Knowledge Grid Research Articles

A Resourceomic Grid for bioinformatics

In this work we revise the layered software architecture for the Knowledge Grid by explicitly introducing the concept of Resourceome, i.e. an “alive” ontology of resources. This approach is necessary to tackle the challenges posed by the “ome” status, reached by the world of bioinformatics resources. The resulting software architecture, a Resourceomic Grid, integrates components to support issues like awareness, discovery, integration and abstraction of resources.

Inter‐organisational intrusion detection using knowledge grid technology

PurposeThis paper introduces a solution for employing intrusion detection technology across organisational boundaries by using knowledge grid technology.Design/methodology/approachEmployment of intrusion detection technology is currently limited to inside organisation deployments. By setting up communities, which maintain trust relationships between network nodes anywhere in the internet, security event data, structured into a common XML‐based format, can be exchanged in a secure and reliable manner.FindingsA modular architecture has been developed which provides functionality to integrate different audit data generating applications and share knowledge about incidents, vulnerabilities and countermeasures from all over the internet. A security policy, based on the Chinese Wall Security Policy, ensures the protection of information inserted into the network.Research limitations/implicationsThe solution is currently in a preliminary stage, providing the description of the design only. Implementation as well as evaluation is under development.Practical implicationsTrusting communities everywhere in the internet will be brought into being so that people may establish trust relationships between each other. Participants may decide themselves whom they trust as a source for security‐related information rather than depending on centralised approaches.Originality/valueNo approach is known combining the two technologies – intrusion detection and grid – as described in this paper. The decentralised, peer‐to‐peer based grid approach together with the introduction of trust relationships and communities results in a new way of thinking about distributing security audit data.

Distributed data mining services leveraging WSRF

The continuous increase of data volumes available from many sources raises new challenges for their effective understanding. Knowledge discovery in large data repositories involves processes and activities that are computationally intensive, collaborative, and distributed in nature. The Grid is a profitable infrastructure that can be effectively exploited for handling distributed data mining and knowledge discovery. To achieve this goal, advanced software tools and services are needed to support the development of KDD applications. The Knowledge Grid is a high-level framework providing Grid-based knowledge discovery tools and services. Such services allow users to create and manage complex knowledge discovery applications that integrate data sources and data mining tools provided as distributed services on the Grid. All of these services are currently being re-designed and re-implemented as WSRF-compliant Grid Services. This paper highlights design aspects and implementation choices involved in such a process.

Semantic component networking: Toward the synergy of static reuse and dynamic clustering of resources in the knowledge grid

Model is a kind of codified knowledge that has been verified in solving problems. Solving a complex problem usually needs a set of models. Using components, the composition of a set of closely related models, could enhance the efficiency of solving problems as components are experience in form of knowledge network. Mappings between components vary with the relevancy of problems. Such mappings can help retrieve appropriate components when solving new problems. This paper investigates the relationship between components to identify these mappings by a set of semantic links and develops relevant rules to form a mechanism for semantically networking and using components. Flexible component reuse can be realized by semantic retrieval and rule reasoning. Extending the notion of component to a general service mechanism, this paper further investigates the organization, reuse and clustering of components in form of Web services and research spaces. The semantic component networking overlay supports intelligent e-Science Knowledge Grid applications by the synergy of static reuse and dynamic clustering of various research spaces and resources on-demand.

Tacit to explicit: an interplay shaping organization knowledge

PurposeAims to study the role tacit knowledge plays in shaping the knowledge base of the knowledge‐intensive growing organizations using the storytelling method.Design/methodology/approachStories were collected from eight human resource professionals working in eight different knowledge‐intensive growing organizations in New Zealand. Interviews containing loosely structured questions were used for collecting stories. These stories were deconstructed on the knowledge grid. This grid attempted to depict a complex interplay of tacit knowledge with the important subsystems (referred to as threads) of organization.FindingsTacit knowledge seemed to be a major concern for the human resource professionals in knowledge‐intensive growing organizations. It plays a significant role in shaping the knowledge base of an organization by interacting with the important subsystems of organization.Research limitations/implicationsThere is a need to study ways of reducing the risk of being dependent on tacit knowledge of a few employees. Technology is needed that would be able to effectively capture the multidimensional interplay of tacit knowledge with important subsystems of organization.Practical implicationsKnowledge being a strategic input in knowledge‐intensive growing organizations, there is a need to address major concerns related to tacit knowledge that these organizations specifically face due to their knowledge‐intensive nature.Originality/valueTacit knowledge interacts with the important subsystems of an organization, thereby shaping its knowledge base. This paper attempts to demonstrate that tacit knowledge operates in multidimensional contexts.

Discovery of knowledge flow in science

Recognizing and understanding knowledge flow between scientists is valuable for science. Discovering, managing, and utilizing such knowledge are advanced services of the e-science knowledge grid environment.

Data mining ontology development for high user usability

This paper mainly introduces the development and implementation of the user-centered data mining service ontology on Universal Knowledge Grid (UKG), UKG is an ontology-based grid architecture model to build large-scale distributed knowledge discovery system on the grid. The data mining ontology services are the main service offering by UKG. It can meet the user requirements of knowledge discovery in different domains and different hierarchies and make the system exoteric, extensible and high usable. A data mining solution for money laundering is introduced.

A scalable P2P platform for the knowledge grid

The knowledge grid needs to operate with a scalable platform to provide large-scale intelligent services. A key function of such a platform is to efficiently support various complex queries in a dynamic large-scale network environment. This paper proposes a platform to support index-based path queries by incorporating a semantic overlay with an underlying structured P2P network that provides object location and management services. Various distributed indexing structures can be dynamically formed by publishing, semantic objects as indexing nodes. Queries are forwarded along the chains of semantic object pointers to search for objects. We investigate the deployment of a scalable distributed trie index for broadcast queries on key strings, propose a decentralized load balancing method for solving the problem of uneven load distribution incurred by heterogeneity of loads and node capacities and by the distributed trie index, and give an approach for improving the availability of the semantic overlay and its trie index. Experiments demonstrate the scalability of the proposed platform.

Automatic generation of document semantics for the e-science Knowledge Grid

This paper proposes an approach to automatically generate semantics for scientific e-documents, and presents its applications in e-document understanding, question answering and question refinement. The approach uses not only keywords and their relations in e-documents, but also the implied meaning of co-occurred keywords that is hard to be exploited, represented and derived by previous semantic representation approaches. The proposed approach facilitates automatic construction, composition, decomposition and derivation of semantics at different granularity levels, which lay the basis for realizing intelligent services of the e-science Knowledge Grid.

A Collaborative Informatics Infrastructure for Multi-Scale Science

The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information in support of systems-based research and is applying it within combustion science. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.

Learning with an active e‐course in the Knowledge Grid environment

AbstractAn active e‐course is an open, self‐representable and self‐organizable media mechanism. Its kernel idea is to organize learning materials in a concept space rather than in a page space. The tailored content and flexible structure of the e‐courses can be dynamically formed to cater for different learners with different backgrounds, capabilities and expectations, at different times and venues. The active e‐course can also assess learners' learning performances and give appropriate suggestions to guide them in further learning. An authoring tool for constructing course ontology and a system prototype have been developed to support an active e‐course, enabling a learner‐centred, highly interactive and adaptive learning approach. The results of an empirical study show that the system can help enhance the effectiveness and efficiency of learning. Copyright © 2005 John Wiley & Sons, Ltd.

The Knowled ge Grid

The Knowled ge Grid

Assessment of eco-security in the Knowledge Grid e-science environment

Ecological security is an important basis of the entire human security system, the cornerstone for human survival. Knowing the status of ecological security is crucial for making decisions to avoid ecological disaster. Existing research, both the basic research on ecological security mechanism and information service systems, is still primitive in their abilities to resolve eco-security problems. This paper investigates the eco-security impact factors and identifies eco-security types. Taking urban eco-security as an example, we develop an assessment method including the indicator system and assessment model, and construct an integrated assessment framework based on data integrity, security assessment and security management with the support of the Knowledge Grid e-science environment. The proposed assessment framework enables decision makers to better know the status of eco-security in making policies for achieving sustainability.

Knowledge Map: Mathematical Model and Dynamic Behaviors

Knowledge representation and reasoning is a key issue of the Knowledge Grid. This paper proposes a Knowledge Map (KM) model for representing and reasoning causal knowledge as an overlay in the Knowledge Grid. It extends Fuzzy Cognitive Maps (FCMs) to represent and reason not only simple cause-effect relations, but also time-delay causal relations, conditional probabilistic causal relations and sequential relations. The mathematical model and dynamic behaviors of KM are presented. Experiments show that, under certain conditions, the dynamic behaviors of KM can translate between different states. Knowing this condition, experts can control or modify the constructed KM while its dynamic behaviors do not accord with their expectation. Simulations and applications show that KM is more powerful and natural than FCM in emulating real world.

Future interconnection environment

The emergence of the Web provided an unprecedented AI research and application platform. By providing access to human-readable content stored in any computer connected to the Internet, it revolutionized business, scientific research, government, and public information services around the globe. Networks pervade nature, society, and virtual worlds, giving structure and function to a variety of resources and behaviors. Discovering the rules that govern the future interconnection environment is a major challenge. The China Knowledge Grid Research Group, is exploring the operating principles of this future interconnection environment.

BUILDING A DATA‐MINING GRID FOR MULTIPLE HUMAN BRAIN DATA ANALYSIS

E‐science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain‐informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data‐mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long‐term, global field of vision.

XML DECLARATIVE DESCRIPTION WITH FIRST‐ORDER LOGICAL CONSTRAINTS

The expressive power of XML Declarative Description (XDD), a unified XML‐based representation language for the Knowledge Grid, is enhanced by a well‐defined mechanism for modeling arbitrary XML first‐order logical constraints (FLCs)—a special kind of constraints comprising XML expressions and logical symbols. The resulting knowledge representation can uniformly express explicit and implicit information, ontologies, axioms as well as integrity, structural and FLCs. It facilitates direct use of ordinary XML elements as its basic language component and semantic units, and formally defines XML clauses for modeling advanced complex statements. It achieves sound, efficient, and flexible computation or inference by means of the Equivalent Transformation (ET) paradigm—a new computational model based on semantic preserving transformations. Basic ET computational rules for reasoning with XDD descriptions with FLCs are also presented. Due to its well‐founded mechanism and expressiveness, employment of the proposed representation and computation framework to model a knowledge grid and its services not only enables direct representation of knowledge bases described by such emerging Semantic Web ontology languages as RDF(S) and OWL, but also offers additional descriptive facilities by allowing expression of and reasoning with rules, relationships, and constraints. Moreover, in order to provide machine‐interpretable descriptions of knowledge grid services, standard service description languages, e.g., WSDL, UDDI, OWL‐S and WSMO are employed and extended with facilities to define additional service relationships, constraints, and composition rules.

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.

Towards Context-Aware Knowledge Management in e-Enterprises

To reduce the negative impact of knowledge loss and to improve knowledge reuse effectiveness in knowledge management in e-Enterprises, this paper presents a context-aware approach to facilitate managing various types of static enterprise information and dynamic process information. Proposed approach features representing and integrating information at different conceptual levels to present contextual knowledge in an open environment. In this paper, we redefine the concept of context in intelligent systems and propose a set of meta-information elements for context description in business environments. In realising the context-awareness in knowledge management, we present a context knowledge structure model and look into the corresponding context knowledge storage and reuse solutions. To enhance context-aware knowledge management for e-Businesses over the global network, we introduce a new concept of Context Knowledge Grid with a layered knowledge interoperation reference model, which are supposed to leverage the contextual knowledge in e-Enterprises and enable interoperation with other knowledge frameworks such as the Semantic Web and the Semantic Grid.

Distributed Data Mining on Grids: Services, Tools, and Applications

Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed and parallel systems. The grid can play a significant role in providing an effective computational support for distributed knowledge discovery applications. For the development of data mining applications on grids we designed a system called Knowledge Grid. This paper describes the Knowledge Grid framework and presents the toolset provided by the Knowledge Grid for implementing distributed knowledge discovery. The paper discusses how to design and implement data mining applications by using the Knowledge Grid tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid. Some performance results are also discussed.