METROLOGICAL SUPPORT OF INFORMATION MEASUREMENT SYSTEMS

Аннотация

INTRODUCTION known and common algorithms (including details The rapid technological evolution of recent years in of data storage, transmission and processing, the field information and communication machine learning algorithms, etc.), the current and technologies have made it possible to form a future state of information systems and significant backlog in terms of developed software technologies. and hardware infrastructure that supports the accumulation and constant replenishment of data METHODS archives of various natures and purposes. Unit systems and dimensions emerged in the late Increasing competition in various areas of human 19th century. However, efforts to adapt these ideas activity - business, medicine, corporate for use in modern digital systems are proving a management, etc. – and the complexity of the challenge. We provide an interpretation of units external environment make approaches to the and dimensions that clarifies the main reasons for expert use of existing data to improve the validity difficulties. We then suggest how a digital system and efficiency of adoption management decisions. would provide adequate support for quantities and units. A layer of metrological information is At the same time, it is not always possible today to envisaged that would track details and allow directly effectively use a well-developed and well- familiar unit formats to be rendered. Three known apparatus probability theory or independent aspects of the data should be mathematical statistics without taking into account captured: 1) the quantity; 2) the measurement the characteristics of a specific subject area, scale, scale type and conversion functions; and 3) computer science, computational complexity of https://www.theamericanjournals.com/index.php/tajet 34 THE USA JOURNALS THE AMERICAN JOURNAL OF ENGINEERING AND TECHNOLOGY (ISSN – 2689-0984) VOLUME 06 ISSUE09 the semantics of numerical data [1]. relationship and whether or not the relationship between variables is statistically significant. This One of the most well-established methods to approach too has its limitations. A key limitation is integrate research findings and assess the the need to exclude studies that use qualitative cumulative knowledge Measuring information techniques to examine success or studies that fail systems success Stacie Petter et al 239 European to report the information required for the Journal of Information Systems within a domain is statistical calculations for the meta-analysis. a qualitative literature review (Oliver, 1987). This method allows a researcher to analyze and While the meta-analysis produces a quantified evaluate both quantitative and qualitative result regarding the relationship between two literature within a domain to draw conclusions variables, the need to exclude some studies may about the state of the field. As with any research not present a complete picture of the literature. technique, there are limitations. Furthermore, a meta-analysis does not examine the direction of causality, because the effect size is an The primary limitation with this approach is that adjusted correlation between two variables [2]. when conflicting findings arise, it becomes difficult to determine the reason for the conflicting results. There have been meta-analyses examining one or Some also perceive that because the literature more of the elements of IS success therefore, this review is qualitative, it is subjective in nature and paper seeks to obtain a different, qualitative view provides little’hard evidence’ to support a finding. of the literature to answer a different set of To counter these shortcomings, the research research questions. While a meta-analysis is aimed technique of meta-analysis has become quite at answering the question:’Is there a correlation popular in the social sciences and now in IS. Meta- between two variables?’, a qualitative literature analysis is an interesting and useful technique to review is better equipped to explain how the synthesize the literature using quantitative data relationships have been studied in the literature, if reported across research studies. there appears to be support for a causal relationship between two variables, and examines The result of a meta-analysis is an’effect size’ if there are any potential boundary conditions for statistic that states the magnitude of the the model. https://www.theamericanjournals.com/index.php/tajet 35 THE USA JOURNALS THE AMERICAN JOURNAL OF ENGINEERING AND TECHNOLOGY (ISSN – 2689-0984) VOLUME 06 ISSUE09 Figure 1. Meta-analysis vs Systematic review advantages over traditional ones, namely: It means combining the results of several studies using statistical methods (that is, quantitative - high speed of control loops for measurement methods of assessment) to test one or more processes, as well as high speed of data acquisition; interrelated scientific hypotheses. - versatility - standard interfaces provide easy A meta-analysis uses either