Information Technology Reference
In-Depth Information
formed in various domains. We are experiencing a strong demand for more
powerful, intelligent computing paradigms for large-scale data measuring,
collecting, modeling, transforming, exploring and managing [7].
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To study the structures of datasets in data nature;
In data nature, a dataset which we will deal with may be a hard disk full of
data, or a database managed by a certain DBMS, or a Web server, therefore,
we need to study how to access these data from these media or circumstances.
It is critical to analyze storage structure and logical structure of a dataset,
which is called the study on the structures of a dataset.
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To acquire available data from data nature;
Like to explore the golden or the oil, we will acquire available data from data
nature. However, it is different from data mining because it only gets original
data rather than process and analyze data. In general, available data should
be acquired from various data sources in data nature and these data should
be integrated. Sometimes they should be stored in the data warehouse after
data cleaning.
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To prove the rules of data nature by theoretical methods;
Like the research on science, we need to establish many theories and methods,
and present hypothesis, induction, deduction and inference, and build up
logical and theoretical systems in order to solve various problems generating
from data nature.
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To discover the rules of data nature by experimental means;
There are a lot of propositions and rules to be verified. Furthermore, many
valuable results will produce through experiments, which is similar to the
chemical experiments. Therefore, we need to establish various experimental
systems and means in order to discover the rules in data nature.
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To develop and utilize data resources in data nature.
Developing and utilizing data resources is a goal to research data nature,
which will support the research on natural science and social science and
serve for human life and social development. We believe that data resources
are the most important resources in this century (perhaps more important
than oil and coal), therefore, it is an important issue to develop and utilize
data resources in data nature, which is an important topic in dataology.
4.2
The Framework of Dataology
The framework of dataology is shown in Fig. 4. This framework includes two
main parts: foundations of dataology and applications of dataology (e.g., uni-
versal dataology, life dataology, behavior dataology, etc).
Foundations of Dataology.
Foundations of dataology is composed of three as-
pects: data acquisition, data analysis and data awareness. They can be divided
in more detail (see Fig. 4). All these technologies require data management.
There are some existing technologies including data integration, data manage-
ment (e.g., file system, database management system and data warehouse, etc.),
data mining, data visualization, etc. They are developing continuously.
