Joseph G. Davis

Open source software reliability model: an empirical approach

We collected bug tracking data from a few popular open source projects and investigated the time related bug reporting patterns from them. The results indicate that along its development cycle, open source projects exhibit similar reliability growth pattern with that of closed source project. Bug arrivals of most open source project will stabilize at a very low level, even though in comparison, no formal testing activities are involved. This stabilizing point would be viewed as the mature point for adoption consideration. The results also show that general Weibull distribution offers possible way to establish the reliability model; Also, popular measures such as page views and download are not highly correlated with the bug arrival rate and may not be suitable measures for a projects quality.

The “global” and the “local” in knowledge management

Purpose – This paper aims to unravel the complexities associated with knowledge sharing in large global organizations through a field study carried out in a large, multinational company (Du Pont), focusing on the critical issues, concrete practices, bottle‐necks, and constraints in knowledge sharing. The tension between “local” production of much of the knowledge and its globalizing is specifically addressed.Design/methodology/approach – Qualitative analysis based on a detailed case study of the knowledge‐sharing practices in two business units, two functional areas (R&D and engineering project management) in four countries.Findings – Focus on certain types of organizational knowledge to the exclusion of others can be counter‐productive. Knowledge management (KM) systems need to be integrative and flexible enough to facilitate the dynamic interplay between different forms of knowledge across the space and time.Research limitations/implications – The results of a case study are somewhat limited in terms of...

An Integrated Approach to Extracting Ontological Structures from Folksonomies

Collaborative tagging systems have recently emerged as one of the rapidly growing web 2.0 applications. The informal social classification structure in these systems, also known as folksonomy, provides a convenient way to annotate resources by allowing users to use any keyword or tag that they find relevant. In turn, the flat and non-hierarchical structure with unsupervised vocabularies leads to low search precision and poor resource navigation and retrieval. This drawback has created the need for ontological structures which provide shared vocabularies and semantic relations for translating and integrating the different sources. In this paper, we propose an integrated approach for extracting ontological structure from folksonomies that exploits the power of low support association rule mining supplemented by an upper ontology such as WordNet.

Service Selection in Web Service Composition: A Comparative Review of Existing Approaches

Web service composition (WSC) offers a range of solutions for rapid creation of complex applications in advanced service-oriented systems by facilitating the composition of already existing concrete web services. One critical challenge in WSC is the dynamic selection of concrete services to be bound to the abstract composite service. In this paper, we provide a comprehensive review of the existing proposals for service selection, and a comparative analysis of the optimization and automated negotiation-based approaches.

Aligning Ontologies and Evaluating Concept Similarities

An innate characteristic of the development of ontologies is that they are often created by independent groups of expertise, which generates the necessity of merging and aligning ontologies covering overlapping domains. However, a central issue in the merging process is the evaluation of the differences between two ontologies, viz. the establishment of a similarity measure between their concepts. Many algorithms and tools have been proposed for merging of ontologies, but the majority of them disregard the structural properties of the source ontologies, focusing mostly on syntactic analysis. This article focuses on the alignment of ontologies through Formal Concept Analysis, a data analysis technique founded on lattice theory, and on the use of similarity measures to identify cross-ontology related concepts.

Creating Shared Information Spaces to Support Collaborative Design Work

The provision of computer support for collaborative work is a central concern for Information Systems (IS) research and practice. In this paper we present the details of an information flow study undertaken in the household division of a large European design and manufacturing company (Delta). The goal of the study was to elicit user requirements for a computer system to facilitate the collaborative work of new product design teams. These requirements form the basis for the design and development of a Web-based LIRÉ (Living Repository) prototype system, the functionalities, features, and rationale of which are discussed. We also present the results of the evaluation of LIRÉ by the users at Delta and our observations on enhancing the sophistication and usefulness of this class of system. A production version based on the prototype but using commercially available software is currently in use by the New Product Development group at Delta.

From Crowdsourcing to Crowdservicing

The evolving vision of Web 3.0 is based on the balanced integration of diverse services provided by human agents and machines over the World Wide Web. This is also the intuition that drives crowdservicing, which helps in creating platforms on which new applications and even enterprises can be build. Crowdsourcing as a concept as well as a practice refers to the idea that the Web can facilitate the aggregation or selection of useful information from a potentially large number of people connected to the Internet.

On local pruning of association rules using directed hypergraphs

Here we propose an adaptive local pruning method for association rules. Our method exploits the exact mapping between a certain class of association rules, namely those whose consequents are singletons and backward directed hypergraphs (B-graphs). The hypergraph which represents the association rules is called an association rules network(ARN). Here we present a simple example of an ARN. We further prove several properties of the ARN and apply the results of our approach to two popular data sets.

Community discovery and analysis in blogspace

Weblog has quickly evolved into a new information and knowledge dissemination channel. Yet it is not easy to discover weblog communities through keyword search. The main contribution of this paper is the study of weblog communities from the perspective of social network analysis. We proposed a new way of collecting and preparing data for weblog community discovery. The data collection stage focuses on gaining knowledge of the strength of social ties between weblogs. The strength of social ties and the clustering feature of social network guided the discovery of weblog communities.

Mining open source software (OSS) data using association rules network

The Open Source Software(OSS) movement has attracted considerable attention in the last few years. In this paper we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we introduce Association Rules Network(ARN), a (hyper)graphical model to represent a special class of association rules. Using ARNs we discover important relationships between the attributes of successful OSS projects. We verify and validate these relationships using Factor Analysis, a classical statistical technique related to Singular Value Decomposition(SVD).