academic event academic publication academic research call for abstracts call for papers CAQDAS Coding Data Computer Aided Qualitative Data Analysis Software conference Data Analysis data analysis techniques data coding data coding techniques data visualization diagrams education research flowcharts focus groups graphs healthcare research maps New Trends in Qualitative Research NTQR qualitative analysis Qualitative Analysis Software Qualitative Data Qualitative Data Analysis Qualitative Experiments Qualitative Research Qualitative Researchers questionnaire surveys Research research methods scopus social research Social Sciences tables visual outputs of qualitative data WCQR WCQR2021 WCQR2022 web of science webQDA world conference World Conference on Qualitative Research
Data visualisation can be used from organising qualitative research data to analysing and presenting results. It also can contribute to researchers and their readers to discover new interpretations and knowledge about the phenomenon studied.
Visual representation is helpful during all phases of data analysis. These allow identifying patterns, numerical and non-numerical trends, using graphs, maps, tables, diagrams, flowcharts, among others.
Qualitative Research has benefited from the enormous progress in terms of methods and techniques with intensive use of technology. The current demands in the investigative context compel more and more researchers to equip themselves with digital tools that provide speed and efficiency in their research processes.
One of the main errors verified in research is the lack of planning of adequate methods for data analysis. For example, to develop a data collection instrument, it is necessary to pay attention to the tools used to obtain results (analysis). Analysing qualitative data is not a task without difficulties, as the non-numeric and unstructured data corpus is generally diffuse and complex. There are no clear and widely accepted rules on how to analyse non-numeric and unstructured data.
The seven essential steps or subtasks that we will describe below are transversal or generic to qualitative data analysis techniques. The technique’s focus on the analysis rests on specific choices according to each objective and research questions.
For very practical purposes, it can be said that qualitative research of scientific nature has three stages: (1) an exploratory phase; (2) fieldwork; (3) analysis and treatment of the empirical and documentary material. The exploratory phase consists of the production of the research project and all the procedures necessary for preparation to enter the field. The fieldwork phase constitutes the primordial moment for understanding, in intersubjectivity, the empirical reality under study.
Content Analysis is a data analysis technique, collected from a variety of sources, but preferably expressed in text or images. The nature of these documents can be varied, such as archival material, literary texts, reports, news, evaluative comments of a given situation, diaries and autobiographies, articles selected through the method of literature review, transcripts of interviews, texts requested on a specific subject, field notes, etc