源的共享。多知识库整合技术已经成为该领域的研究热点之一。提出一种基于知识库分割的多知识库整合方法,采用基于蚁群聚类的分割策略,将知识库有效划分为知识块集。在知识块间利用语义概念映射生成知识块间映射图,从而实现多知识库整合。通过对算法的时间复杂度进行分析,表明该方法在时间复杂度方面要优于基于最小概念集的多知识库整合方法;实验结果也表明该方法在运行性能方面明显优于已有的方法。     

aDApTA: Adaptive approach to information integration in dynamic environments

In complex environments, decision making process faces several challenges due to the dynamic of unpredicted events. There is a highly dynamic flow of information in a situation where most of the relevant data is heterogeneous, cannot be predicted and loaded previously. Even though many efforts have been made in data integration research, choosing the appropriate approach to an unknown (in advance) semantic level of information is still an open issue. The traditional relational data integration methods are not suitable to support complex environments due to the rigidity of their schema. As an alternative, Graph Data models can handle structural heterogeneity complemented by semantic representations like Linked Open Data on the Web. Based on these alternatives, this research proposes aDApTA, an adaptive approach to information integration and its associated architecture. An application example in a real scenario is presented. In this scenario, the logistics of relief goods are managed by a dynamic and multi-perspective view.     

A labeled-tree approach to semantic and structural data interoperability applied in hydrology domain

The issues of data integration and interoperability pose significant challenges in scientific hydrological and environmental studies, due largely to the inherent semantic and structural heterogeneities of massive datasets and non-uniform autonomous data sources. To address these data integration challenges, we propose a unified data integration framework, called Hydrological Integrated Data Environment (HIDE). HIDE is based on a labeled-tree data integration model referred to as DataNode tree. Using this framework, characteristics of datasets gathered from diverse data sources - with different logical and access organizations - can be extracted and classified as Time-Space-Attribute (TSA) labels and are subsequently arranged in a DataNode tree. The uniqueness of our approach is that it effectively combines the semantic aspects of the scientific domain with diverse datasets having different logical organizations to form a unified view. Further, we also adopt a metadata-based approach for specifying the TSA-DataNode tree in order to achieve flexibility and extensibility. The search engine of our HIDE prototype system evaluates a simple user query systematically on the TSA-DataNode tree, presenting integrated results in a standardized format that facilitates both effective and efficient data integration.     

闭环全生命周期管理系统中知识集成与语义标注

为了解决闭环全生命周期管理系统中知识相互独立、无法共享的问题,针对闭环全生命周期特点,提出了一种知识集成与语义标注方法。首先,简要阐述了闭环全生命周期管理系统中知识集成与语义标注的内涵;其次,利用本体技术对低温等离子体设备构建了多维度、多层次知识集成框架;然后,在此基础上,给出了知识文档语义标注流程,设计出一种文档语义向量与本体语义向量的提取与匹配计算方法,完成了低温等离子体设备中一个子系统的知识文档语义标注。设计测试实验并进行验证,实验结果表明,利用闭环全生命周期管理系统中的知识文档数据集进行语义标注,平均准确率达到84%,平均召回率达到79%。所提知识集成与语义标注方法可以实现知识文档在闭环全生命周期管理系统中的共享与重用。     

基于信息语义的异构信息集成方法

在系统集成的过程中，异构信息资源给人们信息共享、处理造成了困难，而异构信息中的语义表示方法一直是一个难点。该文采用基于信息语义的定义方法，提出一个以语义为核心的信息模型，给出异构信息系统集成的一种解决方法。     

一种面向领域WEB服务的数据中心模型

提出一种通用的面向领域WEB服务的数据中心模型.利用语义集成、数据映射、数据仓库及其他数据集成技术,不仅完成分布式异构数据源的无缝数据集成,而且实现数据源与数据中心之间的数据共享和透明数据交换,为领域WEB服务提供统一数据服务.在"油气生产系统软件集成平台"中采用该模型,组建了中国石油油气井生产领域数据中心,构建一个面向油气井生产领域,集生产管理、设备管理、工作流程控制、优化设计、故障诊断、辅助决策等功能为一体的WEB服务平台,解决了海量、分布式异构数据源的有机集成和无缝共享问题.从而验证了该模型的正确性及可行性.     

多尺度矢量简单几何实体数据几何匹配方法研究

数据匹配是空间数据整合及跨尺度数据更新的关键问题之一,其实质是识别出多尺度矢量空间数据中的同名地物,并建立彼此间的关联。数据匹配的技术手段包括语义与几何匹配两种,本文系统地阐述了几何匹配方法,提出了适用于多尺度矢量空间数据的三种匹配模式,可有效解决多尺度数据间点-点,线-线、线-面、点-面、面-面的几何匹配问题。     

Semantic Ontology Mapping for Interoperability of Learning Resource Systems using a rule-based reasoning approach

There is an increasing demand for sharing learning resources between existing learning resource systems to support reusability, exchangeability, and adaptability. The learning resources need to be annotated with ontologies into learning objects that use different metadata standards. These ontologies have introduced the problems of semantic and structural heterogeneity. This research proposes a Semantic Ontology Mapping for Interoperability of Learning Resource Systems. To enable semantic ontology mapping, this research proposes conflict detection and resolution techniques for both semantic and structural conflicts. The Semantic Bridge Ontology has been proposed as a core component for generating mapping rules to reconcile terms defined in local ontologies into terms defined in the target common ontology. This work defines the reasoning rules to classify related learning objects to enhance the powerful deductive reasoning capabilities of the system. As a consequence, ontology-based learning object metadata are generated and used by the semantic query engine to facilitate user queries of learning objects across heterogeneous learning resource systems.     

Learning to integrate web taxonomies

We investigate machine learning methods for automatically integrating objects from different taxonomies into a master taxonomy. This problem is not only currently pervasive on the Web, but is also important to the emerging Semantic Web. A straightforward approach to automating this process would be to build classifiers through machine learning and then use these classifiers to classify objects from the source taxonomies into categories of the master taxonomy. However, conventional machine learning algorithms totally ignore the availability of the source taxonomies. In fact, source and master taxonomies often have common categories under different names or other more complex semantic overlaps. We introduce two techniques that exploit the semantic overlap between the source and master taxonomies to build better classifiers for the master taxonomy. The first technique, Cluster Shrinkage, biases the learning algorithm against splitting source categories by making objects in the same category appear more similar to each other. The second technique, Co-Bootstrapping, tries to facilitate the exploitation of inter-taxonomy relationships by providing category indicator functions as additional features for the objects. Our experiments with real-world Web data show that these proposed add-on techniques can enhance various machine learning algorithms to achieve substantial improvements in performance for taxonomy integration.     

QUERY ROUTING IN A PEER-TO-PEER SEMANTIC LINK NETWORK

A semantic link peer-to-peer (P2P) network specifies and manages semantic relationships between peers' data schemas and can be used as the semantic layer of a scalable Knowledge Grid. The proposed approach consists of an automatic semantic link discovery method, a tool for building and maintaining P2P semantic link networks (P2PSLNs), a semantic-based peer similarity measurement for efficient query routing, and the schema mapping algorithms for query reformulation and heterogeneous data integration. The proposed approach has three important aspects. First, it uses semantic links to enrich the relationships between peers' data schemas. Second, it considers not only nodes but also the XML structure in measuring the similarity between schemas to efficiently and accurately forward queries to relevant peers. Third, it copes with semantic and structural heterogeneity and data inconsistency so that peers can exchange and translate heterogeneous information within a uniform view.     

BIM 和GIS 的空间语义数据集成方法及应用研究

随着数字城市和智慧城市的建设发展,建筑信息模型(BIM)和地理信息系统(GIS) 的集成被广泛研究和应用。目前的集成研究主要是通用数据标准IFC 和CityGML 之间的空间和 语义转换,但由于应用领域和空间尺度等差异,存在信息错误和丢失、几何语义信息耦合度低、 应用拓展性差等问题。为此提出了一种兼顾三维实体对象和地理空间对象的三维城市数据模型, 研究了BIM 和GIS 的空间和语义数据的提取、处理和转换方法,设计了BIM 和三维GIS 的集 成应用框架并在三维可视化平台上进行验证和初步应用。该方法可实现BIM和GIS 信息在几何、 语义、精度上的完全融合,避免了传统的数据转换带来的信息缺失,在多尺度的空间和语义信 息分级存储和加载显示方面存在着优势,有利于实现大规模、高精度的建筑和城市信息的高效 集成。     

An Ontology-Based Approach for Semantic Conflict Resolution in Database Integration

An important task in database integration is to resolve data conflicts, on both schema-level and semantic-level. Especially difficult the latter is. Some existing ontology-based approaches have been criticized for their lack of domain generality and semantic richness. With the aim to overcome these limitations, this paper introduces a systematic approach for detecting and resolving various semantic conflicts in heterogeneous databases, which includes two important parts： a semantic conflict representation model based on our classification framework of semantic conflicts, and a methodology for detecting and resolving semantic conflicts based on this model. The system has been developed, experimental evaluations on which indicate that this approach can resolve much of the semantic conflicts effectively, and keep independent of domains and integration patterns.     

制造网格中制造资源描述机制研究

为实现资源共享和协同工作,制造业对公共技术及服务平台的需求越来越强烈。将网格技术运用到制造业领域,提出了制造网格的概念。基于本体的知识集成方法,改变原有数据库集成中使用中间代理、软件接口等技术所造成的语义信息不清、信息丢失等缺陷,为企业实现制造资源共享和集成提供了解决方法和理论依据。     

新疆生产建设兵团水利信息化资源整合与共享

近年来新疆生产建设兵团水利信息化建设快速发展,但没有形成全面服务、有效支撑、共建共享、协同工作的局面,针对水利信息化应用信息孤岛、数据孤岛、业务割据的状况,兵团开展水利信息资源整合共享工作。结合兵团水利信息建设现状,资源整合与共享采用面向服务的 SOA 架构,基于 J2EE 平台设计、开发、 部署系统,采用 Spring,Struts,MVC 等技术实现异构资源集成,运用 Web Service 解决业务应用服务共享,以 WebGIS 技术提升地图和功能服务能力,解决兵团水利信息化整合中的关键技术和应用服务问题。已初步建成水利信息资源整合集成、业务协同与高效应用的共享服务平台,提升兵团水利信息应用保障能力和服务水平,提高水利行政管理效能,为类似的水利信息化整合共享提供解决方案。     

一种面向云制造的语义BOM知识集成框架

为克服传统BOM信息集成中存在语义知识集成的缺陷, 支持BOM知识在云制造企业间无缝传递、共享和重用, 提出一种面向云制造的语义BOM知识集成框架。该集成框架由语义BOM知识表示、知识映射、知识服务三个模块构成。知识表示模块融合本体论, 用owl DL进行语义BOM的形式化知识表示, 构建语义BOM知识本体模型; 知识映射模块基于语义BOM多视图映射方法, 形成云制造企业所需语义BOM视图; 知识服务模块以Web service为媒介, 将各语义BOM视图封装成知识服务, 通过服务注册、绑定、发现、组合等手段, 实现BOM知识的共享和重用。该框架能支持云制造企业按需在知识重用基础上快速重构BOM知识模型。     

基于语义Web的网络化制造信息集成的研究

分析了当前网络化制造环境下企业资源共享和信息集成的现状及存在问题,结合语义Web技术,提出了网络化制造环境下企业资源信息集成平台的体系结构,为企业资源在语义层及企业本体上的集成提供了实现方式,并将体系结构应用于有色金属行业中,通过实际应用验证了系统的可靠性和稳定性.