Abstract: A number of problems related to the construction of the metadata factory of the digital mathematical library Lobachevskii-DML have been solved. By metadata factory we mean a system of interconnected software tools aimed at creating, processing, storing and managing metadata of digital library objects and allowing integrating created electronic collections into aggregating digital scientific libraries. In order to select the optimal such software tools from existing ones and their modernization:we discussed the features of the presentation of the metadata of documents of various electronic collections related both to the formats used and to changes in the composition and completeness of the set of metadata throughout the entire publication of the corresponding scientific journal;we presented and characterized software tools for managing scientific content and methods for organizing automated integration of repositories of mathematical documents with other information systems;we discussed such an important function of the digital library metadata factory as the normalization of metadata in accordance with the formats of other aggregating libraries.As a result of the development of the metadata factory of the digital mathematical library Lobachevskii-DML, we proposed a system of services for the automated generation of metadata for electronic mathematical collections; we have developed an xml metadata presentation language based on the Journal Archiving and Interchange Tag Suite (NISO JATS); we have created software tools for normalizing metadata of electronic collections of scientific documents in formats developed by international organizations – aggregators of resources in mathematics and Computer Science; we have developed an algorithm for converting metadata to oai_dc format and generating the archive structure for import into DSpace digital storage; we have proposed and implemented methods for integrating electronic mathematical collections of Kazan University into domestic and foreign digital mathematical libraries.

Abstract: International Virtual Observatory (IVO) is a collection of integrated astronomical data archives and software tools that utilize computer networks to create an environment in which research can be conducted. Several countries have initiated national virtual observatory programs that will combine existing databases from ground-based and orbiting observatories and make them easily accessible to researchers. As a result, data from all the world's major observatories will be available to all users and to the public. This is significant not only because of the immense volume of astronomical data but also because the data on stars and galaxies have been compiled from observations in a variety of wavelengths: optical, radio, infrared, gamma ray, X-ray and more. Each wavelength can provide different information about a celestial event or object, but also requires a special expertise to interpret. In a virtual observatory environment, all of this data is integrated so that it can be synthesized and used in a given study. The International Virtual Observatory Alliance (IVOA) represents 17 international projects working in coordination to realize the essential technologies and interoperability standards necessary to create a new research infrastructure. Russian Virtual Observatory is one of the founders and important members of the IVOA. The International Virtual Observatory project was launched about ten years ago, and major IVO achievements in science and technology in recent years are discussed in this presentation. Standards for accessing large astronomical data sets were developed. Such data sets can accommodate the full range of wavelengths and observational techniques for all types of astronomical data: catalogues, images, spectra and time series. The described standards include standards for metadata, data formats, query language, etc. Services for the federation of massive, distributed data sets, regardless of the wavelength, resolution and type of data were developed. Effective mechanisms for publishing huge data sets and data products, as well as data analysis toolkits and services are provided. The services include source extraction, parameter measurements and classification from data bases, data mining from image, spectra and catalogue domains, multivariate statistical tools and multidimensional visualization techniques. Development of prototype VO services and capabilities implemented within the existing data centers, surveys and observatories are also discussed. We show that the VO has evolved beyond the demonstration level to become a real research tool. Scientific results based on end-to-end use of VO tools are discussed in the presentation.

Abstract:

The materials presented at the Conference describe the results of recent years in the following areas: Open access to scientific data and knowledge in Earth Sciences; Data peculiarities in Earth Sciences: new concepts and methods, tools for their collection, integration and processing in different information systems, including systems with intensive use of data; Data mining and mathematical simulation of natural processes in Earth Sciences. Evolution of classical GIS-applications in Earth Sciences; Application to Critical Raw Materials (CRM); social aspects of mining (e.g., the Social Licence to Operate [SLO]); predictive mapping and applications to exploration, landuse and search for extensions of known deposits; Intelligent data analysis, elicitation of facts and knowledge from scientific publications. Thesauruses, ontologies and conceptual modeling. Semantic WEB, linked data. Services. Content semantic structuring. Applications for geosciences, e.g., Ontology-based Dynamic Decision Graphs for Expert systems and decision-aid tools; Application of methods and technologies of the remote sensing in Earth Sciences: from satellites to unmanned aerial vehicles; Information technologies for demonstration and popularization of scientific achievements in Earth Sciences; Applications: environmental risks including mining wastes, natural hazards, water resource management, etc.

Abstract: This article considers approach to intelligent search of complex objects in different types of texts with structural markup which can be used for Big Data processing. We research two types of data entry: relational databases, which use their schemes as structural markup, and full-text scientific documents containing mathematical expressions (formulae). For such full-text documents we suggest additory automated markup to allow formula search. In both cases we use natural language texts, which are semistructured data, as data source for building ontology and conducting search at a later stage. For relational databases those are comments to table and table attribute names; for scientific documents (articles, monographs, etc.) it is a text content of marked up documents.

Abstract:

We investigated the current models of the publication and dissemination of scientific knowledge. We describe the modern information management system of scientific publications and services that determine their functionality.

We discuss the concept of the digital infrastructure of the electronic scientific journal. Under this infrastructure, we understand the complex that combines management software platform of electronic journal and a number of specialized information systems. The software platform realizes the basic operating log management processes. Information systems provide the operation of additional services, taking into account the specifics of the journal subject area.

We present an approach to the organization of the digital infrastructure of the scientific journal based on an open platform Open Journal Systems (OJS). We provide software services that extend the functionality of this platform and considering specificity of the subject area of scientific journals. We have created software modules for automating of electronic scientific journal workflow. These modules are an extension of OJS.

We present a system of services for the automated processing of collections of scientific documents. These services provide verification of document compliance to the accepted rules of formation of collections and their conversion to the established formats; structural analysis of documents and extraction of metadata, as well as their integration into the scientific information space. The system allows to automatically performing a set of operations that cannot be realized for acceptable time with the traditional manual processing of electronic content. It is designed for the large collections of scientific documents.

Algorithms style validation of texts at the article registration stage in the information system of electronic scientific journal, the selection of reviewers, alert and control the timing of reviewing were automated. Information gathering algorithm with dedicated news lines of scientific journals, further analysis and distribution of news by categories and degrees of importance were developed. The algorithm automatically extract bibliographic data from a homogeneous array of publications (in particular, the issues of the scientific journal) and the formation of metadata blocks for export to international information and analytical system were created. Methods integration of OJS platform and international databases of science citation were developed.

We present methods of processing documents containing mathematical formulas: in the collections of documents that contain mathematical formulas, algorithm for the search formulas is developed; basic ideas, approaches and results already obtained by the mathematical knowledge management based on ontology are presented; a method of constructing recommender systems based on mathematical knowledge ontologies described. The method of primary processing automated of scientific article using TеX-notation developed.

The new direction of researches of scientific communications in the environment of Web 2.0 – altmetrics – is considered. We have analyzed the content of the notion «altmetrics», we conducted a comparison of traditional (bibliometric and scientometric) and alternative indicators. We describe the use of world experience informetric services on scientific journals sites. We discussed options for implementing these approaches to create an electronic scientific journal management platform. 

Abstract: An approach is proposed for organizing expert evaluation of a scientific document submitted to a mathematical journal. Domain restriction is associated with the use of the Mathematical Sciences Classification System – MSC. A recommendation system is presented that allows you to create a list of possible experts for conducting scientific peer-reviewing on a mathematical article. The recommender system uses the MSC codes presented by the author of the article on the MSC2020 classifiers. If the codes MSC2000 or MSC2010 are indicated in the article, they are automatically converted to codes MSC2020. For each expert, the system supports a personal profile that contains a set of codes MSC2020, supplemented by numerical characteristics – weights calculated for each code in accordance with the system of accounting for competencies, preferences or refusals to participate in the review procedure. This set is automatically edited if the expert is included in the list of possible reviewers – the weights of several codes increase or decrease, as well as new codes are added. The recommendation system is implemented as an integrated tool (plug-in) of the Open Journal Systems (OJS) platform. The developed method has been tested in the information system of the Lobachevskii Journal of Mathematics (https://ljm.kpfu.ru).

Abstract: The technology of automated construction of the subject domain ontology, based on information extracted from the comments of the TATNEFT oil company relational databases, is considered. The technology is based on building a converter (compiler) translating the logical data model of Epicenter Petrotechnical Open Software Corporation (POSC), presented in the form of ER diagrams and a set of the EXPRESS object-oriented language descriptions, into the OWL ontology description language, recommended by the W3C consortium. The basic syntactic and semantic aspects of the transformation are described.

Abstract: We investigated the current models of the publication and dissemination of scientific knowledge. We also presented different approaches to the organization of the personal information space of scientist. We describe the modern information management system of scientific publications and services that determine their functionality. We have created software modules for automating of electronic scientific journal workflow. These modules are an extension of Open Journal Systems. We describe the architecture of a universal information management system of electronic scientific journals and management platform of “Russian Digital Libraries Journal”.

Abstract: Methods of the semantic documents parsing in digital control system of scientific collections, including electronic journals, offered. The methods of processing documents containing mathematical formulas and methods for the conversion of documents from the OpenXML-format in ТеХ-format considered. The search algorithm for the mathematical formulas in the collections of documents stored in OpenXML-format designed. The algorithm is implemented as online-service on platform science.tatarstan.

Abstract: We described an evolution of thinking model in application with building intellectual question-answer system for automation processing user requests in natural language, starting with simple decision trees and finished with human thinking model. Every model has been developed, prototyped and tested. Experimental data and conclusions for every model provided.

Abstract: We have studied emotions in various aspects: philosophical, psychological and neurophysiological; taking them into account cognitive architecture has been described. Based on Lovheim “Emotion Cube”, “Wheel of emotions” by Plutchik, Tomkins “Theory of affects” and Marvin Minsky thinking model we describe usage of emotions as influence factors for computing processes. Also indicated the possibility of using emotions in intelligent question-answer systems.

Abstract: This paper describes the morphological disambiguation methods and their application for the Tatar language. The state-of-the art technology is discussed. We analyze the contextual and statistical methods and their evaluations for different languages.

Abstract:

Sentiment analysis and opinion mining technologies are growing fast. This is mostly due to a rapid grow of the data sources consisting a vast amount of user opinions and reviews on a wide set of topics. In this paper we describe methods for sentiment analysis of reviews and short messages (tweets), as well as evaluation of results obtained during SentiRuEval-2015.