Admission (Topic Data Mining) - Research Proposal Example

Research proposal: Developing a legal and ethical framework for sound data mining January 21, Research proposal: Developing a legal and ethical framework for sound data miningInformation technology has aided data use in different fields in which extraction and analysis of data offer bases for informed decisions and therefore facilitate efficiency in professional activities. Organizations’ desire to have competitive advantage has mediated applications such as data mining that face environmental challenges like morality, reliability, and validity, especially in the absence of legal or ethical governance.

These concerns identify the need to develop a regulatory framework for data mining in order to optimize benefits to all stakeholders. The need has motivated my desire to complete a PhD program on the subject and I believe that your supervision and capacity of your institution offers me the best opportunity to complete the program and to develop and influence implementation of the proposed framework. Literature reviewExisting literature identifies significance and challenges of data mining. Search techniques ensure availability of data for mining purposes (Weber and Horn 2013, p. 31), and this suggests ease of data mining and its popularity in organizations.

FinancialPro.org is an example of sites that aid data search and its efficiency in availing data is a threat to data privacy and security. Roles of applications such as NoSQL in transforming data management also identify the need for “governance and stewardship” in operating data (Stiglich 2014, p. 22). Until the year 2013, according to Chen, et al (2013, p. 908), the available technique for ensuring privacy of data in data mining was inefficient and destroyed original data. While ensuring privacy achieved an ethical objective in data use, destroying original data established threats to reliability and validity of availed data.

A new approach, which could be subject to other weaknesses, was therefore proposed. Current laws also identify a gap in regulating data mining because even though privacy laws exist, the scope of electronic data, especially data third parties possesses, undermines effectiveness of privacy laws. The United States’ fourth amendment suffers this weakness (Harvard Law Review 2014, p. 691) and situations in other countries such as Oman and Singapore suggest lack of suitable legal frameworks across many countries (Chesterman 2014, p. 51). While privacy establishes legal and ethical concerns over data mining, benefits of data mining are necessary for the contemporary environment.

Moderating use of data mining is the solution and implementing the study will aid this. The following research question will be investigated.What legal and ethical frameworks are necessary for effective data mining?MethodologyA mixed research method is proposed for the study. Interviews will be used to collect quantitative data on data mining usage, associated benefits and ethical and legal issues that organizations face due to usage. Focus groups, consisting of information technology experts, legal experts, and human rights activists will be used to collect qualitative data.

Data analysis will focus on understanding legal and ethical issues facing data mining, benefits of data mining, and possible solutions for effective and acceptable data mining strategies. The research proposal will also aid my long-term interests in information technology and its effects on the society. I look forward to your consideration that will help me achieve my academic, professional, and social objectives.Reference listChen, T et al 2013, ‘Reversible privacy preserving data mining: A combination of difference expansion and privacy preserving,’ Journal of Supercomputing, Vol. 66, No. 2, pp. 907-917. Chesterman, S 2014, Data protection law in Singapore: Privacy and sovereignty in an interconnected world, Academy Publishing, Singapore.

Harvard Law Review 2014, ‘Data mining, dog sniffs, and the Fourth Amendment,’ Harvard Law Review, Vol. 128, No. 2, pp. 691-712.Stiglich, P 2014, ‘Data modeling in the age of big data,’ Business Intelligence Journal, Vol. 19, No. 4, pp. 17-22. Weber, R and Horn, B 2013, ‘“Data Mining” for golden nuggets at financialpro.org,’ Journal of Financial Service Professionals, Vol. 67, No. 6, pp. 31-34.