1,720,958 research outputs found
A new approach to categorising personal data to increase transparency under the obligation to inform
No full textThis thesis contributes to the field of privacy and data protection law, within both Law and Computer Science, by helping to better understand how to increase the transparency of personal data processing and to categorise personal data. To counter the threat to the privacy of individuals which increasing advancements in Information Technology have created, Data Protection laws have been introduced, which include the key principle of transparency. However, as the de facto method of compliance with the obligation to inform (which mandates the provision of certain information about personal data processing to individuals), Privacy Policies have continuously been criticised in their ability to make processing transparent. This problem makes the study of how to increase the transparency of personal data in the context of providing information to individuals about the processing of their personal data a key research area in both Law and Computer Science. In researching this problem, this thesis begins by highlighting a gap in the current literature due to the assumption that the problem lies in how information about processing is presented, summarised or communicated, rather than questioning what information is required for processing to be transparent. The finding that Social Networking Sites provided information about the specific personal data they processed in their Privacy Policies, despite the UK data protection Regulator not making this a recommendation led to the next contribution, a critical analysis of the previous and current data protection law of the EU and the UK on when it is a requirement to inform individuals about the specific personal data being processed. This analysis highlighted that despite its benefits in increasing transparency, organisations are not always required to provide information about the specific personal data they process under the obligation to inform and where they are, the term ‘category’ is used to differentiate between personal data, without a complete categorisation or sufficient guidance on how to do this beyond the categorisation of ‘Special Categories’ of personal data. This gap has led to various parties inferring categorisations from the law, or creating their own, without following a categorisation methodology or taking a consistent approach. The result is inconsistent approaches to categorisation of personal data, which fail to achieve the aims of the principle of transparency. The final contribution of this thesis is a proposed categorisation of personal data, based on categorisation methodology and the Data Information Knowledge Wisdom model in Computer Science, which aims to support organisations in increasing the transparency of their personal data processing and can be built upon in the future to support compliance with the Framework’s wider compliance requirements
Nobody puts data in a corner? Why a new approach to categorising personal data is required for the obligation to inform
No full textTransparency is a key principle of EU data protection law and the obligation to inform is key to ensuring transparency. The purpose of this obligation is to provide data subjects with information that allows them to assess the compliance and trustworthiness of the data controller. Despite the benefits of categorising personal data for this purpose, a coherent and consistent approach to doing so under the obligation to inform has not emerged. It is unclear what a ‘category’ of personal data is and when this information must be provided. This results in reduced transparency for data subjects and uncertainty for data controllers regarding their legal obligations, defeating the purpose of this obligation. This article highlights these issues and calls for clarification on them. It also posits that in clarifying the law, a new approach to categorising personal data is required, to achieve the benefits of categorisation and increase the transparency of personal data processing for data subjects
An extended investigation of the similarity between privacy policies of social networking sites as a precursor for standardization
No full textPrivacy policies are unsatisfactory in communicating information to users. Social networking sites (SNS) exemplify this, attracting growing concerns regarding their use of personal data, whilst lacking incentives to improve their policies. Standardization addresses many of these issues, but is only possible if policies share attributes that can be standardized. This investigation assessed the similarity of two attributes (the clauses and the coverage of forty recommendations made by the UK Information Commissioner) between the privacy policies of the six most frequently visited SNS globally. Similarity was also investigated by looking at whether any recommendations were not addressed by all SNS and if there were any themes of information discussed in the policies, but not included in the ICO Code. We found that similarity in the clauses was low, yet similarity in the recommendations covered was high. This indicates that SNS use different clauses, but to convey similar information. There were a number of recommendations which none of the SNS addressed. There were also four themes of information which all six SNS addressed, which were not recommended in the ICO Code. This paper proposes the policies of SNS already share attributes, indicating the feasibility of standardization at a thematic level currently. Five recommendations are made to begin facilitating this
Investigating similarity between privacy policies of social networking sites as a precursor for standardization
Full text linkThe current execution of privacy policies, as a mode of communicating information to users, is unsatisfactory. Social networking sites (SNS) exemplify this issue, attracting growing concerns regarding their use of personal data and its effect on user privacy. This demonstrates the need for more informative policies. However, SNS lack the incentives required to improve policies, which is exacerbated by the difficulties of creating a policy that is both concise and compliant. Standardization addresses many of these issues, providing benefits for users and SNS, although it is only possible if policies share attributes which can be standardized. This investigation used thematic analysis and cross- document structure theory, to assess the similarity of attributes between the privacy policies (as available in August 2014), of the six most frequently visited SNS globally. Using the Jaccard similarity coefficient, two types of attribute were measured; the clauses used by SNS and the coverage of forty recommendations made by the UK Information Commissioner’s Office. Analysis showed that whilst similarity in the clauses used was low, similarity in the recommendations covered was high, indicating that SNS use different clauses, but to convey similar information. The analysis also showed that low similarity in the clauses was largely due to differences in semantics, elaboration and functionality between SNS. Therefore, this paper proposes that the policies of SNS already share attributes, indicating the feasibility of standardization and five recommendations are made to begin facilitating this, based on the findings of the investigation
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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