This document provides an overview of qualitative research and qualitative data analysis. It defines qualitative research as collecting and analyzing non-quantitative data through methods like interviews and focus groups. The document outlines different types of qualitative research and analysis techniques including phenomenology, ethnography, case studies, grounded theory, and historical research. It then discusses the process of analyzing qualitative data through coding, content analysis, and identifying themes and patterns. Specific analytical approaches like domain analysis, taxonomic analysis, and componential analysis are also summarized.

1. Topic:
Analysing Qualitative Data from
Information Organizations
Submitted By: Aleeza Ahmad
Roll No. 07
M.Phil (LIS) Second Semester
Minhaj University, Lahore
Submitted to: Dr. Nadeem Siddique

2. What is Research?
• Research
• Research is defined as a careful consideration of study regarding a particular concern
or a problem using scientific methods
• Research can be classified in many different ways on the basis of the
methodology of research, the knowledge it creates, the user group, the
research problem it investigates etc.
• Basic Research
• Applied Research
• Qualitative Research
• Quantitative Research
• Descriptive Research
• Analytical Research

3. Qualitative Research
• Qualitative research presents a non-quantitative type of analysis
• Qualitative research is collecting, analyzing and interpreting data by observing
what people do and say
• Qualitative research refers to the meanings, definitions, characteristics, symbols,
metaphors, and description of things. Qualitative research is much more
subjective and uses very different methods of collecting information ,mainly
individual, in-depth interviews and focus groups
• The nature of this type of research is exploratory and open ended. Small number
of people are interviewed in depth and or a relatively small number of focus
groups are conducted. Qualitative research can be further classified in the
following types:
• I. Phenomenology
• II. Ethnography
• III. Case study
• IV. Grounded theory
• V. Historical research

4. Qualitative Research Pyramid

5. Overview of Data Analysis
• When field work ends, the researcher begins the equally important
chore of formal data analysis
• While there are numerous approaches to the analysis of qualitative
data, Miles and Huberman usefully summarize such analysis as a
combination of:
• Data reduction
• Data display
• Conclusion drawing and verification

6. Role of Researcher
• To analyse qualitative data you, the researcher, must move between
the role of the scientist and that of the artist
• Researcher-Scientist
• Researcher-Artist
• Interpretive skills require that the researcher engage in both
convergent and divergent thinking
• Wolcott describes data as the process in which the researcher
considers units of data such as words, behavior, events and ideas, as
well as the properties of these units. From analysis you must then
move to the process of interpretation

7. Data Analysis Process
• Data analysis may involve coding, content analysis or ethnographic
analysis
• Whatever the technique employed, it follows a nonlinear process of
seeing a pattern, returning to the data or the study setting, and
exploring or confirming the facilitates the identification of essential
features and the systematic description of interrelationships among
them – in short how things work

8. Preliminary Data Analysis
• Data analysis is the process of bringing order, structure and meaning
to the mass of collected data
• It does not proceed in a tidy linear fashion. Rather, it is a messy,
ambiguous, time – consuming, creative and fascinating process
• The purpose of this process is to search for general statement about
relationships among categories of data

9. Preliminary Data Analysis Process
Researcher-as-research-instrument function as information processor
Uses selective perception to tease out notable events or comments
Determines preliminary units of data
Creates initial broad categories for data units

10. Process of Identifying Initial Data Categories
Read a Unit of Data
Read Next Unit of data Assign a Category
Yes
Is it the same Category
No
Assign New Category

11. Detailed Data Analysis
• Essentially, this more detailed data analysis involves reconfiguring the units
of data in order to view the phenomena from fresh perspectives, and
watching for emergent theories pertinent to the enquiry. To achieve the
required understanding of what an investigation has discovered, and to
interpret it meaningfully and contextually, researchers employ numerous
methods of qualitative data analysis
• Among them are:
• Affixing codes to a set of field notes
• Noting reflections or other remarks in margins of notes
• Sorting and sifting data to identify key events, phrases, relationships between
variables, patterns, themes
• Confirming Patterns and themes through additional data collection and analysis
• Developing new theories or contributing to existing theories

12. Coding and Content Analysis
• Qualitative research data consist primarily of text (such as interview
transcripts, observations and field notes)
• For this reason analysis demands that investigators consider the
semantic relationships of words by describing and classifying
terminology unique to the enquiry.
• According to Mead, ‘data analysis involves taking constructions
gathered from the context and reconstructing them into meaningful
words’

13. Coding
• Such classification of terminology and language constructs goes by many
names
• Lincoln and Guba, for example, refer to the process of analyzing textual
data as ‘unitizing’ or disaggregating data into the smallest pieces of
information that may stand alone as independent thoughts in the absences
of additional information other than a broad understanding of the context
• Miles and Huberman, on the other hand, speak of ‘chunks’ of data, which
during analysis are assigned codes
• Glesne recommend that you begin with a simple coding scheme
• Inevitably the codes will change, expand and collapse, creating a data
management nightmare

14. Content Analysis
• Another approach to textual data analysis in qualitative enquiries is
the use of content analysis
• This classifies textual material by reducing it to more relevant,
manageable bits of data
• Content analysis can involve the use of qualitative data collection
methods, either alone or in combination with quantitative analysis

15. Ethnographic Data Analysis
• Another form of data analysis in qualitative studies involves use of the
ethnographic analytical model
• Spardley’s analytical model of ethnographic analysis can provide both
methodological guidance and also facilitate the ‘systematic
examination of something to determine its parts, the relationship
among parts, and their relationship to the whole’
• The data for the study may be drawn from:
• Observation field notes
• Reflexive journal notes
• Individual interview and focus group transcripts

16. Domain Analysis
• Domains in data analysis are categories that include other categories
• The domain structure includes a cover term, included terms, and
semantic relationship of these terms
• Primary analytical goal of researcher is to find patterns that exist in
the research data

17. Taxonomic Analysis
• In Spardley’s model the next step in formal data analysis uses
taxonomic analysis to identify patterns in the organization of cultural
domains
• During this process the researcher begins to focus the data analysis
• The taxonomy differs from a domain in that it shows the relationship
among all the terms in domain

18. Componential Analysis
• Once taxonomic analysis has been completed the next logical step is
to consider the descriptive attributes (components of meaning) of
terms in each domain. This is referred to as componential analysis

19. Theme Analysis
• The final analytical strategy used in ethnographic research is theme
analysis
• Theme analysis seeks to discover and identify the relationships
among domains and connections with the description of a study’s
cultural setting

20. Memos and Visual Displays
• During data analysis one challenge for the researcher is to remain at arm’s
length from the flood of particulars
• Data analysis requires immersion, but the researcher also must be able to
stand back and reflect on the meaning of data – an uncomfortable
combination of experience – near and experience – distant
• Notes written by the researcher to her/himself, or ‘memos’, offer one way
to stand back from data immersion
• Strauss and Corbin define the memo as written form of abstract thinking
and general design, a graphic representation of visual images, used
particularly to demonstrate the relationships between concepts
• The reflexive journal is a place in which the researcher deliberately looks
up and away from empirical data to conceptual levels of an investigation

21. Cont…..
• In addition to memos another important technique for understanding
data is the use of figures, tables, matrices and other illustrations –
although these are most easily employed with empirical data

22. Using Computers for Qualitative Data Analysis
• The key to using computers in qualitative research is to know on the
one hand what computers can do and, on the other, what you want
or need to do
• Miles and Huberman offer sound, extended advice on both counts
• Summary is:
• Entering and editing notes
• Coding notes
• Storing and Retrieving data
• Memo-writing and theory building
• Displaying and mapping data

23. Review
• This chapter has attempted to clarify the goals and components of
the qualitative data analysis process
• Some of the complexity and challenge of systematically categorizing,
coding, comparing and reconfiguring enormous quantities of data, all
of which support the process of searching for meaning in the many
patterns and themes has been introduced
• The process of data analysis is time – consuming and ambiguous, but
the creative search for patterns and themes in data will reward the
qualitative researcher with fresh insights into the operation of
information organizations

24. References
• https://en.wikibooks.org/wiki/Research_Methods/Types_of_Research
• Qualitative Research for the Information Professional: A practical Handbook
(Second Edition) by G. E. Gorman and Peter Clayton with contributions from
Sydney J. Shep and Adela Clayton (2005)