The dissertation is devoted to solving an important scientific and practical problem – improving the efficiency of information and software resources of the World Data System (WDS), developing approaches and implementing tools to support interdisciplinary research in the WDS.
WDS Members since its inception in 1956 have accumulated a large amount of data and many applications (information systems, services), which are in great demand in international research aimed at finding answers to global challenges facing humanity. However, this is hindered by difficulties in the interaction of legacy applications, the use of different formats and methods of data access, and so on. Solving the problems of analysis, forecasting, scenario modeling of crisis and security phenomena and studying their impact on the economy and society, such as global threats to sustainable development, spreading the SARS-CoV-2 pandemic, etc., also require tools for rapid integration of data from different sources and applications. The problem of organizing, planning, and supporting interdisciplinary research in WDS arises. Varying degrees of depth on particular aspects of integration has led to the need for effective models, methods, and tools needed to implement these solutions.
Within the framework of the dissertation, an analysis of the WDS and a separate World Data Center as a controlled object was performed, unresolved issues of support for interdisciplinary research were identified and analyzed, the prospects of creating the platform to support interdisciplinary research were substantiated as a universal tool for solving problems of organizing the WDS functioning. The concept of the platform to support interdisciplinary research in the World Data System was developed. For the first time, a method was proposed for the harmonization of data of different nature, taking into account estimates of information loss of data conversion procedures and estimates of consistency of data obtained from different sources, to design a procedure for converting data with the lowest information loss. The dissertation proposes the MAS architecture for the transformation of heterogeneous but semantically identical information into metadata, suitable for further analysis and research. The clausal logic of planning the interaction of applications to solve problems of interdisciplinary research was modified. A formal logical system was developed. This formalism is the basis of the integration component of the platform is built. The components of the formal system were described: the language of clausal first-order logic; knowledge base, which is based on an ontology of axioms depicting the methods of services, and an ontology of data sources described in the OWL language based on RDF; inference rules necessary to obtain the desired result in cases where it is necessary to combine methods of both one and different services. The inference method in the clausal logic of application interactions was further developed. The proposed inference method is based on the typification of statements and analogies, it is the formal basis of the inference mechanism in the platform. The output constructed in abstract space is used to control the inference process in the initial solution search space, which will increase the inference efficiency by cutting off most of the unpromising inference branches in the initial space. The algorithm of the solution scheme recovery for the services (applications) integration was developed as a basis for the mechanism of the solution scheme recovery to obtain the functional sequence of actions (scenario) from the output of the inference mechanism. The scenario is executed by the system, taking into account the features and purpose of services (applications). The service-oriented architecture of the platform to support interdisciplinary research was developed, the principles of functioning of interaction of its components were described.
The tools of the Platform were developed based on the proposed concept and original set of models, methods, and algorithms. The Platform provides integration of applications and data sources, processing queries to distributed sources, systemic harmonization of data of various nature, problem-oriented intelligent data processing and automated application generation. An experimental study of the created Platform was conducted on the example of solving a number of applied problems, including analysis and forecasting of world conflicts, construction of strategies and scenarios of sustainable development of Ukraine, analysis and forecast modeling of the COVID-19 epidemic spread in Ukraine, etc.
Components of the developed platform to support interdisciplinary research in the World Data System were implemented at the several scientific and commercial organizations, which allowed to confirm the efficiency of the Platform.
