RADAR: Resilient Application for Dependable Aided Reporting

Many organizations must produce many reports for various reasons. Although this activity could appear simple to carry out, this fact is not at all true: indeed, generating reports requires the collection of possibly large and heterogeneous data sets. Furthermore, different professional figures are involved in the process, possibly with different skills (database technicians, domain experts, employees): the lack of common knowledge and of a unifying framework significantly obstructs the effective and efficient definition and continuous generation of reports. This paper presents a novel framework named RADAR, which is the acronym for “Resilient Application for Dependable Aided Reporting”: the framework has been devised to be a ”bridge” between data and employees in charge of generating reports. Specifically, it builds a common knowledge base in which database administrators and domain experts describe their knowledge about the application domain and the gathered data; this knowledge can be browsed by employees to find out the relevant data to aggregate and insert into reports, while designing report layouts; the framework assists the overall process from data definition to report generation. The paper presents the application scenario and the vision by means of a running example, defines the data model and presents the architecture of the framework.

Specifics of nature of the biometric data definition in law of the European Union

The article offers analysis of the approaches in Russian and European legal doctrine to the definition of “biometric data”, as well as the evolution of the legal definition formation of biometric data in the legislative acts of the EU. The article analyzes the role of biometric data in the personal data system, their characteristics, and the determination of a list of key features that allow an individual's data to be classified as biometric data. Special attention is paid to the list of characteristics that fall under the category of biometric data in accordance with existing scientific approaches on personal data, as well as the provisions of the General Data Protection Regulation. The article highlights the main problems of interpretation of the category of biometric data in legal sources, and also suggests the author's legal definition of biometric data that meets, in the author's opinion, the main criteria that characterize specific data of an individual as biometric.

Methods of big data definition: Russian and foreign experience

This article explores the main approaches of Russian and foreign authors towards big data definition; reflects the classification of data, components of big data; and provides comparative characteristics to legal regulation of big data. The subject of this research is the legislation of the Russian Federation and legislation of the European Union that regulate the activity on collection, processing and use of big data, personal data and information; judicial and arbitration practice of the Russian Federation in the sphere of personal data; normative legal acts of the Russian Federation; governmental regulation of the Russian Federation and foreign countries in the area of processing, use and transmission of data; as well as legal doctrine in the field of research dedicated to the nature of big data. The relevance of this research is substantiated by the fact that there is yet no conceptual uniformity with regards to big data in the world; the essence and methods of regulating big data are not fully explored. The goal of this research is determine the legal qualification of the data that comprise big data. The task lies in giving definition to the term “big data”; demonstrate the approaches towards determination of legal nature of big data; conduct  classification of big data; outline the criteria for distinguishing data that comprise the concept of big data; formulate the model for optimal regulation of relations in the process of activity on collection, processing, and use of the data. The original definition of big data in the narrow and broad sense is provided. As a result, the author distinguishes the types of data, reflects the legal qualification of data depending on the category of data contained therein: industrial data, user data, and personal data. Attention is also turned to the contractual form of big data circulation.

PORTABILITY OF CARTOGRAPHIC SYMBOLS LIBRARY FOR OPEN STANDARDS

The Geological Survey of Brazil has a library of palaeontology symbols to use in geological mapping works, currently in bitmap format and adapted for ESRI platform. This type of representation has presented anti-aliasing problems when reduced, in addition to not being suitable for map presentation on the web, according to OGC (Open Geospatial Consortium) specifications. This work presents a reproducible method in any symbol library type. The method consists of converting the symbol library to open-source format, resulting an OpenType font file, which can be installed on any operating system and view each symbol font in any software that has this functionality, such as a GIS (Geographic Information Systems) software. The need to develop font construction technique is due to improving typographic quality of cartographic representations and making library compatible with main GIS softwares. Those 61 pictorial palaeontology symbols were converted, one by one, to SVG (Scalable Vector Graphics) format. We imported each symbol as a glyph in FontForge font editor. Major computer platforms use OpenType format due to its wide availability and typographic flexibility, including provisions to deal with diverse characteristics of internationally symbolic alphabet systems. There is even the possibility of symbols standardizing in the UTF-8 alphabet system, an issue for the scientific community to study. The advantage of using the SVG format is its size, a compact text file, and has an excellent compression factor. In addition, version-control repositories, like GitHub, can store SVG files, which would facilitate content management. The adopted method proved to be applicable to any cartographic symbols library with good results. Rendering tests on different platforms (web or desktop) showed no noticeable differences. One of the most important aspects of the method presented in this work was to make cartographic symbols library public and open-source for use by the geoscientific community, regardless whether an open-source or proprietary platform is used, and so, the Geological Survey of Brazil will be able to distribute geological symbology patterns, according to Open Data definition.

Development of a customised data management system for a COVID-19-adapted colorectal cancer pathway

ObjectivesA customised data management system was required for a rapidly implemented COVID-19-adapted colorectal cancer pathway in order to mitigate the risks of delayed and missed diagnoses during the pandemic. We assessed its performance and robustness.MethodsA system was developed using Microsoft Excel (2007) to retain the spreadsheets’ intuitiveness of direct data entry. Visual Basic for Applications (VBA) was used to construct a user-friendly interface to enhance efficiency of data entry and segregate the data for operational tasks.ResultsLarge data segregation was possible using VBA macros. Data validation and conditional formatting minimised data entry errors. Computation by the COUNT function facilitated live data monitoring.ConclusionIt is possible to rapidly implement a makeshift database system with clinicians’ regular input. Large-volume data management using a spreadsheet system is possible with appropriate data definition and VBA-programmed data segregation. The described concept is applicable to any data management system construction requiring speed and flexibility in a resource-limited situation.

How useful are equality indicators? The expressive function of ‘stat imperfecta’ in disability rights advocacy

Background: The measurement of equality is often difficult for groups who are weakly defined or poorly represented in official datasets. Social statistics are an essential component in rights recognition and advocacy because they make protected groups of persons visible and reveal the extent of their inequalities in comparison with population norms.Aims and objectives: This paper examines how disabled persons have been included, or not, in EU statistics used for evidenced-based policy – for example in the European Semester process concerning Member States’ employment and social policies, or in monitoring compliance with international human rights standards under the UN CRPD.Methods: Over a period of a decade we mapped and disaggregated disability data from the main European social surveys, examining the availability and limitations of different sources to answer various policy questions.Findings: The analysis produced indicators revealing stark inequalities between disabled and non-disabled persons but raised challenging questions about data quality, reliability and comparability. This revealed tensions in engaging the trust of policymakers in less familiar, or less reliable, data concerning minority groups.Discussion and conclusions: Despite limitations of precision, imperfect statistics often retain a strong expressive function in human rights promotion. Greater investment is needed from governments and statistical authorities to strengthen disability equality data and indicators concerning marginalised rights holders.<br />Key messages<br /><ul><li>Disability equality has not been mainstreamed very effectively in EU public statistics.</li><br /><li>A wide variety of public data indicate unequal outcomes for disabled people across the EU.</li><br /><li>Statistical weaknesses arise from data definition and from inconsistencies in data collection.</li><br /><li>Despite limitations, imperfect statistics achieved a strong expressive function in rights advocacy.</li></ul>

Linear Kalman-Bucy filter with vector autoregressive signal and noise

The linear Kalman-Bucy filter problem for a system, at that a signal and a noise are vector independent stationary autoregressive processes with orders larger than 1, is investigated. The recurrent equations for filter and its error are delivered. The optimal way of the initial data definition is proposed. Some numerical examples are given. In one of them the algorithm leads to a stationary behavior at infinity. In the other example the Kalman- Bucy filter is impossible because the filter error goes to infinity. A behavior of a signal and its error is illustrated by a simulation of a signal and a noise as vector Gaussian stationary autoregressive processes. The simulation supports theoretical conclusions.