Використання метаданих для вирішення задач великих даних

Abstract

Today, the volumes of used by application sys­tems are growing exponentially and have reached such si­zes that they cannot be processed by traditional sys­tems. So the term Big data appeared. The main prob­lems of such sets are associated, first of all, not on­ly with their volumes, but also with the variety and com­plexity of the information they contain. Thus, along with the growth of volumes and the number of big initiatives, the metadata become the most im­portant priority for the success of large projects. En­terprises understand that the full use of the ope­ra­ti­o­nal potential of machine learning, in-depth learning and ar­tificial intellect requires the unprocessed was sup­plemented with metadata. Therefore, the purpose of this work is to analyze the effect of metadata to solving the big problems, determine the main categories of da­ta to be annotated by metadata, and the main types of metadata used for this. Today, metadata is a means of classifying, organizing, and characterizing or its contents. De­­pending on the role they play in solving big problems, NISO identifies four main types of metadata: administrative, descriptive, structural, and markup languages. Dif­fe­rent types of metadata can be used in a certain way to ef­fectively solve problems of management, search, in­tegration, etc. A separate issue is the way of their creation/automatic generation, since the manual cre­ation of metadata is a laborious process, and their vo­lume is often several times larger than the volume of the itself.