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    Usage of the digital economy information infrastructure to improve the quality of statistical data

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    Statistics agencies are the main data provider on the economic position of the macroeconomic level. Most economic decisions on a national scale are based on statistical data. Data processing is a key business process for statistical agencies. At the same time, the quality of statistical data supplied by Rosstat is not always high enough. There are adjustments, a discrepancy between data sets describing the same economic phenomenon is revealed. The purpose of the work is to describe the methods of collecting and processing statistical information that will contribute to improving the quality of the presented data. From the information point of view, the statistical agency is engaged in the organization of information exchange between data providers and consumers, acts as a data aggregator. To organize the information exchange within community you need to create a semantic space to ensure the meaningful filling of the data. The main role in the semantic space is played by the identifiers of objects. The article considers the unified identifiers of statistical accounting objects as a method of collecting and processing statistical information and improving its quality. The international statistical practice use methods of standardizing the turnover of statistical data. Information standards are designed to unify identifiers and namespace for participants of the statistical information turnover and to provide a single semantic space. If you use of unified identifiers, the procedures for processing statistical data become transparent, it allow you grouping by different sections, as well as decomposition of aggregated data into components.The results of the work are recommendations on the use of Core component of the information infrastructure for the collection and analysis of statistical data. In the existing information infrastructure of the Russian digital economy, there are a number of data sources, the use of which will improve the quality of collection and processing of statistical data. To create a semantic space of statistical data in the Russian Federation, the most important section is the registers of Core Components. The use of registers will allow you to organize the binding of statistical data from different domains, as well as to implement the link of aggregated data with microdata. Significant progress is observed in the marking of goods, which allows you to track object’s movement through all stages of the life cycle, as well as the location. The government of the Russian Federation initiated a project on labeling of goods, and this information gives an opportunity to get a clear picture of a significant part of the economy. An additional information source of statistical data can be the corporate sector, where actively used tracking systems that monitor the goods, vehicles, containers, warehousing.Conclusion: There are several options for creation of the semantic space for statistical data. World experience is guided by the use of the Web architecture, which involves the technological identifiers. Semantics of statistical data can be ensured by using the potential of the information infrastructure, which will solve a number of problems of statistical accounting

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

    Использование информационной инфраструктуры цифровой экономики для повышения качества статистических данных

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    Statistics agencies are the main data provider on the economic position of the macroeconomic level. Most economic decisions on a national scale are based on statistical data. Data processing is a key business process for statistical agencies. At the same time, the quality of statistical data supplied by Rosstat is not always high enough. There are adjustments, a discrepancy between data sets describing the same economic phenomenon is revealed. The purpose of the work is to describe the methods of collecting and processing statistical information that will contribute to improving the quality of the presented data. From the information point of view, the statistical agency is engaged in the organization of information exchange between data providers and consumers, acts as a data aggregator. To organize the information exchange within community you need to create a semantic space to ensure the meaningful filling of the data. The main role in the semantic space is played by the identifiers of objects. The article considers the unified identifiers of statistical accounting objects as a method of collecting and processing statistical information and improving its quality. The international statistical practice use methods of standardizing the turnover of statistical data. Information standards are designed to unify identifiers and namespace for participants of the statistical information turnover and to provide a single semantic space. If you use of unified identifiers, the procedures for processing statistical data become transparent, it allow you grouping by different sections, as well as decomposition of aggregated data into components.The results of the work are recommendations on the use of Core component of the information infrastructure for the collection and analysis of statistical data. In the existing information infrastructure of the Russian digital economy, there are a number of data sources, the use of which will improve the quality of collection and processing of statistical data. To create a semantic space of statistical data in the Russian Federation, the most important section is the registers of Core Components. The use of registers will allow you to organize the binding of statistical data from different domains, as well as to implement the link of aggregated data with microdata. Significant progress is observed in the marking of goods, which allows you to track object’s movement through all stages of the life cycle, as well as the location. The government of the Russian Federation initiated a project on labeling of goods, and this information gives an opportunity to get a clear picture of a significant part of the economy. An additional information source of statistical data can be the corporate sector, where actively used tracking systems that monitor the goods, vehicles, containers, warehousing.Conclusion: There are several options for creation of the semantic space for statistical data. World experience is guided by the use of the Web architecture, which involves the technological identifiers. Semantics of statistical data can be ensured by using the potential of the information infrastructure, which will solve a number of problems of statistical accounting.Официальная статистика является основным поставщиком данных об экономическом состоянии макроэкономического уровня, на основе статистических данных принимается большинство экономических решений государственного масштаба. Работа с данными для органов статистики является ключевым бизнес-процессом. Вместе с тем уровень качества статистических данных, поставляемых Росстатом, не всегда оказывается достаточно высоким. Наблюдаются корректировки статистических данных, выявляются несоответствие между наборами данных, описывающих одно и то же экономическое явление.Целью работы является описание методов сбора и обработки статистической информации, которые будут способствовать повышению качества поставляемых данных. С информационной точки зрения статистическое агентство занимаются  организацией информационного обмена между поставщиками данных и потребителями, выступает агрегатором данных. Для организации информационного обмена в рамках сообщества пользователей создается семантическое пространство, призванное обеспечить смысловое наполнение данных. Основную роль в создании семантического пространства играют идентификаторы объектов учета. В качестве методов сбора и обработки статистической информации и повышения ее качества в статье рассматриваются использование единых идентификаторов отдельных объектов статистического учета. В международной статистической практике применяются методы стандартизации оборота статистических данных. Информационные стандарты призваны унифицировать идентификаторы и пространство имен для участников оборота статистической информации, что позволяет обеспечить единое семантическое пространство. С применением единых идентификаторов становятся прозрачными процедуры обработки статистических данных, в том числе группировка по разным срезам, а также разложение агрегированных данных на составляющие.Результатами работы являются рекомендации по использованию отдельных элементов информационной инфраструктуры для сбора и анализа статистических данных. В существующей информационной инфраструктуре цифровой экономики существует ряд источников данных, использование которых будет способствовать повышению качества сбора и обработки статистических данных. Для создания семантического пространства статистических данных в РФ наиболее актуальным разделом являются реестры базовых объектов. Использование реестров позволит организовать связывание статистических данных из разных предметных областей, а также реализовывать соединение агрегированных данных с микроданными. Существенный прогресс наблюдается в маркировке товаров, которая позволяет отслеживать движение по всем этапам жизненного цикла, а также местоположение объекта. Правительство РФ инициировало проект по маркировке товаров, и эта информация дает возможность получить полное представление о существенной части экономики. Дополнительным информационным источником статистических данных может выступать корпоративный сектор, активно использующий в своей деятельности системы прослеживания, которые выполняют мониторинг товара, транспортных средств, контейнеров, складского хозяйства.Заключение: Существует несколько вариантов обеспечения семантического единообразия статистических данных. Мировой опыт ориентируется на использование веб архитектуры, предполагающей использование технологических идентификаторов. Семантику статистических данных возможно обеспечить путем использования созданного потенциала информационной инфраструктуры, что позволит решить ряд проблем статистического учета

    Variations on the Author

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    “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

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    We 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

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    We 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

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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