Sources, Acquisition, Classification of Data: The term ‘data’ is a plural form of the Latin word ‘datum,’ and literally, it means anything that is given.
Sources, acquisition, and classification of Data
Many sources have defined data in different ways. According to the Oxford Encyclopaedic English Dictionary, “data are known facts or things used as a basis for inference or reckoning.”
UNESCO defines data as “facts, concepts, or instructions in a formalised manner suitable for communication, interpretation, or processing by human or automatic means.”
UNIT VII – Data Interpretation (Click on the topic to read)
|
UGC NET Study Materials for Paper 1 (eBook with MCQ) BUY NOW |
McGraw-Hill Encyclopaedia of Science and Technology defined as ‘numerical or qualitative values derived from scientific experiments.’
In social sciences, data are stated as values or facts, together with their accompanying study design, codebooks, research reports, etc. and are used by researchers for the purpose of secondary analysis.
In humanities, the text, such as Biblical materials or Shakespeare’s drama deals with a fixed quantity of data represented by a finite amount of text to be interpreted.
In Information Science, “data as quantitative facts derived from experimentation, calculation, or direct observation.”
In brief, data is basically unorganized statistical facts and figures collected for some specific purposes, such as analysis.
Types of Data in Social Sciences
The following categorisation is normally observed in social sciences:
i) Data based on scale: Based on the scale of measurement, data can be categorised as follows:
- Nominal data
- Ordinal data
- Interval data
- Ratio data
ii) Data based on continuity: Data with reference to continuity can be categorised as follows:
- Continuous data
- Discrete data
iii) Data based on number of characteristics: Data can also be categorised on the basis of number of variables considered. These are:
- Univariate data: Univariate data are obtained when one characteristicis used for observation, e.g., the performance of student in a givenclass.
- Bivariate data: Bivariate data result when instead of one, twocharacteristics are measured simultaneously, e.g., height and weightof tenth class students.
- Multivariate data: Multivariate data consist of observations on threeor more characteristics, e.g., family size, income and savings in a metropolitan city in India.
iv) Data based on time: There are two types of data under this category. These are:
Time series data –Data recorded in a chronological order a cross time are referred to as time series data. It takes different values at different times, e.g., the number of books added to a library in different years, monthly production of steel in a plant, yearly intake of students in a university.
Cross Sectional data – This refers to data for the same unit or for different units at a point of time, e.g., data across sections of people, region or segments of the society.
v) Data according to origin: Data under this category can be put as follows:
Primary data: The data obtained firsthand from individuals by direct observation, counting, and measurement or by interviews or mailing a questionnaire are called primary data.
Secondary data: The data collected initially for the purpose and already published in books or reports but are used later on for some other purpose are referred to as secondary data. For example, data collected from census reports, books, data monographs, etc.
vi) Data according to characteristic: Data can be categorised on the basis of the characteristics as follows:
Quantitative data: When the characteristic of observation is quantified we get quantitative data. Quantitative data result from the measurement of the magnitude of the characteristic used. For example, age of a person, price of a commodity, income of a family, etc.
Qualitative data: When the characteristic of observation is a quality or attribute, we get qualitative data. For example, sex or colour of a person, or intelligence of a student.
Sources of Data
The sources of data can be categorised as the followings:
Static Data: Static data is those data that does not change during processing. This type of data can not be changed when written or printed.
Examples:
- A newspaper story: hard copy cannot be changed once printed.
- Data stored on a CD ROM (not re-writable): a CD ROM cannot be edited.
These are two examples of static data or information as they cannot be changed.
Dynamic data: Dynamic data refers to data that changes during processing – it is updated as and when necessary. The data is never expected to be the same when re-input.
Examples:
- Data on a webpage that is updated from time to time.
- Data on a CD RW can be rewritten or edited
- Data from a stock market.
These are the examples of dynamic data, as they change with the time.
Sources of Data based on Origin
Primary source: A primary source is an original document that contains first hand information about a topic or an event. The primary sources exist on a spectrum and different fields of study may use different types of primary source documents.
Example: The field of History may use letters and diary entries as primary source evidence, while the Sciences may use a publication of original research as a primary source.
Here, some common examples of primary source documents:
- Historical documents (letters, pamphlets, political tracts, manifestos)
- Data and Research Results (scientific article presenting original findings, statistics)
- Blogs articles, tweets, and other social media entries
- Original works of art
- Works of literature
- Video footage & photographs
- Interview transcripts
- Eyewitness accounts, newspapers articles & autobiographies
- Lab notebooks and case studies
Secondary Sources: A secondary source is an interpretation, analysis, evaluation or discussion of an event or issue that is based on primary source evidence. The secondary sources list, summarise, compare, and evaluate information or studies so as to draw conclusions or present on the current state of knowledge on a topic. The secondary sources are often in the form of scholarly discourse or reviews.
Common examples of secondary sources are:
- Biographies
- Monographs written about the topic
- Indexes, Abstracts, Bibliographies
- Literary criticism
- Reviews of movies, books, musical recordings, works of arts, etc.
- Journal articles
- Newsletters and professional news sources
Acquisition of Data (Collection of data)
The acquisition or collection of data can be categorised based on the sources of data. There are two types of sources; primary sources and secondary sources.
The primary sourced of data can also be called primary data, similarly the secondary sources data is called secondary data. We have already mentioned above what are the sources in primary and secondary sourced data.
You can also go through the topic for sources, acquisition and collection of data in Research Aptitude of UGC NET Paper 1.
Related Topics:
UGC NET Syllabus (Updated): Paper 1 and 2
Solved Question Papers of UGC NET Paper 1
UGC NET Study Materials for Paper 1 (Download PDF)
Official Website for UGC NET