Maurice McNaughton

Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem

Open data have the potential to improve the governance of universities as public institutions. In addition, open data are likely to increase the quality, efficacy and efficiency of the research and analysis of higher education systems by providing a shared empirical base for critical interrogation and reinterpretation. Drawing on research conducted by the Emerging Impacts of Open Data in Developing Countries project, and using an ecosystems approach, this research paper considers the supply, demand and use of open data as well as the roles of intermediaries in the governance of South African public higher education. It shows that governments higher education database is a closed and isolated data source in the data ecosystem; and that the open data that are made available by government is inaccessible and rarely used. In contrast, government data made available by data intermediaries in the ecosystem are being used by key stakeholders. Intermediaries are found to play several important roles in the ecosystem: (i) they increase the accessibility and utility of data; (ii) they may assume the role of a “keystone species” in a data ecosystem; and (iii) they have the potential to democratize the impacts and use of open data. The article concludes that despite poor data provision by government, the public university governance open data ecosystem has evolved because intermediaries in the ecosystem have reduced the viscosity of government data. Further increasing the fluidity of government open data will improve access and ensure the sustainability of open data supply in the ecosystem.

An Approach to Using Ontologies for the Development of High Quality Disaster Recovery Plans

Disasters have the potential to cripple a country and those countries that are particularly susceptible to disasters must have effective disaster recovery plans (DRP) in place to ensure that the country can return to normalcy as soon as possible after the devastation. However, for the plan to be effective it must be of high quality, which is often viewed as a multidimensional concept containing essential factors for DRP, such as consistency, completeness, reliability and feasibility. Therefore, any methodology for the development of DRP must take these dimensions into account as their affect on quality is considerable. In this regard, the authors describe a quality based methodology for the development of DRP, including a methodology that makes use of ontologies containing properties that are suited to the development of these high quality plans. The applicability of the proposed methodology will be demonstrated through a case study of an electric utility company in Jamaica. point where the society is unable to continue to function using only its resources (e.g., human, monetary). These disasters are often classified as either natural (e.g., hurricanes, earthquakes) or manmade (e.g., terrorism, oil spills) (AlcantaraAyala, 2002; Faulkner, 2001; IDNDR, 1992). Regardless of their classification, disasters are likely to inflict extensive damage on a country’s society and infrastructure and the DOI: 10.4018/jiscrm.2010040103 36 International Journal of Information Systems for Crisis Response Management, 2(2), 35-53, April-June 2010 Copyright

Data preparation: Art or science?

Data preparation is often cited as the most time consuming phase of a Knowledge Discovery and Data Mining (KDDM) process. This is attributed to the fact that this phase is highly dependent on the expertise of the analyst. Although process models exist for KDDM the description of their phases of the process focus on outlining what must be done but often do not detail how this should be done. While there is some research in addressing the how of the phases, the data preparation phase is thought to be the most challenging and is often described as an art rather than a science. The tasks defined in this phase are thought to be highly dependent on the expertise of the analyst and the context. While we are of the view that there will always be an art to data preparation we will demonstrate that the science can actually enhance the art. We further contend that as more research of this kind is published, that demonstrates a variety of data preparation techniques that enhance the data mining process, the more effective will be the science of data preparation.

Using Multiple Case Studies to Analyse Open Source Software Business Sustainability in Sub-Saharan Africa

Amidst the debate about what sort of technology is appropriate for achieving sustainable development, Free and Open Source Software (FOSS) offers some solutions to today’s technology problems for many developing countries. However, there is a paucity of empirical evidence to help us understand the potentials FOSS technologies have for small businesses in Sub-Saharan Africa. This research utilizes nine case studies data from seven African countries to find out how entrepreneurs are leveraging FOSS to help them create sustainable business based on openness. The findings show increasing awareness of the business potential of FOSS, and a business model incorporating both FOSS and proprietary software is needed to run a sustainable IT business in these countries. However, the lack of skilled FOSS developer base, the absence of appropriate policies, and poor payment habits by clients are just some of the factors affecting businesses. Other problems encountered, possible solutions to those problems and lessons to be learnt from each case study are also discussed. The research offers entrepreneurs, ICT practitioners, and policy makers the platform to understand the Why and How FOSS technologies are impacting the traditional way of doing business in Sub-Saharan Africa.

Big Data Analytics and Customs Throughput: The Case of Jamaica

Three main functions of customs agencies are security and facilitation of international trade, fair and efficient collection of revenue and protection of public health and safety. These functions are becoming more difficult due to rapid changes in the operational environment. In this increasingly difficult environment the World Customs Organization advocates less intrusive customs inspections under the revised Kyoto Convention. However, customs administrations in developing countries, like Jamaica, have to contend with the simultaneous conflicting tensions between growing trade flows, service quality demands of private operators, and increased revenue demand pressures of governments. This paper discusses the potential of Big Data Analytics and Data Mining techniques, adapted from other sectors, to explore the research question: Can Big Data Analytics improve efficiency and effectiveness of Customs Operations in developing countries by increasing the precision of targeted physical inspections? This is explored through the use of a case study, Jamaica.

Discovering Knowledge Nuggets in Financial Data: The Case of a Financial Services Institution.

The success stories of organisations that have been transformed through the application of business intelligence are numerous and well documented. However, there are many organisations that have made significant investments in these technologies without the expected returns. What organisations must understand is that the application of the analytics itself is a small part of the process and if the expected results are to be realized a more structured process model must be followed. The most common approach is the KDDM process model, which includes a very important data preparation stage.

An agile approach for academic analytics: a case study

Purpose The purpose of this paper is to describe an agile approach to academic analytics that is currently being applied on one of the campuses of a leading higher educational institution in the Caribbean. This agile approach enables the rapid development of a strategic analytics roadmap and proof-of-concept analytics applications for the institution. Design/methodology/approach The approach was developed using Design Science which involves the development and rigorous evaluation of an artifact. The agile approach is the artifact and the design evaluation was done using the observational method of primary cases studies where the artifact is studied in depth in a business environment, in this case this was a leading higher educational institution in the Caribbean. Findings The final output, the roadmap, highlights the importance of a balanced portfolio of analytics initiatives, relevant and tailored to the institution’s specific context that includes technology and applications projects, as well as capacity building, organizational structures and policy initiatives. Research limitations/implications The approach that was used and the specific techniques proposed can be extended by other researchers and in so doing will increase the body of research as it relates to agile analytics. Practical implications The approach will be beneficial to educational institutions that are considering how best to harness the strategic value of its data. The analytics roadmap will allow the institution to be clear about the path they should take to maximize their investments in analytics initiatives. Originality/value A number of existing well-accepted research techniques have been synthesized in the development and application of this agile approach. The approach and final roadmap consider the institution’s readiness for and understanding of what is involved in analytics before investing significant resources in its adoption.

An Actor Network Perspective of Tourism Open Data

Abstract This chapter explores the data exchange relationships between stakeholders in a tourism domain as a means of assessing the potential application of open data initiatives. Social network analysis is utilized to analyze network relationships and explain the pattern and consequences of these relationships. Based on centrality and other network attributes, the analysis highlights the key influencers in the tourism data ecosystem examined, and suggests that initial steps towards implementing a tourism open data policy should focus on opening up tourism asset data, and relaxing current restrictive data exchange practices. The agency with responsibility for collecting and disseminating tourism asset data, is well positioned to become the data broker in an emergent tourism open data ecosystem.