Data quality is crucial for operational efficiency and sound decision making. This paper focuses on believability, a major aspect of quality, measured along three dimensions: trustworthiness, reasonableness, and temporality. We ground our approach on provenance, i.e. the origin and subsequent processing history of data. We present our provenance model and our approach for computing believability based on provenance metadata. The approach is structured into three increasingly complex building blocks: (1) definition of metrics for assessing the believability of data sources, (2) definition of metrics for assessing the believability of data resulting from one process run and (3) assessment of believability based on all the sources and processing history of data. We illustrate our approach with a scenario based on Internet data. To our knowledge, this is the first work to develop a precise approach to measuring data believability and making explicit use of provenance-based measurements.

Abstract—The evolution towards cross-organizational collaboration and interaction patterns has led to the emergence of scalable, Web services-based composition infrastructures. The success of service-oriented architecture (SOA) was mainly influenced by the standardization of composition languages such as BPEL. However, compositions require humans to be in the loop and ways to interface with people in a service-oriented manner. In this paper, we discuss Human-Provided Services (HPS) enabling the seamless integration of human capabilities in SOA. In complex and large-scale environments, processes might span interactions among partially unknown participants residing in different organizational units. To address the problem of trusted selection of participants, we introduce a mining approach for the automatic inference of trust relations. Unlike a securitybased view on trust, our approach relates to the emergence of trust across humans and services from a social perspective. Keywords-interaction patterns; trust; mixed systems; human involvement in SOA; online help and support I.

This paper is available online at www.jtaer.com DOI: 10.4067/S0718-18762010000200008

There are currently very few practical methods for assessing the quality of resources or the reliability of other entities in the online environment. This makes it difficult to make decisions about which resources can be relied upon and which entities it is safe to interact with. Trust and reputation systems are aimed at solving this problem by enabling service consumers to reliably assess the quality of services and the reliability of entities before they decide to use a particular service or to interact with or depend on a given entity. Such systems should also allow serious service providers and online players to correctly represent the reliability of themselves and the quality of their services. In the case of reputation systems, the basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive its reputation score. In the case of trust systems, the basic idea is to analyse and combine paths and networks of trust relationships in order to derive measures of trustworthiness of specific nodes. Reputation scores and trust measures can assist other parties in deciding whether or not to transact with a given party in the future, and whether it is safe to depend on a given resource or entity. This represents an incentive for good behaviour and for offering reliable resources, which thereby tends to have a positive effect on the quality of online markets and communities. This chapter describes the background, current status and future trend of online trust and reputation systems.

Abstract. Peer-to-Peer (P2P) computing is widely recognized as a promising paradigm for building next generation distributed applications. However, the autonomous, heterogeneous, and decentralized nature of participating peers introduces the following challenge for resource sharing: how to make peers profitable in the untrusted P2P environment? To address the problem, we present a self-policing and distributed approach by combining two models: PET, a personalized trust model, and M-CUBE, a multiple-currency based economic model, to lay a foundation for resource sharing in untrusted P2P computing environments. PET is a flexible trust model that can adapt to different requirements, and provides the solid support for the currency management in M-CUBE. M-CUBE provides a novel self-policing and quality-aware framework for the sharing of multiple resources, including both homogeneous and heterogeneous resources. We evaluate the efficacy and performance of this approach in the context of a real application, a peer-to-peer Web server sharing. Our results show that our approach is flexible enough to adapt to different situations and effective to make the system profitable, especially for systems with large scale.

Reputation systems are indispensable for the operation of Internet mediated services, electronic markets, document ranking systems, P2P networks and Ad Hoc networks. Here we survey available distributed approaches to the graph based reputation measures. Graph based reputation measures can be viewed as random walks on directed weighted graphs whose edges represent interactions among peers. We classify the distributed approaches to graph based reputation measures into three categories. The first category is based on asynchronous methods. The second category is based on the aggregation/decomposition methods. And the third category is based on the personalization methods which use local information.

Abstract. In an increasingly automated and networked world humans are facing new problems stemming from the introduction of machine-intensive communication. The natural human ability to asses, accumulate and evaluate trust in other humans through direct interpersonal communications is significantly impaired when humans interact with systems alone. The development of applications that rely on trust, like electronic commerce, is significantly affected by this fact. This paper outlines a joint project that Nokia and Hewlett-Packard have just begun which analyses a) the ability of technology to replace the traditional notion of human-evaluated trust with a measure of trust that can be evaluated for the human by automated systems, and b) how this measurement can be communicated to the human by a personal appliance that we call an Intimate Trust Advisor (ITA). 1.

Reputation and trust are two very useful tools that are used to facilitate decision making in diverse fields from an ancient fish market to state-of-the-art ecommerce. Reputation is the opinion of one entity about another. In an absolute context, it is the trustworthiness of an entity [26]. Trust, on the other hand, is

Abstract. Trust is an approach to managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system. As a result, trust has been widely studied in multiagent systems and related fields such as the semantic web. Here we introduce a simple approach to reasoning about trust with logic, describe how it can be combined with reasoning about beliefs using logic, and demonstrate its use on an example. The example highlights a number of issues related to resolving weighted arguments. 1

The article describes and gives an economic analysis of a business model for commercial content delivery networks (CDN) based on the Peer-to-Peer model. The content is stored in the CDN on the hosts of the peers. An user pays for access to the content, and can sell the content to other users as in a direct sales network. The content trade is a free market. Transactions (including billing and accounting) are handled by superpeers, who receive a markup for their services and pay the content provider a gratification for every transaction. The system makes use of reputation mechanisms with a goal contrary to most P2P research: to promote content trading and discourage sharing for free. The article compares the profit obtained by the content provider in a client-server CDN and the P2P CDN, and analyzes the stable-state prices in a P2P CDN.