Intelligent Management and Efficient Operation of Big Data

This chapter details how Big Data can be used and implemented in networking and computing infrastructures. Specifically, it addresses three main aspects: the timely extraction of relevant knowledge from heterogeneous, and very often unstructured large data sources, the enhancement on the performance of processing and networking (cloud) infrastructures that are the most important foundational pillars of Big Data applications or services, and novel ways to efficiently manage network infrastructures with high-level composed policies for supporting the transmission of large amounts of data with distinct requisites (video vs. non-video). A case study involving an intelligent management solution to route data traffic with diverse requirements in a wide area Internet Exchange Point is presented, discussed in the context of Big Data, and evaluated.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201

A Layered Software Architecture for the Management of a Manufacturing Company

In this paper we describe a layered software architecture in the management of a manufactur-ing company that intensively uses computer technology. Application tools, new and legacy, after the updating, operate in a context of an open web oriented architecture. The software architecture enables the integration and interoperability among all tools that support business processes. Manufacturing Executive System and Text Mining tools are excellent interfaces, the former both for internal production and management processes and the latter for external processes coming from the market. In this way, it is possible to implement, a computer integrated factory, flexible and agile, that immediately responds to customer requirements.ICT, Service Oriented Architecture, Web Services, Computer-Integrated Factory, Application Software

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Massive ontology interface

This paper describes the Massive Ontology Interface (MOI), a web portal which facilitates interaction with a large ontology (over 200,000 concepts and 1.6M assertions) that is built automatically using OpenCyc as a backbone. The aim of the interface is to simplify interaction with the massive amounts of information and guide the user towards understanding the ontology’s data. Using either a text or graph-based representation, users can discuss and edit the ontology. Social elements utilizing gamification techniques are included to encourage users to create and collaborate on stored knowledge as part of a web community. An evaluation by 30 users comparing MOI with OpenCyc’s original interface showed significant improvements in user understanding of the ontology, although full testing of the interface’s social elements lies in the future

Usability discussions in open source development

The public nature of discussion in open source projects provides a valuable resource for understanding the mechanisms of open source software development. In this paper we explore how open source projects address issues of usability. We examine bug reports of several projects to characterise how developers address and resolve issues concerning user interfaces and interaction design. We discuss how bug reporting and discussion systems can be improved to better support bug reporters and open source developers

Exploring usability discussions in open source development

The public nature of discussion in open source projects provides a valuable resource for understanding the mechanisms of open source software development. In this paper we explore how open source projects address issues of usability. We examine bug reports of several projects to characterise how developers address and resolve issues concerning user interfaces and interaction design. We discuss how bug reporting and discussion systems can be improved to better support bug reporters and open source developers