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Documentation and Gathering of Data
Bibliography
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Introduction
At the center of any good data management is documentation which is instrumental in
introducing your data, providing a detailed description of their key attributes, and contextualizes
them. More importantly, documentation linked to the research project describes what the
researchers did and why they made such choices (Blank & Rasmussen, 2004). In this respect,
documentation provides detailed about the context of data gathering, how data was collected, and
the form in which it was collected. Moreover, documentation also describes what the gathered
data is about, how it is formatted, organized, and structured, as well as how the researcher
manipulated or transformed the data. Data gathering is the process of collecting and assessing
information on variables of interest, in a well-known methodical manner that enables one to
answer stated research questions, test hypotheses, and assess results (Gurat, 2018). Also,
documentation shows how you validated data, its ethical limits, and how you analyzed the data.
Clear, thorough documentation is instrumental to the researchers and other scholars who may reuse the data in future. Moreover, good documentation plays a vital role in helping researchers get
clarity on and remember details regarding their data and its provenance, to evaluate the data’s
quality and evidentiary value, and to avert misinterpreting or erroneously using the data (Blank
& Rasmussen, 2004). There are various examples of data documentation, including
questionnaires used for surveys, guidance materials utilized for team-based fieldwork,
instructions for focus group facilitation, and consent forms, among others. This paper explores
four-academic sources related to the topic of my essay: critically evaluating documentation and
gathering of data as one academic area from my IFP modules.
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Bibliography
Blank, G., & Rasmussen, K. B. (2004). The data documentation initiative. Social Science
Computer Review, 22(3), 307–318. https://doi.org/10.1177/0894439304263144
Blank & Rasmussen (2004) in their article underline the importance of having good
documentation to facilitate effective secondary analysis of social science data. Based on this
article, the standardization of internet access has heightened the problem of reading and
comprehending the contents of data files. In this respect, the authors recommend the
standardization of documenting data to resolve such problems. There is a need to have standard
formats for both documentation and data that can be read and displayed by software and
computers anywhere in the world. The author provides the data documentation initiatives created
by the North American and European Survey research and data archive organizations to help
define the documentation standard. According to Blank & Rasmussen (2004) data documentation
refers to the “rich, full technical documentation of a data set…providing information about
sponsorship, history, structure, design, setting, and limitations of data sets” (p.310). Accurate
documentation plays a vital role in facilitating easy, accurate utilization of data. Based on this
article, research and teaching utilization of data requires accurate documentation.
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Gurat, M. (2018). College students’ data management skills in a private university in the
Philippines. International Journal of Social Sciences & Educational Studies, 5(2).
https://doi.org/10.23918/ijsses.v5i2p1
According to Gurat (2018), data management skills refers to the’ abilities that individuals utilize
effectively to use and manage information, including exploring patterns, understanding database
design concepts, data analysis, file and account management, business intelligence, database
planning and design, data integrity, and communication. Based on this article, every person must
be equipped with skills and knowledge in managing data because our society can only be
understood via data around us. In this respect, Gurat (2018) sought to explore the college
students’ data management skills by conducting a mixed method research using descriptive
approach. The study used undergraduate schools of Saint Mary’s University at Bayombong ,
Philippines. The researcher sought to understand the college students’ ability to effectively
handle data for easy access, including arranging or sorting and coding. The findings established
that most of the college students were fairly skillful in managing data. The findings also
established that the students’ data management skills are not yet completely achieved.
Consequently, the article recommends that data management skills should be taught as much as
computation or writing skills are taught due to the significance it plays in the society.
“Based on the analyzed data, it was found that most of the students have moderately skillful data
management. The data management skills of the students are not yet fully achieved. Hence, each
individual must be equipped with knowledge and skills in managing data even if standard
methods of managing data already exist” (Gurat, 2018).
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Taherdoost, H. (2021). Data Collection Methods and Tools for Research; A Step-by-Step Guide
to Choose Data Collection Technique for Academic and Business Research Projects.
International Journal of Academic Research in Management (IJARM), 10(1), 10–38.
https://doi.org/10.4135/9781071802731.n6
One of the fundamental steps in the research study is data gathering which enables researchers to
find answers to the research question. According to Taherdoost (2021), data gathering refers to
the process of collecting data to gain insights concerning the research topic. Based on this article,
there are various types of data and data collection methods. The article also underlines the
difficulties involved in selecting an appropriate data gathering method based on the type of data
utilized in the study. Consequently, Taherdoost (2021) provides a comprehensive source for data
gathering methods, such as defining the data gathering process and deliberating the main types of
data. Furthermore, the author also explains the possible methodologies for collecting data based
on these categories. Also, the article defines the benefits and disadvantages of using the various
data gathering methods and lists the primary challenges of data gathering, as well as reviewing
the ethical consideration in this process. the types of data described in this article includes
qualitative and quantitative data, while data gathering methods are divided into two main
categories, including primary and secondary data gathering methods. According to Taherdoost
(2021, p. 12), “generally, data collection methods are divided to two main categories of Primary
Data Collection Methods and Secondary Data Collection Methods.”
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Extract from the article on the types of data gathering methods
Source: Taherdoost (2021, p.13)
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Suresh, G., Suresh, K., & Thomas, S. V. (2011). Design, data analysis and sampling techniques
for clinical research. Annals of Indian Academy of Neurology, 14(4), 287.
https://doi.org/10.4103/0972-2327.91951
According to Suresh, Suresh, & Thomas (2011), Statistical analysis plays an instrumental role in
enabling researchers to draw meaningful inference from their data analysis. Therefore, based on
this study, inappropriate utilization of research design and data analysis is likely to render
improper and insufficient outcomes and conclusion. Translating research problem into the
statistical premise with suitable logical and methodological design and them back-translating the
statistical outcomes into relevant knowledge that can be used to make informed decision is a
critical challenge for the researchers. Therefore, this article describes different sampling methods
that can be appropriately utilized, especially in medical studies with diverse challenges and
scenarios. The researchers underline the importance of ensuring data analysis and sampling
techniques for clinical studies have excellent validity and reliability. Based on the article,
researchers can utilize probability sampling methods to get unbiased outcomes to guarantee valid
and reliable inferences from the sample. According to Suresh, Suresh, & Thomas (2011),
“Validity is the degree to which the investigative goals are measured accurately. The degree to
which the research truly measures what it intended to measure determines the fundamentals of
medical research.”
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References
Blank, G., & Rasmussen, K. B. (2004). The data documentation initiative. Social Science
Computer Review, 22(3), 307–318. https://doi.org/10.1177/0894439304263144
Gurat, M. (2018). College students’ data management skills in a private university in the
Philippines. International Journal of Social Sciences & Educational Studies, 5(2).
https://doi.org/10.23918/ijsses.v5i2p1
Suresh, G., Suresh, K., & Thomas, S. V. (2011). Design, data analysis and sampling techniques
for clinical research. Annals of Indian Academy of Neurology, 14(4), 287.
https://doi.org/10.4103/0972-2327.91951
Taherdoost, H. (2021). Data Collection Methods and Tools for Research; A Step-by-Step Guide
to Choose Data Collection Technique for Academic and Business Research Projects.
International Journal of Academic Research in Management (IJARM), 10(1), 10–38.
https://doi.org/10.4135/9781071802731.n6