The article attempts to redefine the names for the research area, which is the use of information systems for the analysis and management of spatial data. To resolve the nomenclature issues, the studies were conducted into the structure evolution of spatial data, and on software for these data processing, GIS acronyms were reviewed; another study was performed by means of terminological analogies, comparing definitions of similar, in terms of word formation, names referred to other areas of research. Moreover, questionnaires of job positions were analysed and, based on a literature review, the nomenclature used to define the field of studies on spatial data was analysed. The conducted studies resulted in the development of seven terminological postulates intended for the formulation of limitations and rules to give new definitions. The new author’s definitions of geomatics and geoinformatics terms are presented at the end of the paper.

This article discusses the growing role of Geomatics and Geoinformatics in the education of specialists at various universities, with particular emphasis on the mining industry. The study used a qualitative desk research approach that included analysis of institutional curricula, legislative documents, and scientific publications related to spatial data processing, mining education, and the geomatics professional framework. The paper identifies the requirements and educational goals for mining geomaticians who can act as managers of spatial data infrastructure in mining companies, managing the mining modelling processes and its impact on the environment and the local community. The article concludes with recommendations for restructuring educational programs to meet industry expectations for data-centric mining operations. The introduction of the profile of the ’mining geomatician’ can contribute significantly to the development of the industry, making it more modern and adapted to the requirements of a modern knowledge and technology-based economy.

This study presents a comprehensive GIS-based multicriteria decision analysis (MCDA) framework for identifying prospective groundwater abstraction sites in a 9 municipality region of South-East Poland (Podkarpackie Voivodeship), covering approximately 830 km². The analysis integrated hydrogeological parameters (aquifer thickness, quality, productivity, water table depth, protection degree, recharge zones) with spatial risk factors (contamination sources, exclusion zones) and population density patterns. The MCDA approach provides a decision support tool for municipal authorities tasked with water infrastructure planning under conditions of limited baseline data. The framework demonstrates the utility of a carefully specified GIS-MCDA framework to provide such support, while highlighting the need for improved data sharing to enable full statistical validation.

This paper attempts to define a name for an area of science and technology that encompasses the acquisition, processing and application of spatial data in the mining industry. A comparative study of the evolution of spatial data exchange methods between Geographic Information Systems (GISs) and General Mining Planning (GMP) software is carried out to define the problem and name it. Subsequent modifications of the acronym GIS towards the specialisation of its application in mining are then reviewed. This is followed by the identification of three terminological postulates designed to formulate constraints and rules for the creation of a new definition. The subsequent analysis identifies the nomenclatural basis of the research area of geomatics and determines its applicability in the context of mining. The results of the research made it possible to formulate a new definition of “mining geomatics”. The final section of the article presents an initial proposal for an inventory of the basic concepts of mining geomatics in the form of a Body of Knowledge for mining geomatics.

The Satellite Radar Interferometry is one of the common methods that allow to measure the land subsidence caused by the underground black coal excavation. The interferometry images processed from the repeat-pass Synthetic Aperture Radar (SAR) systems give the spatial image of the terrain subjected to the surface subsidence over mining areas. Until now, the InSAR methods using data from the SAR Systems like ERS-1/ERS-2 and Envisat-1 were limited to a repeat-pass cycle of 35-day only. Recently, the ESA launched Sentinel-1A and 1B, and together they can provide the InSAR coverage in a 6-day repeat cycle. The studied area was the Upper Silesian Coal Basin in Poland, where the underground coal mining causes continuous subsidence of terrain surface and mining tremors (mine-induced seismicity). The main problem was with overlapping the subsidence caused by the mining exploitation with the epicentre tremors. Based on the Sentinel SAR images, research was done in regard to the correlation between the short term ground subsidence range border and the mine-induced seismicity epicentres localisation.

The article describes the results of an analysis of problems experienced by Polish mining enterprises when processing large amounts of data. A literature review identifies some common characteristics of these problems within the field of Big Data that are particularly evident in the case of spatial data. Furthermore, the determinants of these enterprises’ ability to implement new technologies for large-scale processing of spatial data sets are enumerated.