PicShark: mitigating metadata scarcity through large-scale P2P collaboration

With the commoditization of digital devices, personal information and media sharing is becoming a key application on the pervasive Web. In such a context, data annotation rather than data production is the main bottleneck. Metadata scarcity represents a major obstacle preventing efficient information processing in large and heterogeneous communities. However, social communities also open the door to new possibilities for addressing local metadata scarcity by taking advantage of global collections of resources. We propose to tackle the lack of metadata in large-scale distributed systems through a collaborative process leveraging on both content and metadata. We develop a community-based and self-organizing system called PicShark in which information entropy—in terms of missing metadata—is gradually alleviated through decentralized instance and schema matching. Our approach focuses on semi-structured metadata and confines computationally expensive operations to the edge of the network, while keeping distributed operations as simple as possible to ensure scalability. PicShark builds on structured Peer-to-Peer networks for distributed look-up operations, but extends the application of self-organization principles to the propagation of metadata and the creation of schema mappings. We demonstrate the practical applicability of our method in an image sharing scenario and provide experimental evidences illustrating the validity of our approach. The work presented in this article was supported by the Swiss NSF National Competence Center in Research on Mobile Information and Communication Systems (NCCR MICS, grant number 5005-67322), by the EPFL Center for Global Computing as part of the European project NEPOMUK No FP6-027705, and by the Líon project supported by Science Foundation Ireland under Grant No. SFI/02/CE1/I131.     

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.     

Modelling with knowledge: A review of emerging semantic approaches to environmental modelling

Models, and to a lesser extent datasets, embody sophisticated statements of environmental knowledge. Yet, the knowledge they incorporate is rarely self-contained enough for them to be understood and used – by humans or machines – without the modeller's mediation. This severely limits the options in reusing environmental models and connecting them to datasets or other models. The notion of “declarative modelling” has been suggested as a remedy to help design, communicate, share and integrate models. Yet, not all these objectives have been achieved by declarative modelling in its current implementations.Semantically aware environmental modelling is a way of designing, implementing and deploying environmental datasets and models based on the independent, standardized formalization of the underlying environmental science. It can be seen as the result of merging the rationale of declarative modelling with modern knowledge representation theory, through the mediation of the integrative vision of a Semantic Web. In this paper, we review the present and preview the future of semantic modelling in environmental science: from the mediation approach, where formal knowledge is the key to automatic integration of datasets, models and analytical pipelines, to the knowledge-driven approach, where the knowledge is the key not only to integration, but also to overcoming scale and paradigm differences and to novel potentials for model design and automated knowledge discovery.     

语义为核心的多文种信息处理平台的模型

提出了一个基于语义、面向自然语言处理的多文种信息处理平台的模型SMIPP.该模型主要由应用程序/用户接口层、文字输入层和文字输出层、信息处理服务层、语料库层、多文种代码体系SemaCode层和语言Ontology层组成,该平台把各种语言文字统一用具有自描述能力的SemaCode表示,并通过语言Ontology来表示词汇的语义以及在各个文种间的联系,再通过服务形式提供各种基于语料库的文字信息处理功能,是一个全新的多文种信息处理模型.     

Fostering collective and individual learning through knowledge building

The purpose of this study was to design and examine a computer-supported knowledge-building environment and to investigate both collective knowledge-building dynamics and individual learning in the context of a tertiary education course in mainland China. The participants were 102 students in four intact Year-one tertiary business classes. Two classes experienced a knowledge-building environment (CKB) and the other two were taught using a regular project-based approach (RPBL). Data were obtained from interactions in the forum, writing quality, group-learning portfolios, and surveys. Quantitative analyses indicated that the knowledge-building groups outperformed the comparison groups on academic literacy assessed in terms of conceptual understanding and explanation, and obtained higher scores on beliefs about collaboration. Within-group analyses indicated that the students’ engagement in Knowledge Forum was a significant predictor of their academic literacy. Qualitative contrastive analyses of high- and low-performance groups identified different patterns of conceptual, metacognitive and social processes, and showed that student groups engaging in more collective and meta-discourse discourse moves performed better on individual scores in academic literacy. The implications of examining both collaborative dynamics and individual learning and designing computer-supported knowledge building for tertiary students are discussed.     

From P2P to reliable semantic P2P systems

Current research to harness the power of P2P networks involves building reliable Semantic Peer-to-Peer (SP2P) systems. SP2P systems combine two complementary technologies: P2P networking and ontologies. There are several types of SP2P systems with applications to knowledge management systems, databases, the Semantic Web, emergent semantics, web services, and information systems. Correct semantic mapping is fundamental for success of SP2P systems where semantic mapping refers to semantic relationship between concepts from different ontologies. Current research on SP2P systems has emphasized semantics at the cost of dealing with the traditional issues of P2P networks of reliability and scalability. As a result of their lack of resilience to temporary mapping faults, SP2P systems can suffer from disconnection failures. Disconnection failures arise when SP2P systems that use adaptive query routing methods treat temporary mapping faults as permanent mapping faults. This paper identifies the disconnection failure problem due to temporary semantic mapping faults and proposes an algorithm to resolve it. To identify the problem, we will use a simulation model of SP2P systems. The Fault-Tolerant Adaptive Query Routing (FTAQR) algorithm proposed to resolve the problem is an adaptation of the generous tit-for-tat method originally developed in evolutionary game theory. The paper demonstrates that the reliability of an SP2P system increases by using the algorithm.     

Team leader strategies for enabling collaboration technology adaptation: team technology knowledge to improve globally distributed systems development work

Active management of team adaptation of collaboration technologies offers an important lever for influencing success rates in distributed project work, particularly in settings characterized by high task interdependence, such as information systems development (ISD). Substantial uncertainty exists as to how a leader might influence such technology adaptation during project work. Prior research indicates that a major leader resource to accomplish technology adaptation in these settings would be team technology knowledge (TTK). This empirical field study develops a five-factor model of strategies regarding awareness of TTK that team leaders take in intervening to affect technology adaptation in distributed ISD projects. The analysis indicates insights into when and why these strategies are effective and how they relate to each other as well as the leader's awareness of TTK. The study provides a way for ISD team leaders to approach improving team collaboration from a socio-technical perspective as well as insights into potential levers for improving team technology adaptation and the efficacy of ISD projects.     

New knowledge in strategic management through visually mining semantic networks

Today’s highly competitive business world requires that managers be able to make fast and accurate strategic decisions, as well as learn to adapt to new strategic challenges. This necessity calls for a deep experience and a dynamic understanding of strategic management. The trait of dynamic understanding is mainly the skill of generating additional knowledge and innovative solutions under the new environmental conditions. Building on the concepts of information processing, this paper aims to support managers in constructing new strategic management knowledge, through representing and mining existing knowledge through graph visualization. To this end, a three-stage framework is proposed and described. The framework can enable managers to develop a deeper understanding of the strategic management domain, and expand on existing knowledge through visual analysis. The model further supports a case study that involves unstructured knowledge of profit patterns and the related strategies to succeed using these patterns. The applicability of the framework is shown in the case study, where the unstructured knowledge in a strategic management book is first represented as a semantic network, and then visually mined for revealing new knowledge.     

Entity Notation: enabling knowledge representations for resource-constrained sensors

The forthcoming ambient systems will contain a large amount of sensors. Representing the data produced by these sensors in a format suitable for ambient intelligence applications would enable a large number of useful services. However, such formats tend to require processing power and communication bandwidth not available in many sensors utilizing ultra low-power microcontrollers and radio chip solutions. This paper presents a lightweight data representation, Entity Notation, to tackle this problem. Sensors with limited computation and communication capabilities can use Entity Notation to describe the data they produce. Entity Notation can be transformed into knowledge representations in a straightforward manner, and hence, the data produced by sensor nodes can be utilized with ease by any ambient intelligence system compatible with the common knowledge representations. This paper presents the design of Entity Notation, its implementations on embedded sensors and the evaluation of its performance.     

The need for systems development capability in design science research: enabling researcher-systems developer collaboration

Information systems as an artefact-oriented discipline require a strong interaction between researchers, developers and users regarding design of, development of, and the study of the use of digital artefacts in social settings. During recent years, performing research in a design science research spirit has gained increasing interest. In larger scale design research endeavours, access to systems development capabilities becomes necessary. Such a unit, InnovationLab, was established in 2006 in a university setting in Sweden. In this paper we are investigating the 5 years’ experience of running this InnovationLab. Our findings point to an innovation lab being valuable for research in general and especially for design science research. However, in order to balance the business of an innovation lab, it will be necessary to provide services for other stakeholders (such as administrative units, teachers, and students) as a means for developing systems development capability aimed at supporting researchers.     

Engaging construction stakeholders with sustainability through a knowledge harvesting platform

With the new regulations and policies related to climate change, the construction industry has been put under pressure to increase the sustainability of its practices. Many organisations are now adapting their practices to meet government legislative targets (e.g. reducing carbon emissions) and consider the environmental, social and economic performance of buildings. In addition, the sustainable construction is also a rapidly changing field, with technological advances, changes in legislation and increasingly educated clients driving the industry to constantly adapt to remain competitive. This represents a key problem for construction professionals as they must continually be aware of new information, best practices, technologies and changing legislation (at a local, national and international level) which are often disseminated from different organisations/individuals through dispersed media.     

P2P备份系统的协作机制研究

P2P备份系统已经成为确保数据可用的解决方案之一,它的关键思想是利用P2P网络节点的空闲存储空间来存储数据.由于P2P网络是一个高动态的环境,该系统的主要缺陷是对等节点之间缺乏协作机制.为了解决这个缺陷,系统定义一组时间表,它模拟每一个节点的可用性和需求,解决节点之间的备份协作问题并且确保有效的使用节点资源.仿真实验结果表明,基于时间表协作机制能改善P2P备份系统的性能.     

基于P2P的分布式工作流平台

随着跨组织业务的拓展,分布式工作流已经成为研究热点。通过对分布式工作流和P2P技术的分析,提出了一种基于P2P的分布式工作流平台。描述了它的网络架构和系统架构,建立了底层的消息通信机制,给出了工作流的定义和执行的分布式设计。相对于传统的工作流平台而言,该平台具有可靠性高、异步协同能力强和应用广泛的特点。     

A framework for semantic grouping in P2P databases

Sharing of structured data in decentralized environments is a challenging problem, especially in the absence of a global schema. Social network structures map network links to semantic relations between participants in order to assist in efficient resource discovery and information exchange. In this work, we propose a scheme that automates the process of creating schema synopses from semantic clusters of peers which own autonomous relational databases. The resulting mediated schemas can be used as global interfaces for relevant queries. Active nodes are able to initiate the group schema creation process, which produces a mediated schema representative of nodes with similar semantics. Group schemas are then propagated in the overlay and used as a single interface for relevant queries. This increases both the quality and the quantity of the retrieved answers and allows for fast discovery of interest groups by joining peers. As our experimental evaluations show, this method increases both the quality and the quantity of the retrieved answers and allows for faster discovery of semantic groups by joining peers.     

The MASSIF platform: a modular and semantic platform for the development of flexible IoT services

In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or by processing the combined data. The processes of combining data can consist both of merging the dynamic sensed data, as well as fusing the sensed data with background and historical data. Semantics can aid in this task, as they have proven their use in data integration, knowledge exchange and reasoning. Semantic services performing reasoning on the integrated sensed data, combined with background knowledge, such as profile data, allow extracting useful information and support intelligent decision making. However, advanced reasoning on the combination of this sensed data and background knowledge is still hard to achieve. Furthermore, the collaboration between semantic services allows to reach complex decisions. The dynamic composition of such collaborative workflows that can adapt to the current context, has not received much attention yet. In this paper, we present MASSIF, a data-driven platform for the semantic annotation of and reasoning on IoT data. It allows the integration of multiple modular reasoning services that can collaborate in a flexible manner to facilitate complex decision-making processes. Data-driven workflows are enabled by letting services specify the data they would like to consume. After thorough processing, these services can decide to share their decisions with other consumers. By defining the data these services would like to consume, they can operate on a subset of data, improving reasoning efficiency. Furthermore, each of these services can integrate the consumed data with background knowledge in its own context model, for rapid intelligent decision making. To show the strengths of the platform, two use cases are detailed and thoroughly evaluated.     

基于语义查询的P2P路由模型研究

针对结构化P2P网络路由模型中存在难以有效支持内容定位的问题,提出基于语义查询的P2P路由模型.利用概念向量来描述文档、节点、簇和查询请求;通过节点概念向量间的相似度聚成不同层次的语义簇,并采用基于概念相似度计算进行路由选取和转发的路由策略;利用节点的异构性,让性能好的超级节点承担更多的工作量,并引入服务节点便于快速导航语义簇中的语义类别.实验结果表明,该路由模型能有效提高系统的搜索效率.     

DartGrid II: a semantic grid platform for ITS

Intelligent transportation systems offer an alternative approach to solving many problems by implementing advances in information, Internet, communication, and cybernetics technologies. Grid computing can support traffic data semantization, resource sharing, ITS subsystem cooperation, and global-scale distributed computing that connects all kinds of resources. We are currently using grid technology to build DartGrid II, a semantic ITS platform to support resource sharing, service flow management, and cross-domain cooperation.     

P2P电子商务平台DEP中搜索机制的研究

将P2P应用于电子商务,面临的首要挑战就是如何表达和存储电子商务数据,以及如何高效地搜索到所需数据[1].针对设计的一个电子商务平台DEP模型,通过引入移动代理和缓存优化机制提高了DEP中的搜索效率.此外还对几种不同的搜索方案进行了对比分析与实验,结果表明DEP本身具有很好的可扩展性,与传统模型相比可以很大程度地降低数据检索时的查询路由次数及系统的通讯量,优化后的搜索算法也取得了很好的优化效果.     

B2B collaboration through web services-based multi-agent system

Web services open a door for better B2B collaboration in large distributed environment such as Internet. Process-oriented systems like workflow management systems have been taking the main role for web service-based B2B collaboration in such an environment. However, conventional workflow management systems don’t offer complete solutions for B2B collaborations considering many unsolved issues such as security, trust and complex and flexible interaction handling. In this paper, we propose a web service-based multi-agent platform, which can be used as a complementary solution for B2B collaborations. It fits naturally into the B2B interaction model and provides a very loosely coupled open system architecture.