PIVOT: An adaptive information discovery framework for computational grids

In a traditional computational grid environment, the owners of resources usually provide information about their resources extracted by pre-configured information services or web services. However, such information is not sufficient for the scheduler in the high-performance distributed computing. To solve this problem, we propose a scalable grid information service framework, named PIVOT (adaPtive Information discoVery framewOrk for compuTational grid). By using deadline-constrained flooding collector dissemination and P2P-like information collection schemes, PIVOT provides an active mechanism to collect application-specific resource information. In particular, PIVOT provides a resource information service for application-specific schedulers. The best-effort performance on overhead traffic and communication latency during information discovery is guaranteed by two new distributed cooperative algorithms. The experimental results in the simulations and real computational grid platform demonstrate that PIVOT has a high level of adaptability for application-specific resource information discovery, and also improves the accuracy of resource allocation and the efficiency of executing parallel tasks in traditional information services.     

基于Petri网的语义Web服务发现框架的研究

针对目前语义Web服务发现研究中存在的不足,提出一种基于Petri网的语义Web服务发现框架.该框架利用OWL-S本体提供的语义信息及Petir网在系统动态行为方面的验证功能,从服务注册中心发现用户所需的服务组合.Web服务的发现结果不仅满足用户的功能需求,而且保证无死锁并能够正确执行,提高了服务发现的准确性.最后通过实例分析验证了该服务发现框架的有效性.     

Perception-based hidden Markov models: a theoretical framework for data mining and knowledge discovery

 The combination of objective measurements and human perceptions using hidden Markov models with particular reference to sequential data mining and knowledge discovery is presented in this paper. Both human preferences and statistical analysis are utilized for verification and identification of hypotheses as well as detection of hidden patterns. As another theoretical view, this work attempts to formalize the complementarity of the computational theories of hidden Markov models and perceptions for providing solutions associated with the manipulation of the internet.     

'Soft' systems thinking and information systems: a framework for client-led design

Abstract. Since the mid-1980s there has been a growing interest in the application of soft systems methodology (SSM) to the information systems design process. This interest has resulted from attempts to overcome the recognized deficiencies of conventional computer systems analysis methods and techniques. A particular problem which has received attention over the past 5 years is the epistemological and operational differences between the investigative process of the pre-design stage and the technological specification. We suggest that this argument is somewhat unproductive and advocate a necessary rethinking about the nature of information systems and the use of technology to support their activities. A re-evaluation of the way that we set about designing computer-based information systems suggests that many of the problems of conventional systems analysis methods may be alleviated by an approach that allows the 'client', or 'user', to have a greater control over the identification, specification and development of their information system(s). The authors' belief in this course of action has led to the development of client-led design as an underpinning philosophy for user participation in the design of computer-based information systems. Client-led design draws upon and develops concepts and tools from 'interpretive', or 'soft', systems thinking and, in particular, can be seen as providing a framework for the type of subjective inquiry that Checkland & Scholes (1990) referred to as 'ideal-type' mode 2 SSM. This paper is related to the papers published in the Journal of Information Systems (Vol. 3, No. 3), which was a special edition to illustrate the influence of 'soft' systems thinking upon information systems design and development.     

Ubiquitous Personal Study: a framework for supporting information access and sharing

The information resources on the Web are diversified, the amount of which is increasing rapidly. Demands for selecting useful information from the Internet, managing personal contents, and sharing contents under control have risen. In this study, we propose the Ubiquitous Personal Study, a framework of personalized virtual study to support accessing, managing, organizing, sharing and recommending information. In this paper, we focus on discussing the framework, and design and implementation issues on how to implement it with Web 2.0 mash-up technology and Open Source Software.     

A framework for virtual organization requirements

Virtual organizations (VOs) are formed by an alliance of organizations linked by a partnership for dealing with emerging challenges. Information and communication technologies play a fundamental role facilitating cooperation, communication and collaboration among the VO members. The formal identification and representation of Requirements Engineering (RE) for one organization have been researched to a large extent along with several elicitation techniques. However, these techniques are not adequate for covering the major challenges of RE for VO. We explore the work done in the management and RE fields to propose a model-based framework for eliciting VOs’ requirements. The goal is to analyze the VO from two points of view: border (intra-organizational, inter-organizational and extra-organizational) and abstract (intentional, organizational and operational). This article includes the framework validation with a case study and a transformation process to develop partial Business Process Diagram from the intentional models.     

Building a model for an information property framework

The paper argues that intellectual property has become fixated on a few unchanging postulates, categories and rules even while society is transiting towards a new era, that of information; such a transition makes serious reversals of thinking in intellectual property timely. The paper outlines the fundamental cracks in intellectual property that have become more prominent in the last two decades of the 20th century and suggests a model for integrating it into the emergent information society. The model proposes to transcend the disparate tendencies in current forms of intellectual property. The paper concludes by pointing to the need for establishing a tool of measuring creativity that could be crucial for such a model.     

VisGets: coordinated visualizations for web-based information exploration and discovery

In common Web-based search interfaces, it can be difficult to formulate queries that simultaneously combine temporal, spatial, and topical data filters. We investigate how coordinated visualizations can enhance search and exploration of information on the World Wide Web by easing the formulation of these types of queries. Drawing from visual information seeking and exploratory search, we introduce emph{VisGets} -- interactive query visualizations of Web-based information that operate with online information within a Web browser. VisGets provide the information seeker with visual overviews of Web resources and offer a way to visually filter the data. Our goal is to facilitate the construction of dynamic search queries that combine filters from more than one data dimension. We present a prototype information exploration system featuring three linked VisGets (temporal, spatial, and topical), and used it to visually explore news items from online RSS feeds.     

Novel information discovery for intelligence and counterterrorism

Intelligence analysts construct hypotheses from large volumes of data, but are often limited by social and organizational norms and their own preconceptions and biases. The use of exploratory data mining technology can mitigate these limitations by requiring fewer assumptions. We present the design of the ATHENS system, which discovers novel information, relative to a specified set of existing knowledge, in large information repositories such as the World Wide Web. We illustrate the use of the system by starting from the terms “al Qaeda” and “bin Laden”" and running the ATHENS system as if on September 12th, 2001. This provides a picture of what novel information could have been known at the time. This is of some intrinsic interest, but also serves to validate the performance of the system since much of this novel information has been discovered by conventional means in the intervening years.     

A framework for knowledge discovery and evolution in databases

A concept for knowledge discovery and evolution in databases is described. The key issues include: using a database query to discover new rules; using not only positive examples (answer to a query), but also negative examples to discover new rules; and harmonizing existing rules with the new rules. A tool for characterizing the exceptions in databases and evolving knowledge as a database evolves is developed     

Organizational information security policies: a review and research framework

A major stream of research within the field of information systems security examines the use of organizational policies that specify how users of information and technology resources should behave in order to prevent, detect, and respond to security incidents. However, this growing (and at times, conflicting) body of research has made it challenging for researchers and practitioners to comprehend the current state of knowledge on the formation, implementation, and effectiveness of security policies in organizations. Accordingly, the purpose of this paper is to synthesize what we know and what remains to be learned about organizational information security policies, with an eye toward a holistic understanding of this research stream and the identification of promising paths for future study. We review 114 influential security policy-related journal articles and identify five core relationships examined in the literature. Based on these relationships, we outline a research framework that synthesizes the construct linkages within the current literature. Building on our analysis of these results, we identify a series of gaps and draw on additional theoretical perspectives to propose a revised framework that can be used as a basis for future research.     

A framework for virtual organization creation in a breeding environment

Effectiveness in the process of creating virtual organizations (VO) is an important pre-condition for having a truly dynamic VOs, in response to collaboration opportunities in fast changing market contexts. A realistic approach to materialize agility in VO creation is defined under the assumption of a VO Breeding Environment (VBE), that guarantees the preparedness of its members to quickly get engaged in collaboration processes. After a survey of past approaches and a characterization of the VBE concept, a discussion of the process and suggested functionalities towards a VO creation framework are presented in this context. Finally a list of supporting tools is described and future research challenges are pointed out.     

Knowledge discovery in high-dimensional data: case studies and a user survey for the rank-by-feature framework

Knowledge discovery in high-dimensional data is a challenging enterprise, but new visual analytic tools appear to offer users remarkable powers if they are ready to learn new concepts and interfaces. Our three-year effort to develop versions of the hierarchical clustering explorer (HCE) began with building an interactive tool for exploring clustering results. It expanded, based on user needs, to include other potent analytic and visualization tools for multivariate data, especially the rank-by-feature framework. Our own successes using HCE provided some testimonial evidence of its utility, but we felt it necessary to get beyond our subjective impressions. This paper presents an evaluation of the hierarchical clustering explorer (HCE) using three case studies and an e-mail user survey (n=57) to focus on skill acquisition with the novel concepts and interface for the rank-by-feature framework. Knowledgeable and motivated users in diverse fields provided multiple perspectives that refined our understanding of strengths and weaknesses. A user survey confirmed the benefits of HCE, but gave less guidance about improvements. Both evaluations suggested improved training methods.     

Structured-case: a methodological framework for building theory in information systems research

This paper presents a methodological framework, structured-case, that assists IS researchers to undertake and assess theory building research within the interpretive paradigm, and explains its value in achieving convincing explanations that are strongly linked to both the research themes and data collected in the field.     

Optimization framework for DFG-based automated process discovery approaches

The problem of automatically discovering business process models from event logs has been intensely investigated in the past two decades, leading to a wide range of approaches that strike various trade-offs between accuracy, model complexity, and execution time. A few studies have suggested that the accuracy of automated process discovery approaches can be enhanced by means of metaheuristic optimization techniques. However, these studies have remained at the level of proposals without validation on real-life datasets or they have only considered one metaheuristic in isolation. This article presents a metaheuristic optimization framework for automated process discovery. The key idea of the framework is to construct a directly-follows graph (DFG) from the event log, to perturb this DFG so as to generate new candidate solutions, and to apply a DFG-based automated process discovery approach in order to derive a process model from each DFG. The framework can be instantiated by linking it to an automated process discovery approach, an optimization metaheuristic, and the quality measure to be optimized (e.g., fitness, precision, F-score). The article considers several instantiations of the framework corresponding to four optimization metaheuristics, three automated process discovery approaches (Inductive Miner—directly-follows, Fodina, and Split Miner), and one accuracy measure (Markovian F-score). These framework instances are compared using a set of 20 real-life event logs. The evaluation shows that metaheuristic optimization consistently yields visible improvements in F-score for all the three automated process discovery approaches, at the cost of execution times in the order of minutes, versus seconds for the baseline approaches.

     

Dialectical hermeneutics: a theoretical framework for the implementation of information systems

Abstract. Despite the proliferation of information technology, the implementation of information systems remains problematic. Many systems fail to live up to expectations and some end up as disasters. Research on implementation has been conducted for the past two decades, but no theoretical framework for IS implementation has been widely accepted. This paper proposes dialectical hermeneutics as a theoretical framework for IS implementation research. Dialectical hermeneutics, as an integrative theoretical framework, combines both interpretive and critical elements, and addresses those social and organizational issues which are critical to the successful implementation of information systems. The case study research method was used to examine the implementation of systems in three organizations.     

Towards a framework for energy-aware information systems in manufacturing

Environmental concerns, stricter legislation and inflated energy costs, together yield energy efficiency as an important pillar for virtually every industrial sector. Mindful of this challenge, ISs can act as enablers of energy-based management and intelligent decision support. Based on empirical evidence through two case studies combined with the design of a system prototype, this paper identifies those major functionalities that suffice to characterize an IS as ‘energy-aware’ in manufacturing. The functionalities are classified into two broad categories: (a) energy monitoring and (b) energy-aware analytics and are then combined into a high-level architecture. As a prerequisite for deploying such functionalities, this research presents also an approach integrating energy and operational information flows. Beyond that, the technologies that support the real-time and large-scale handling of energy data are provided. Our effort scales up to introduce a generic framework of a case-independent energy-aware IS.     

Distributed cognition as a theoretical framework for information visualization

Even though information visualization (InfoVis) research has matured in recent years, it is generally acknowledged that the field still lacks supporting, encompassing theories. In this paper, we argue that the distributed cognition framework can be used to substantiate the theoretical foundation of InfoVis. We highlight fundamental assumptions and theoretical constructs of the distributed cognition approach, based on the cognitive science literature and a real life scenario. We then discuss how the distributed cognition framework can have an impact on the research directions and methodologies we take as InfoVis researchers. Our contributions are as follows. First, we highlight the view that cognition is more an emergent property of interaction than a property of the human mind. Second, we argue that a reductionist approach to study the abstract properties of isolated human minds may not be useful in informing InfoVis design. Finally we propose to make cognition an explicit research agenda, and discuss the implications on how we perform evaluation and theory building.     

A unified framework for web video topic discovery and visualization

Together with the explosive growth of web video in sharing sites like YouTube, automatic topic discovery and visualization have become increasingly important in helping to organize and navigate such large-scale videos. Previous work dealt with the topic discovery and visualization problem separately, and did not take fully into account of the distinctive characteristics of multi-modality and sparsity in web video features. This paper tries to solve web video topic discovery problem with visualization under a single framework, and proposes a Star-structured K-partite Graph based co-clustering and ranking framework, which consists of three stages: (1) firstly, represent the web videos and their multi-model features (e.g., keyword, near-duplicate keyframe, near-duplicate aural frame, etc.) as a Star-structured K-partite Graph; (2) secondly, group videos and their features simultaneously into clusters (topics) and organize the generated clusters as a linked cluster network; (3) finally, rank each type of nodes in the linked cluster network by “popularity” and visualize them as a novel interface to let user interactively browse topics in multi-level scales. Experiments on a YouTube benchmark dataset demonstrate the flexibility and effectiveness of our proposed framework.     

Inter-organizational relationships and information technology: a conceptual synthesis and a research framework

Inter-organizational strategies that leverage information technology capabilities are becoming more widespread but the degree of research attention is limited. This paper integrates theoretical concepts from transaction cost economics, organization theory and political economy to develop a conceptual framework to understand inter-organizational relationships, particularly those that explicitly leverage information technology capabilities. Further, we develop research directions and approaches to bridge the requirements of theory building and theory testing.