[Qualitative Data Analysis in Contemporary Information Science] This paper examines the methods (procedures, techniques) of empirical data analysis within the qualitative research in the XXI century’s Information Science. The text consists of two parts, the first of them characterizes qualitative data analysis in general, the second one – in Information Science. The basic research strategy used here is critical literature review in various versions. The issue of qualitative data analysis (QDA) is present both in methodological discussions and research practice of social sciences, particularly in sociology, psychology, ethnography and marketing studies. It makes the most significant matter, because the way of analyzing any gathered empirical material determines the research outcomes, their content, validity and credibility. However, generally accepted, precisely formulated standards of QDA have not yet been created, in contrast – different approaches and interpretations can easily be noticed. That, in turn, results from the very essence of the qualitative methodology, where exploration procedures are not strictly repeatable and empirical material is rich and hardly quantifiable. On the other hand, there exist different techniques of qualitative analysis, including – inter alia – the constant comparative method and concept mapping, as well as specialized computer software devoted to QDA. udThe main purpose of this paper is to study if, how and to what extent the contemporary Information Science is interested in the above indicated problems and what are their theoretical and empirical consequences for the discipline. As a result, the inquiry here is of exploratory nature. Two major questions have been asked. First of all, do information scientists reflect on qualitative data analysis in the context of the discipline’s subject and research field? How the body of literature in that area looks like? Secondly, is the qualitative data analysis really and properly used in the empirical research of Information Science? Which QDA techniques are preferred and why? What in particular is investigated using qualitative data analysis? The answers to these questions may enhance the level of methodological consciousness within Information Science in Poland. ud
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机译：[当代信息科学中的定性数据分析]本文研究了二十一世纪信息科学中的定性研究中的经验数据分析方法（过程，技术）。本书由两部分组成，第一部分主要描述定性数据分析的特征，第二部分–信息科学。这里使用的基本研究策略是各种版本的重要文献综述。定性数据分析（QDA）问题在社会科学的方法论讨论和研究实践中都存在，特别是在社会学，心理学，人种学和市场研究中。这是最重要的事情，因为分析任何收集的经验材料的方式都决定了研究成果，其内容，有效性和可信度。但是，相比之下，尚未建立公认的，精确制定的QDA标准-可以很容易地注意到不同的方法和解释。反过来，这是由于定性方法的本质所致，在该方法中，勘探程序并非严格可重复，经验材料丰富且难以量化。另一方面，存在不同的定性分析技术，其中包括-持续比较方法和概念映射，以及专用于QDA的专用计算机软件。 ud本文的主要目的是研究当代信息科学是否，如何以及在多大程度上对上述问题感兴趣，以及它们对该学科有何理论和经验意义。结果，这里的询问是探索性的。提出了两个主要问题。首先，信息科学家是否会在该学科的主题和研究领域的背景下反思定性数据分析？该地区的文学体如何？其次，定性数据分析在信息科学的实证研究中是否真正正确地使用了？首选哪种QDA技术，为什么？使用定性数据分析特别要调查什么？这些问题的答案可能会提高波兰信息科学界的方法论意识水平。 ud
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