Data Processing Practices Research Articles

Transformation from total-field magnetic anomaly to the projection of the anomalous vector onto the normal geomagnetic field based on an optimization method

The total-field magnetic anomaly [Formula: see text] is approximated as the component [Formula: see text] of the anomalous vector [Formula: see text] along the direction of the normal geomagnetic field. It is widely used in magnetic data processing and interpretation practices as a routine if [Formula: see text] is relatively small. But in highly magnetic environments, the distinction between [Formula: see text] and [Formula: see text] is often too large to be ignored. We carefully investigate the difference between [Formula: see text] and [Formula: see text] and find that it will increase rapidly in the trend of the quadratic function as [Formula: see text] strengthens. We also test the effects of approximation on the component transformation and reduction to the pole on a synthetic single-sphere model. As expected, the error caused by inaccurate information will propagate into subsequent data processing procedures and adversely affect the results. Therefore, we have developed an optimization strategy based on the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm to transform the total-field anomaly into [Formula: see text]. First, we have constructed an objective function after transforming [Formula: see text] into [Formula: see text] through the component transformation in the frequency domain. Then, using [Formula: see text] as the initial value of [Formula: see text], [Formula: see text] is calculated iteratively by the L-BFGS algorithm. To test the validity of the optimization algorithm, [Formula: see text] is transformed for noise-free and noise-corrupted models and models with a background field. The synthetics indicate that the transformed [Formula: see text] is almost the same as the model [Formula: see text], whose maximum error is approximately one-hundredth (30 nT) of the difference (8000 nT) between the modeled [Formula: see text] and [Formula: see text]. The synthetics and field data example from the Yangshan Iron Mine, Fujian Province, southern China, also indicate that the data transformation and forward-modeling results can benefit from the direct use of transformed [Formula: see text] instead of [Formula: see text].

Facebook’s Anticompetitive Lean in Strategies

Facebook is under fire on several fronts and with good reason. Regulators strive to make sense of and address a plethora of seemingly unrelated issues that arise from the operation of its platform. These range from antitrust, privacy violations, dissemination of harmful content and speech, deception and polarisation to political manipulation. This paper identifies Facebook’s unrestricted and excessive data collection as a unifying theme that requires immediate antitrust action. Once a privacy-oriented social network, Facebook soon mutated into a surveillance machine designed to hoover people’s personal data to identify and understand people’s interests, preferences and emotions and turn that knowledge into profit through the sale of targeted ads. Since people’s innate preference for privacy stood in the way of Facebook’s growth, Facebook resorted to privacy intrusions and deception to access as much user data as possible, thereby gaining market power. Currently, its overwhelming dominant position in the social media market means that no matter how much data Facebook extracts from users, how transparent its information about its data processing practices is and how many privacy scandals ensue from its reckless handling of data, users have nowhere else to go. This paper provides a course of action to correct this unacceptable anticompetitive outcome. The imposition of unfair commercial terms on consumers, the distortion of the competitive process through privacy violations and misleading practices, the squeezing of news publishers’ traffic and foreclosure of actual and potential competitors by Facebook, can be stopped. A combination of data and consumer protection measures alone cannot stop Facebook’s actions, but antitrust enforcement can be used to curb Facebook’s ability to reinforce its data-driven abuse of its market power.

The impact of transparency on mobile privacy decision making

Smart devices provide unprecedented access to users’ personal information, on which businesses capitalize to offer personalized services. Although users must grant permission before their personal information is shared, they often do so without knowing the consequences of their decision. Based on the EU General Data Protection Regulation, which mandates service providers to comprehensively inform users about the purpose and terms of personal data processing, this article examines how increased transparency regarding personal data processing practices in mobile permission requests impact users in making informed decisions. We conducted an online experiment with 307 participants to test the effect of transparency on users’ decisions about and comprehension of the requested permission. The results indicate increased comprehension of data processing practices when privacy policies are transparently disclosed, whereas acceptance rates do not vary significantly. We condense our findings into principles that service providers can apply to design privacy-transparent mobile apps.

Convergence analysis of distributed stochastic gradient descent with shuffling

When using stochastic gradient descent (SGD) to solve large-scale machine learning problems especially deep learning problems, a common practice of data processing is to shuffle the training data, partition the data across multiple threads/machines if needed, and then perform several epochs of training on the re-shuffled (either locally or globally) data. The above procedure makes the instances used to compute the gradients no longer independently sampled from the training data set, which contradicts with the basic assumptions of conventional convergence analysis of SGD. Then does the distributed SGD method have desirable convergence properties in this practical situation? In this paper, we give answers to this question. First, we give a mathematical formulation for the practical data processing procedure in distributed machine learning, which we call (data partition with) global/local shuffling. We observe that global shuffling is equivalent to without-replacement sampling if the shuffling operations are independent. Second, we prove SGD with global shuffling and local shuffling has convergence guarantee for non-convex tasks like deep learning. The convergence rate for local shuffling is slower than that for global shuffling, since it will lose some information if there’s no communication between partitioned data. We also consider the situation when the permutation after shuffling is not uniformly distributed (We call it insufficient shuffling), and discuss the condition under which this insufficiency will not influence the convergence rate. Finally, we give the convergence analysis in convex case. An interesting finding is that, the non-convex tasks like deep learning are more suitable to apply shuffling comparing to the convex tasks. Our theoretical results provide important insights to large-scale machine learning, especially in the selection of data processing methods in order to achieve faster convergence and good speedup. Our theoretical findings are verified by extensive experiments on logistic regression and deep neural networks.

The Role of Human Dignity in Processing (Health) Data Building on the Organ Trade Prohibition

The datafication, commodification and commercialization of our existence as an inevitable part of the online infrastructure of today, not only affects our privacy but it goes deeper by touching upon even more fundamental conditions of being human. In this chapter, bio-medical regulations prohibiting the trade of human body parts are explored to see whether the non-commercialization principle in these laws is helpful in assessing data processing practices. An analogy between data processing and organ trade may help us to develop a new perspective on what constitutes improper commercial use of personal data and find ways to prohibit (reprehensible aspects of) the trade in personal data. We propose to reorient the debate on data processing by introducing the notion of human dignity as constraint into the discussion. A prohibition of personal data commercialism (analogous to a prohibition of transplant commercialism) could contribute to a more future-proof regulation of data processing activities.

Some Reflections on Dignity as an Alternative Legal Concept in Data Protection Regulation

AbstractAs the use of the Internet and online platforms grows, the scale of collecting and processing personal data and turnovers have increased correspondingly.1At the same time, public awareness about the Internet turning into a genuine profiling and advertisement machine, as well as a powerful surveillance instrument, grows. More people today are concerned about the ways in which public and private actors store and use private information. Many individuals note that they lose sight of the consequences once they give consent to the collection of their sometimes most intimate personal data. The Snowden revelations and the recent Facebook and Cambridge Analytica scandal have only reinforced this public awareness.Objections against these data processing practices cannot be explained as breaches of data protection or privacy regulation alone. In this Article, it is argued that recently passed regulations fail to solve the unease of data subjects as other, more fundamental values are at stake here. A different or complementary ethical and legal framework is needed to interpret this generally felt unease vis-à-vis current data practices and secondly to confront future developments on the data market. The concept of human dignity may be a helpful perspective in this respect. In the context of data processing, human dignity is generally interpreted in a quite specific manner, such as contributing to the empowerment and self-determination of autonomous individuals. It can be argued, however, that human dignity—in the context of the commodification and commoditization of online personal data—should be seen in a different, quite opposite, light. In sum, future regulation of privacy and data protection attention should shift towards more constraining dimensions of human dignity.

Shattering one-way mirrors – data subject access rights in practice

The right of access occupies a central role in EU data protection law's arsenal of data subject empowerment measures. It can be seen as a necessary enabler for most other data subject rights as well as an important role in monitoring operations and (en)forcing compliance. Despite some high-profile revelations regarding unsavoury data processing practices over the past few years, access rights still appear to be underused and not properly accommodated. It is especially this last hypothesis we tried to investigate and substantiate through a legal empirical study. During the first half of 2017, around sixty information society service providers were contacted with data subject access requests. Eventually, the study confirmed the general suspicion that access rights are by and large not adequately accommodated. The systematic approach did allow for a more granular identification of key issues and broader problematic trends. Notably, it uncovered an often-flagrant lack of awareness; organisation; motivation; and harmonisation. Despite the poor results of the empirical study, we still believe there to be an important role for data subject empowerment tools in a hyper-complex, automated and ubiquitous data-processing ecosystem. Even if only used marginally, they provide a checks and balances infrastructure overseeing controllers' processing operations, both on an individual basis as well as collectively. The empirical findings also allow identifying concrete suggestions aimed at controllers, such as relatively easy fixes in privacy policies and access rights templates.

Employers as Nightmare Readers: An Analysis of Ethical and Legal Concerns Regarding Employer-Employee Practices on SNS

AbstractThe aim of this interdisciplinary paper is to study the social reality surrounding the data processing practices employers and employees engage in on social networking sites (SNS). Considering the lack of empirical studies, as well as the considerable uncertainty in the way personal data protection is implemented across the European Union (EU), the paper offers insights on the topic. Qualitative text analysis of semi-structured interviews with employers from the service sector (N=10) and the field of media and communication (N=15), as well as employers from organisations which had experienced various problems due to things their employees had posted on social media (N=14), and employees from the financial sector (N=15) were carried out to explore whether the data protection principles, which can be viewed as the most important guidelines for employers in the EU, are actually followed in their everyday SNS data processing practices. Even though the data protection principles emphasise the need for fair, purposeful, transparent, minimal and accurate processing of personal data, our interviews with employers and employees reveal that the actual SNS processing practices rarely live up to the standards. Our findings indicate that there is a growing mismatch between the social reality and legal requirements regarding data subjects.

Computation of adherence to medication and visualization of medication histories in R with AdhereR: Towards transparent and reproducible use of electronic healthcare data

Adherence to medications is an important indicator of the quality of medication management and impacts on health outcomes and cost-effectiveness of healthcare delivery. Electronic healthcare data (EHD) are increasingly used to estimate adherence in research and clinical practice, yet standardization and transparency of data processing are still a concern. Comprehensive and flexible open-source algorithms can facilitate the development of high-quality, consistent, and reproducible evidence in this field. Some EHD-based clinical decision support systems (CDSS) include visualization of medication histories, but this is rarely integrated in adherence analyses and not easily accessible for data exploration or implementation in new clinical settings. We introduce AdhereR, a package for the widely used open-source statistical environment R, designed to support researchers in computing EHD-based adherence estimates and in visualizing individual medication histories and adherence patterns. AdhereR implements a set of functions that are consistent with current adherence guidelines, definitions and operationalizations. We illustrate the use of AdhereR with an example dataset of 2-year records of 100 patients and describe the various analysis choices possible and how they can be adapted to different health conditions and types of medications. The package is freely available for use and its implementation facilitates the integration of medication history visualizations in open-source CDSS platforms.

Systematic Approaches for Signal Processing of Soil Shaking Table Test

Selecting an appropriate methodology in signal processing of shaking table test is of fundamental importance for evaluating the soil dynamic parameters. This paper presents the systematic approaches in selecting an appropriate signal processing method for a soil shaking table test. A soil model of 150 mm in diameter and 100 mm in height was tested on a 1g shaking table. The soil model was instrumented with accelerometers to measure the resultant accelerations under different shaking motions. Under normal data processing practices, the acceleration data was adjusted and numerically integrated to obtain the linear displacement data. However, the accuracy and reliability of the computed displacement data and the adopted adjustment technique often raise arguments. In the present study, the acceleration data was subjected to two baseline correction schemes and one method of digital band-pass filtering. The results from the three signal processing methods were compared with the actual displacement data obtained from a direct measurement using laser displacement sensor. Bandpass filtering method was found to be a more reliable data processing method in this particular study. The use of laser displacement sensor can serve as a useful reference when choosing an appropriate adjustment scheme in data processing.

Development of a Safety Inspection Framework on Construction Sites Using Mobile Computing

AbstractSite safety inspection is an essential task to ensure that construction operations are carried out in a safe manner, in accordance with relevant health and safety policies and standards of a particular jurisdiction. It is also critical to the smooth execution, monitoring, and controlling of construction activities. The evidence gathered from construction experts as well as from previous studies suggests that the efficiency and effectiveness of current inspection processes are less than satisfactory. This paper reports an Australian research project that develops an innovative safety inspection approach to incorporate mobile computing technologies into safety inspection processes in order to facilitate more effective data collection, processing, and control practices. The paper also discusses the interview results of safety practitioners about the proposed inspection approach. The approach was implemented through the development and test of a prototype mobile inspection tool. The feasibility and us...

The new privacy guidelines of the OECD: what changes for businesses?

OECD Guidelines governing the protection of privacy and transborder flows of personal data, see the Annex to the Recommendation of the Council concerning Guidelines governing the Protection of Privacy and Transborder Flows of Personal Data (2013). C(80)58/FINAL, as amended on 11 July 2013 by C(2013)79. The revised OECD Privacy Guidelines are indicative of a trend to increased accountability of businesses in the area of data protection which will ultimately require many companies to revise their data-processing practices (including in the area of competition law investigations and compliance programmes) and privacy governance frameworks. In 1980, the OECD adopted a set of eight basic privacy principles. Today, these principles are reflected in all relevant general data protection frameworks worldwide, including the EU's Data Protection Directive 95/46/EC,1 the EU-US Safe Harbour framework2 and the APEC Privacy Framework. The OECD's Guidelines governing the protection of privacy and transborder flows of personal...

Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

Cloud computing techniques take the form of distributed computing by utilizing multiple computers to execute computing simultaneously on the service side. To process the increasing quantity of multimedia data, numerous large-scale multimedia data storage computing techniques in the cloud computing have been developed. Of all the techniques, Hadoop plays a key role in the cloud computing. Hadoop, a computing cluster formed by low-priced hardware, can conduct the parallel computing of petabytes of multimedia data. Hadoop features high-reliability, high-efficiency, and high-scalability. The numerous large-scale multimedia data computing techniques include not only the key core techniques, Hadoop and MapReduce, but also the data collection techniques, such as File Transfer Protocol and Flume. In addition, distributed system configuration allocation, automatic installation, and monitoring platform building and management techniques are all included. As a result, only with the integration of all the techniques, a reliable large-scale multimedia data platform can be offered. In this paper, we introduce how cloud computing can make a breakthrough by proposing a multimedia social network dataset on Hadoop platform and implementing a prototype version. Detailed specifications and design issues are discussed as well. An important finding of this article is that we can save more time if we conduct the multimedia social networking analysis using Cloud Hadoop Platform rather than using a single computer. The advantages of cloud computing over the traditional data processing practices are fully demonstrated in this article. The applicable framework designs and the tools available for the large-scale data processing are also proposed. We show the experimental multimedia data including data sizes and processing time.

Who decides on the future of data protection? Role of law firms in shaping European data protection regime

Drawing on theories of European integration and governance and sociological studies on the influence of elite law firms on rule-setting, this paper shows that law firms (a) operate in the area of data protection that is of extreme complexity and requires expert knowledge; and (b) display characteristics similar to other actors who succeeded in influencing agenda-setting and the results of policy-making despite having no formal competence to do so. This article proposes a hypothesis of the influence of elite law firms in EU data protection rule-setting. It argues that the EU data protection sector is prone to such influence as it is by definition transnational and, at some technical and some core points, inadequate to reflect the real data processing practices and therefore is entrenched with uncertainty. Therefore, the research into politics of data protection in Europe cannot disregard the role of these actors in shaping the European data protection regime.

Much Ado about Cookies: The European Debate on the New Provisions of the ePrivacy Directive regarding Cookies

Abstract: The fear of losing the privacy of internet users' personal data and of unfair data processing practices may lead to internet users staying off the internet and, therefore, not participating in online transactions. The European Commission wants to encourage internet users to conclude more online cross-border transactions that would strengthen the internal market. As a result, new provisions of the ePrivacy Directive regarding cookies aim to ensure the right to online privacy and to protect internet users from unfair data processing practices. Whether these goals will be reached depends on the character of the adopted provisions, i.e., whether they actually ensure the right to online privacy of internet users. Furthermore, proper and uniform implementation of these provisions by the Member States is needed in order to improve internet users' confidence that they receive the same level of protection of their right to online privacy across borders. This paper assesses the feasibility of these provisions contributing to the increased confidence of internet users in concluding online transactions, taking into account the implementation measures adopted by two Member States, the Netherlands and the UK, as well as consumer behaviour research findings. Résumé: La crainte de compromettre la confidentialité des données personnelles des utilisateurs d'internet, ainsi que de l'exploitation déloyale de ces données pourrait dissuader les utilisateurs à utiliser internet et, par conséquence, à éviter de réaliser des transactions en ligne. La Commission européenne souhaite d'encourager les internautes à effectuer davantage de transactions transfrontalières afin de renfoncer le marché intérieur. Ainsi, les nouvelles dispositions de la directive Vie Privée ou ePrivacy au regard des cookies visent à garantir le droit à la vie privée en ligne et à protéger les internautes de l'exploitation déloyale de leurs données personnelles. La réalisation de ces objectifs dépend du caractère des dispositions prises, à savoir verifier si celles-ci préservent vraiment le droit à la vie privée des internautes. En outre, la mise en œuvre rigoureuse et uniforme de ces dispositions par les États Membres est nécessaire dans le but d'en rassurer les internautes garantissant les mêmes critères de confidentialité et de protection de leurs données personnelles en ligne au-delà des frontières. Cette étude vise à évaluer l'efficacité de ces dispositions à renforcer la confiance des internautes lorsqu'ils réalisent des transactions en ligne, compte tenu des mesures adoptées par deux États Membres, les Pays-Bas et le Royaume-Uni, ainsi que des conclusions basées sur le comportement des consommateurs.

What happens to my data? A novel approach to informing users of data processing practices

Citizens increasingly use the Internet to buy products or engage in interactions with others, both individuals and businesses. In doing so they invariably share (personal) data. While extensive data protection legislation exists in many countries around the world, citizens are not always aware (enough) of their rights and obligations with respect to sharing (personal) data. To remedy this gap, users ought to become better informed of companies’ data processing practices. In the past, various research groups have attempted to create tools to this end, for example through the use of icons or labels similar to those used in nutrition. However, none of these tools have gained extensive adoption, mostly because it turns out that capturing privacy legislation in simple, accessible graphics is a complicated task. Moreover, we believe that the tools that were developed so far do not align closely enough with the preferences and understanding of ordinary users, precisely because they are too ‘legalistic’.
 
 In this paper we discuss a user study conducted to gain a better understanding of the kinds of information users would wish to receive with respect to companies’ data processing practices, and the form this information ought to take. On the basis of this user study we found a new approach to communicating this information, in which we return to the OECD’s Fair Information Principles, which formed the basis for (almost all) data protection legislation. We end the paper with a rudimentary proposal for an end user tool to be used on companies’ Web sites.

Much Ado About Cookies: The European Debate on the New Provisions of the Eprivacy Directive Regarding Cookies

The fear of losing the privacy of internet users' personal data and of unfair data processing practices may lead to internet users staying off the internet and, therefore, not participating in online transactions. The European Commission wants to encourage internet users to conclude more online cross-border transactions that would strengthen the internal market. As a result, new provisions of the ePrivacy Directive regarding cookies aim to ensure the right to online privacy and to protect internet users from unfair data processing practices. Whether these goals will be reached depends on the character of the adopted provisions, i.e., whether they actually ensure the right to online privacy of internet users. Furthermore, proper and uniform implementation of these provisions by the Member States is needed in order to improve internet users' confidence that they receive the same level of protection of their right to online privacy across borders. This paper assesses the feasibility of these provisions contributing to the increased confidence of internet users in concluding online transactions, taking into account the implementation measures adopted by two Member States, the Netherlands and the UK, as well as consumer behaviour research findings.

The Inverse Relationship between Secrecy and Privacy

In civil libertarian discourse, the inverse relationship between government secrecy and privacy is well recognized and widely acknowledged - so widely, in fact, that it can come to seem as though we might regain sufficient privacy simply by cabining official secrecy. But regimes of secrecy that insulate private-sector data processing practices also contribute materially to the decline of privacy, and indeed play a vital role in facilitating government efforts to make citizens' lives transparent. In addition, there is an inverse relationship between openness and privacy that we are inclined to resist discussing. When, for example, a government agency posts on its website documents containing private information about individual citizens, or when a social networking service establishes default rules for transmitting information from member pages to commercial partners, openness contributes materially to the exposure that people experience. Our public discourse about information policy reinforces the devaluation of privacy in two opposite but mutually-reinforcing ways, by valorizing political economies organized around secrecy and by elevating openness as an ultimate good. The shelter that privacy affords for self-development is essential to a healthy democracy. It is therefore important to interrogate both our regimes of secrecy and our discourses about openness.

The Problems of Budgeting and Financial Decision Process

Many companies recognize that the traditional annual budget (produced near yearend and then used as a guide for the following year even though it is out of date) is just not good enough. Instead, they are turning to alternative budgets (forecasts) that are updated every few months. They impose new requirements on financial decision-making. Management must access and process information more quickly, and this often means a change of the current practice of data collection and processing or even acquiring special software to do the job. The budgeting process and financial decisions can be accelerated and improved in several ways, and the paper deals with advantages and disadvantages of the possible ways.

Study and practice of wide-angle seismic data processing

This paper presents the special processing methods used for wide-angle land seismic data through both theoretical study and model testing. They are different from conventional ones in the following aspects: separation of reflection and refraction waves, long offset NMO and stacking and forward modeling and inversion. These processing techniques have been applied for the first time to land seismic data from Liaohe areas, resulting in greatly improved quality of the deep formation and better imaging of the shallow layer obtained in the volcanic-shielded area. Wide-angle reflection and refraction seismic surveys were carried out in the Liaohe area using the maximum offset of 6500m and with the target around 2000ms. In the processing, we adopted the τ ∼p transform and the high-order normal moveout correction.