voprstatВопросы статистикиVoprosy Statistiki2313-63832658-5499The Federal State Budgetary Institution "Scientific Research Institute for Socio-Economic Statistics of the Federal State Statistics Service" (Statistics Research Institute of Rosstat)10.34023/2313-6383-2020-27-2-5-16voprstat-1086Research ArticleРАЗВИТИЕ ГОСУДАРСТВЕННОЙ СТАТИСТИКИDEVELOPMENT OF STATE STATISTICSСвязанные статистические данные: актуальность и перспективыLinked Open Statistical Data: Relevance and Prospectshttps://orcid.org/0000-0001-6659-0961АкаткинЮ. М.AkatkinYu. M.

Акаткин Юрий Михайлович - канд. экон. наук, заведующий научной лабораторией «Семантического анализа и интеграции»

Yuri M. Akatkin - Cand. Sci. (Econ.), Head, Laboratory of Semantic Analysis and Integration

u.akatkin@semanticpro.orghttps://orcid.org/0000-0002-3205-1457ЛайкамК. Э.LaykamK. E.

Лайкам Константин Эмильевич - д-р экон. наук, канд. техн. наук, заместитель руководителя 

директор НИИ «Институт современных экономических исследований»

Konstantin E. Laykam - Dr. Sci. (Econ.), Cand. Sci. (Tech.), Deputy Head

Director, Institute of Modern Economic Researches

laikam@gks.ruhttps://orcid.org/0000-0001-8226-3549ЯсиновскаяЕ. Д.YasinovskayaE. D.

Ясиновская Елена Донатовна - старший научный сотрудник научной лаборатории «Семантического анализа и интеграции»

Elena D. Yasinovskaya - Senior Researcher, Laboratory of Semantic Analysis and Integration

elena@semanticpro.orgРоссийский экономический университет имени Г.В. ПлехановаРоссияPlekhanov Russian University of EconomicsRussian FederationРоссийский экономический университет имени Г.В. Плеханова; Федеральная служба государственной статистикиРоссияPlekhanov Russian University of Economics; Federal State Statistics ServiceRussian Federation202001052020272516Copyright © Акаткин Ю.М., Лайкам К.Э., Ясиновская Е.Д., 20202020Акаткин Ю.М., Лайкам К.Э., Ясиновская Е.Д.Akatkin Y.M., Laykam K.E., Yasinovskaya E.D.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://voprstat.elpub.ru/jour/article/view/1086

В данной статье после развернутой аргументации актуальности проведенного исследования рассмотрены перспективы внедрения концепции связанных статистических данных, формируемых в рамках единого информационного пространства, обеспечивающего эффективное производство, распространение и повторное использование статистических и административных данных. Реализация этой качественно новой концепции на основе технологических новаций, предпринимаемая в целях более полного удовлетворения быстро возрастающих потребностей пользователей - ключевая задача цифровой трансформации, определенная Правительством Российской Федерации в области официальной статистики. Большая часть открытых данных связана со статистикой: демографическими, экономическими и социальными показателями. Их описание и представление в виде связанных данных могло бы стать важной основой для ускорения социально-экономического развития страны путем создания новых общественно значимых государственных, муниципальных, некоммерческих и коммерческих услуг/продуктов.

В статистике связанные открытые данные (Linked Open Statistical Data, LOSD) позволяют выполнять анализ на основе скоординированной, интегрированной информационной базы как альтернативы использованию разрозненных и часто противоречивых наборов данных. Национальные статистические службы и государственные органы целого ряда стран, а также международные организации уже перешли на парадигму связанных данных. Авторы статьи рассматривают преимущества этого подхода, а также практику его применения в международных проектах.

Приведены примеры и лучший опыт создания связанных открытых статистических данных в публикациях и стратегических документах в рамках Европейской статистической системы. Показано, что развитие связанных статистических данных сдерживается отсутствием доступных онтологий и стандартов - расширений, необходимых для обеспечения требований к классификации различных концептов в статистике и управлению ими. Проведенный в статье анализ проектов и инициатив отражает возможности и перспективы решения данной проблемы в сфере государственной статистики. Сформулированные авторами рекомендации основаны как на анализе международной практики, так и на результатах собственного опыта разработок в рамках научно-исследовательского проекта «Центр семантической интеграции».

After a detailed argumentation of the study’s relevance, this article discusses the prospects for introducing the concept of linked open statistics produced within the framework of a single information environment that ensures efficient production, dissemination, and reuse of statistical and administrative data. The implementation of this qualitatively new concept based on technological innovations and aimed to meet rapidly growing user demands is a key task of digital transformation, defined by the Government of the Russian Federation in the field of official statistics. The major part of open data concerns statistics such as demographic, economic and social indicators. Describing and presenting them in the form of linked open statistics sets an important background for accelerating socio-economic development by introducing new socially significant state, municipal, non-commercial and commercial services/products.

Linked Open Statistical Data (LOSD) allows performing analysis based on a coordinated, integrated information environment as an alternative to using disparate and often controversial data sets. National statistical institutes and government bodies in many countries, together with international organizations, have already chosen the paradigm of linked open statistics. The authors discuss the advantages of this approach, as well as its practical application in international projects.

The article presents the examples and best practices of linked open statistics in a number of publications and strategic documents within the European Statistical System. It also shows the constraints of the linked open statistics development due to the lack of accessible ontologies and standards - the extensions necessary to meet the requirements for classification and management of various concepts in statistics domain. The analysis of projects and initiatives carried out in the article reflects the possibilities and prospects of solving this problem in the field of state statistics. The authors formulate a set of recommendations based both on the analysis of international practice and on the results of their own development experience within the research project «Center of Semantic Integration».

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The authors declare that there are no conflicts of interest present.