Heterogeneous Data Resources Research Articles

Role-Based Access Control in a Data Grid Using the Storage Resource Broker and Shibboleth

In this paper, we propose a role-based access control (RBAC) system for data resources in the Storage Resource Broker (SRB). The SRB is a Data Grid management system, which can integrate heterogeneous data resources of virtual organizations (VOs). The SRB stores the access control information of individual users in the Metadata Catalog (MCAT) database. However, because of the specific MCAT schema structure, this information can only be used by the SRB applications. If VOs also have many non-SRB applications, each with its own storage format for user access control information, it creates a scalability problem with regard to administration. To solve this problem, we developed a RBAC system with Shibboleth, which is an attribute authorization service currently being used in many Grid environments. Thus, the administration overhead is reduced because the role privileges of individual users are now managed by Shibboleth, not by MCAT or applications. In addition, access control policies need to be specified and managed across multiple VOs. For the specification of access control policies, we used the Core and Hierarchical RBAC profile of the eXtensible Access Control Markup Language (XACML); and for distributed administration of those policies, we used the Object, Metadata and Artifacts Registry (OMAR). OMAR is based on the e-business eXtensible Markup Language (ebXML) registry specifications developed to achieve interoperable registries and repositories. Our RBAC system provides scalable and fine-grain access control and allows privacy protection. Performance analysis shows that our system adds only a small overhead to the existing security infrastructure of the SRB.

Semantic Web for Health Care and Life Sciences: a review of the state of the art

Semantic Web for Health Care and Life Sciences: a review of the state of the art

Vision of Cyberinfrastructure for End-to-End Environmental Explorations (C4E4)

Holistic approaches are needed for understanding and addressing a wide range of environmental issues that require multidis- ciplinary studies of complex and interlocking systems. The writers' vision of a cyberinfrastructure for end-to-end environmental explo- ration C4E4 that combines data and modeling tools in an integrated environment across different spatial and temporal scales is presented. The overall goal behind C4E4 is to enable a broad environmental research and remediation community to address the challenges of environmental data management and integration in real-world settings. The St. Joseph Watershed in northern Indiana is chosen as a test bed in this effort. The C4E4 framework will allow researchers to combine heterogeneous data resources with state-of- the-art modeling and visualization tools through a user-friendly web portal. By engaging TeraGrid resources, C4E4 will have the computational resources to store, manipulate, and query large data sets, thereby facilitating new science. C4E4 will serve as a prototype, and provide valuable experience for scaling up to larger observatories at the national level. This paper presents the writers' vision and goals, initial efforts, and briefly describes how C4E4 can benefit the environmental community.

A service-oriented system for distributed data querying and integration on Grids

Data Grids rely on the coordinated sharing of and interaction across multiple autonomous database management systems. They provide transparent access to heterogeneous and autonomous data resources stored on Grid nodes. Data sharing tools for Grids must include both distributed query processing and data integration functionality. This paper presents the implementation of a data sharing system that (i) is tailored to data Grids, (ii) supports well established and widely spread relational DBMSs, and (iii) adopts a hybrid architecture by relying on a peer model for query reformulation to retrieve semantically equivalent expressions, and on a wrapper-mediator integration model for accessing and querying distributed data sources. The system builds upon the infrastructure provided by the OGSA-DQP distributed query processor and the XMAP query reformulation algorithm. The paper discusses the implementation methodology, and presents empirical evaluation results.

Building biomedical web communities using a semantically aware content management system

Web-based biomedical communities are becoming an increasingly popular vehicle for sharing information amongst researchers and are fast gaining an online presence. However, information organization and exchange in such communities is usually unstructured, rendering interoperability between communities difficult. Furthermore, specialized software to create such communities at low cost-targeted at the specific common information requirements of biomedical researchers-has been largely lacking. At the same time, a growing number of biological knowledge bases and biomedical resources are being structured for the Semantic Web. Several groups are creating reference ontologies for the biomedical domain, actively publishing controlled vocabularies and making data available in Resource Description Framework (RDF) language. We have developed the Science Collaboration Framework (SCF) as a reusable platform for advanced structured online collaboration in biomedical research that leverages these ontologies and RDF resources. SCF supports structured 'Web 2.0' style community discourse amongst researchers, makes heterogeneous data resources available to the collaborating scientist, captures the semantics of the relationship among the resources and structures discourse around the resources. The first instance of the SCF framework is being used to create an open-access online community for stem cell research-StemBook (http://www.stembook.org). We believe that such a framework is required to achieve optimal productivity and leveraging of resources in interdisciplinary scientific research. We expect it to be particularly beneficial in highly interdisciplinary areas, such as neurodegenerative disease and neurorepair research, as well as having broad utility across the natural sciences.

Ontology-based information extraction and integration from heterogeneous data sources

In this paper we present the design, implementation and evaluation of SOBA, a system for ontology-based information extraction from heterogeneous data resources, including plain text, tables and image captions. SOBA is capable of processing structured information, text and image captions to extract information and integrate it into a coherent knowledge base. To establish coherence, SOBA interlinks the information extracted from different sources and detects duplicate information. The knowledge base produced by SOBA can then be used to query for information contained in the different sources in an integrated and seamless manner. Overall, this allows for advanced retrieval functionality by which questions can be answered precisely. A further distinguishing feature of the SOBA system is that it straightforwardly integrates deep and shallow natural language processing to increase robustness and accuracy. We discuss the implementation and application of the SOBA system within the SmartWeb multimodal dialog system. In addition, we present a thorough evaluation of the different components of the system. However, an end-to-end evaluation of the whole SmartWeb system is out of the scope of this paper and has been presented elsewhere by the SmartWeb consortium.

An ontology-based support for product conceptual design

The research presented in this paper is a follow-up of our prior work involving the development of a graphical modeling tool to support designers at the conceptual design stage. To close the loop for supporting designers in generating design concepts flexibly, fast, and easily, an ontology-based approach for knowledge management that works along with the graphical modeling tool is discussed. Ontology and databases for the tool are developed to promote the systematic capture of design knowledge and efficient reuse of the design knowledge selection. In order to locate the proper information and query the data from the databases, the relationship between the ontology and databases, the data analysis process, ontology enrichment, and the ontology-based query engine are built to offer users multiple design results according to users’ requirements. A tire design example is presented to demonstrate the proposed approach. The ontology-based method described in this paper can help retrieve and save the complex relations, support the reasoning, integrate heterogeneous data resources and offer users more accurate, proper and comprehensive data.

XML in Motion from Genome to Drug

Information technology (IT) has emerged as a central to the solution of contemporary genomics and drug discovery problems. Researchers involved in genomics, proteomics, transcriptional profiling, high throughput structure determination, and in other sub-disciplines of bioinformatics have direct impact on this IT revolution. As the full genome sequences of many species, data from structural genomics, micro-arrays, and proteomics became available, integration of these data to a common platform require sophisticated bioinformatics tools. Organizing these data into knowledgeable databases and developing appropriate software tools for analyzing the same are going to be major challenges. XML (eXtensible Markup Language) forms the backbone of biological data representation and exchange over the internet, enabling researchers to aggregate data from various heterogeneous data resources. The present article covers a comprehensive idea of the integration of XML on particular type of biological databases mainly dealing with sequence-structure-function relationship and its application towards drug discovery. This e-medical science approach should be applied to other scientific domains and the latest trend in semantic web applications is also highlighted.

XML in Motion from Genome to Drug

AbstractInformation technology (IT) has emerged as a central to the solution of contemporary genomics and drug discovery problems. Researchers involved in genomics, proteomics, transcriptional profiling, high throughput structure determination, and in other sub-disciplines of bioinformatics have direct impact on this IT revolution. As the full genome sequences of many species, data from structural genomics, micro-arrays, and proteomics became available, integration of these data to a common platform require sophisticated bioinformatics tools. Organizing these data into knowledgeable databases and developing appropriate software tools for analyzing the same are going to be major challenges. XML (eXtensible Markup Language) forms the backbone of biological data representation and exchange over the internet, enabling researchers to aggregate data from various heterogeneous data resources. The present article covers a comprehensive idea of the integration of XML on particular type of biological databases mainly dealing with sequence-structure-function relationship and its application towards drug discovery. This e-medical science approach should be applied to other scientific domains and the latest trend in semantic web applications is also highlighted.

Preface to the Special Issue on Grid Data Management

Initially developed for the scientific community, Grid computing is now breaking into other important fields such as enterprise information systems, thus making data management more critical than ever. New Grid applications are characterized with high heterogeneity, high autonomy and large-scale distribution of computing and data resources. Managing and transparently accessing large numbers of autonomous, heterogeneous data resources efficiently is an open problem. Furthermore, different Grids may have different requirements with respect to autonomy, query expressiveness, efficiency, quality of service, fault-tolerance, security, etc. Thus, different solutions need be investigated, ranging from extensions of distributed and parallel computing techniques to more decentralized, self-adaptive techniques such as Peer-to-peer (P2P). This special issue on Grid data management is based on papers selected from the International Workshop on High-Performance Data Management in Grid Environments (HPDGrid 2006), co-located with the VecPar Conference, July 13, 2006, Rio de Janeiro (http://vecpar.fe.up.pt/hpdg06). HPDGrid 2006 brought together researchers and practitioners from the high-performance computing, distributed systems and database communities to discuss the challenges and propose novel solutions in the design and implementation of data management in Grid environments. This special issue includes four papers which reflect the main discussions and results of the workshop. All four papers have been reviewed according to the rules of JOGC (the first paper was directly handled by the editor-in-chief). The first paper “Grid Data Management: open problems and new issues,” by Esther Pacitti, Patrick Valduriez and Marta Mattoso, is an introduction to the special issue, focusing on the main open problems and new issues related to Grid data management. First, it recalls the main principles behind data management in distributed systems and the basic techniques. Then, it makes precise the requirements for Grid data management and discusses the main techniques needed to address these requirements. This implies revisiting distributed database techniques in major ways, in particular, using P2P techniques. The second paper “Enterprise Grids: Challenges Ahead,” by Ricardo Jimenez-Peris, Marta PatinoMartinez and Bettina Kemme, discusses the use of Grid technology in enterprise computing where the Grid is viewed as a new architecture for data centers. The paper identifies the significant gap between what is required by enterprise Grids and what is currently J Grid Computing (2007) 5:271–272 DOI 10.1007/s10723-007-9078-4

Constraint-based brokering (CBB) for publishing and discovery of web services

Much effort is being made by the IT industry towards the development of a Web Service infrastructure to enable the discovery and sharing of heterogeneous applications and data resources. The existing implementation of Web Service registries does not have constraint specification and processing capabilities to achieve intelligent service discovery. In this work, we have extended the Web Service Description Language to allow service providers to specify their service constraints, and developed a Constraint-based Web Service Broker capable of matching a service requestor's requirement specification against providers' constraints to find their desired services. This paper presents the extended Web Service Description Language, the architecture and implementation of the Broker, the constraint matching technique, and the result of a performance evaluation.

Ontology-Based Query Division and Reformulation for Heterogeneous Information Integration

People can obtain information from heterogeneous data resources by semantic querying based on ontology. The difficult problem is how to reformulate a global query into multiple sub-queries over those local data bases. This paper presents a kind of uniform expression for queries of concept instances and a method in dividing the query expression into the local ones. All local query results can be integrated for the users' purposes. Using these methods to query integrated data resources, users can get right results they desire.

A global and parallel file system for grids

Data management is one of the most important problems in grid environments. Most of the efforts in data management in grids have been focused on data replication. Data replication is a practical and effective method to achieve efficient data access in grids. However all data replication schemes lack in providing a grid file system. One important challenge facing grid computing is the design of a grid file system. The Global Grid Forum defines a Grid File System as a human-readable resource namespace for management of heterogeneous distributed data resources, that can span across multiple autonomous administrative domains. This paper describes a new Grid File System according to the Global Grid Forum recommendations that integrates heterogeneous data storage resources in grids using standard grid technologies: GridFTP and the Resource Namespace Services, both defined by the Global Grid Forum. To obtain high performance, we apply the parallel I /O techniques used in traditional parallel file systems.

Biological SOAP servers and web services provided by the public sequence data bank.

A number of biological data resources (i.e. databases and data analytical tools) are searchable and usable on-line thanks to the internet and the World Wide Web (WWW) servers. The output from the web server is easy for us to browse. However, it is laborious and sometimes impossible for us to write a computer program that finds a useful data resource, sends a proper query and processes the output. It is a serious obstacle to the integration of distributed heterogeneous data resources. To solve the issue, we have implemented a SOAP (Simple Object Access Protocol) server and web services that provide a program-friendly interface. The web services are accessible at http://www.xml.nig.ac.jp/.

The UK e-Science Core Programme and the Grid

This paper describes the £120M UK ‘e-Science’ ( http://www.research-councils.ac.uk/ and http://www.escience-grid.org.uk) initiative and begins by defining what is meant by the term e-Science. The majority of the £120M, some £75M, is funding large-scale e-Science pilot projects in many areas of science and engineering. The infrastructure needed to support such projects must permit routine sharing of distributed and heterogeneous computational and data resources as well as supporting effective collaboration between groups of scientists. Such an infrastructure is commonly referred to as the Grid. Apart from £10M towards a Teraflop computer, the remaining funds, some £35M, constitute the e-Science ‘Core Programme’. The goal of this Core Programme is to advance the development of robust and generic Grid middleware in collaboration with industry. The key elements of the Core Programme will be outlined including details of a UK e-Science Grid testbed. The pilot e-Science projects that have so far been announced are then briefly described. These projects span a range of disciplines from particle physics and astronomy to engineering and healthcare, and illustrate the breadth of the UK e-Science Programme. In addition to these major e-Science projects, the Core Programme is funding a series of short-term e-Science demonstrators across a number of disciplines as well as projects in network traffic engineering and some international collaborative activities. We conclude with some remarks about the need to develop a data architecture for the Grid that will allow federated access to relational databases as well as flat files.

Architecture of a mediator for a bioinformatics database federation.

Developments in our ability to integrate and analyze data held in existing heterogeneous data resources can lead to an increase in our understanding of biological function at all levels. However, supporting ad hoc queries across multiple data resources and correlating data retrieved from these is still difficult. To address this, we are building a mediator based on the functional data model database, P/FDM, which integrates access to heterogeneous distributed biological databases. Our architecture makes use of the existing search capabilities and indexes of the underlying databases, without infringing on their autonomy. Central to our design philosophy is the use of schemas. We have adopted a federated architecture with a five-level schema, arising from the use of the ANSI-SPARC three-level schema to describe both the existing autonomous data resources and the mediator itself. We describe the use of mapping functions and list comprehensions in query splitting, producing execution plans, code generation, and result fusion. We give an example of cross-database querying involving data held locally in P/FDM systems and external data in SRS.

An integrated interactive environment for knowledge discovery from heterogeneous data resources

Discovering knowledge such as causal relations among objects in large data collections is very important in many decision-making processes. In this paper, we present our development of an integrated environment acting as a software agent for discovering correlative attributes of data objects from multiple heterogeneous resources. The environment provides necessary supporting tools and processing engines for acquiring, collecting, and extracting relevant information from multiple data resources, and then forming meaningful knowledge patterns. The agent system is featured with an interactive user interface that provides useful communication channels for human supervisors to actively engage in necessary consultation and guidance in the entire knowledge discovery processes. A cross-reference technique is employed for searching and discovering coherent set of correlative patterns from the heterogeneous data resources. A Bayesian network approach is applied as a knowledge representation scheme for recording and manipulating the discovered causal relations. The system employs common data warehousing and OLAP techniques to form integrated data repository and generate database queries over large data collections from various distinct data resources.

Deployment of personalized e-catalogues: An agent-based framework integrated with XML metadata and user models

In e-commerce applications, supporting electronic catalogues (e-catalogues) to provide product-search services on the Internet is emerging as an important function of electronic brokers (e-brokers). However, as the Internet expands, an increasing number of virtual stores are selling products on-line. The explosive growth of information is creating difficulties for customers searching for the product information they desire. In this work, an integrated framework is proposed to develop personalized e-catalogues. The proposed framework integrates XML-based metadata models, user models and agents. The XML-based metadata model can facilitate resource-discovery and format translation, and can flexibly model the definitions of diverse product attributes in heterogeneous data resources. The proposed user model can model a user’s shopping interests to resources, categories and products. This work integrates the agent technology with the proposed metadata model and user model to develop a personalized e-catalogue system. The novel system effectively provides an integrated search for heterogeneous product information, as well as supporting personalized product search and browsing for each user based upon their profiles.