Table 2 Indicator data types,... | Emerald Publishing

Table 2

Indicator data types, connotations and characteristics

Division standard	Data types	Connotation	Features
Measurement scale	Categorical data	According to the classification or grouping of certain attributes of objective phenomena, data reflecting the type of things	There is a juxtaposed relationship between each category, and there is no need to distinguish the pros and cons or the size, and the order can be changed arbitrarily; for example, according to the nature of the economy, enterprises are divided into state-owned, collective, private and other economies
	Sequential data	Non-numeric data measured for the level difference or order difference between objective objects	The categories are ordered and can be represented by numerical codes; for example, the test scores can be divided into excellent, good, medium, pass and fail
	Numeric data	The observed value of the objective object measured according to the digital scale, which is expressed as a specific value	Indicates the quantitative characteristics of the objective object; for example, income 1000 yuan, age 20 years, weight 50 kg, etc.
The relationship between objective subject and time	Section data	Observation data of the same indicator of multiple objective objects at the same time point	Obtained in different spaces to describe the changes of objective objects at a certain moment
	Time series data	Observation data of an indicator of an objective object at different time points	Acquired in chronological order, describing how an objective phenomenon changes over time
	Panel data	Sample data composed of multiple cross-sectional sample observations on a time series	Also called “parallel data” or Panel Data, it is an m*n data matrix, which records a certain indicator data of m objects on n time nodes
Collection method	Statistical data	Data on the characteristics, scale, structure, level and other indicators of natural elements in a certain area	Using a certain measurement scale to measure the results of things, different measurement scales get different types of statistical data
	Survey data	Indicator data collected through surveys or observations without external interference	Statistical indicator data about socio-economic phenomena are basically survey observation data
	Experimental data	Metric data collected from control subjects	Much of the data in the natural sciences come from experimental data
Data structure	Structured data	Data with rigorous logical and physical structure stored in the database	It is expressed as a two-dimensional structure, the data is in row units, and the attributes of each row of data are the same
	Semi-structured data	Data with multiple types of textual, irregular, incomplete or implicit structures	Entities belonging to the same class can have different properties; for example, storing employee resumes
	Unstructured data	It can only be stored in the form of various types of files, and the structure is not fixed	Generally stored in binary data format; for example, various documents, pictures, videos, etc.

Division standard	Data types	Connotation	Features
Measurement scale	Categorical data	According to the classification or grouping of certain attributes of objective phenomena, data reflecting the type of things	There is a juxtaposed relationship between each category, and there is no need to distinguish the pros and cons or the size, and the order can be changed arbitrarily; for example, according to the nature of the economy, enterprises are divided into state-owned, collective, private and other economies
	Sequential data	Non-numeric data measured for the level difference or order difference between objective objects	The categories are ordered and can be represented by numerical codes; for example, the test scores can be divided into excellent, good, medium, pass and fail
	Numeric data	The observed value of the objective object measured according to the digital scale, which is expressed as a specific value	Indicates the quantitative characteristics of the objective object; for example, income 1000 yuan, age 20 years, weight 50 kg, etc.
The relationship between objective subject and time	Section data	Observation data of the same indicator of multiple objective objects at the same time point	Obtained in different spaces to describe the changes of objective objects at a certain moment
	Time series data	Observation data of an indicator of an objective object at different time points	Acquired in chronological order, describing how an objective phenomenon changes over time
	Panel data	Sample data composed of multiple cross-sectional sample observations on a time series	Also called “parallel data” or Panel Data, it is an m*n data matrix, which records a certain indicator data of m objects on n time nodes
Collection method	Statistical data	Data on the characteristics, scale, structure, level and other indicators of natural elements in a certain area	Using a certain measurement scale to measure the results of things, different measurement scales get different types of statistical data
	Survey data	Indicator data collected through surveys or observations without external interference	Statistical indicator data about socio-economic phenomena are basically survey observation data
	Experimental data	Metric data collected from control subjects	Much of the data in the natural sciences come from experimental data
Data structure	Structured data	Data with rigorous logical and physical structure stored in the database	It is expressed as a two-dimensional structure, the data is in row units, and the attributes of each row of data are the same
	Semi-structured data	Data with multiple types of textual, irregular, incomplete or implicit structures	Entities belonging to the same class can have different properties; for example, storing employee resumes
	Unstructured data	It can only be stored in the form of various types of files, and the structure is not fixed	Generally stored in binary data format; for example, various documents, pictures, videos, etc.