Review of literature resources is an important and essential process in development of any research study. Understanding the difference and effectiveness of each type of literary resource will help to answer research questions or test a hypothesis. The three different types of literature resources are primary, secondary, and tertiary. Most new researchers are familiar with primary resources, were the researcher gathers information and data directly from their recruited subjects (Garrard, 2007). When the context is vague, secondary and tertiary resources often get grouped together (Garrard, 2007). The purpose of this paper will be to effectively distinguish secondary and tertiary resources, identify the advantages and disadvantages, how and where to access this data, proper storage and filing once giving access rights, and data ownership.
Distinguishing Secondary from Tertiary Data
 Secondary data is data accessed by a researcher outside of the original study. They then produce their own analysis and interpretation, different than the original (Garrard, 2007; Tantawi, 2017). For example, instead of a researcher conducting a questionnaire about patient satisfaction, the data collected by a hospital is used to answer their own hypothesis about patient satisfaction. U.S. Census and Center for Disease Control National Database for Health Statistics as examples of larger public access secondary data sources.

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Tertiary data is a collection of primary and secondary data that is filtered and analyzed together. A tertiary resource is of value to a researcher in that it can group information into one database or one article, can lead the researcher to significant primary and secondary resources and datasets, can analyze larger quantities of research studies or research data that are related to one another, and can assist in referencing a comprehensive article or dataset gathered by another researcher (Garrard, 2007). For example, by locating systematic reviews in the Cochrane Library Database, the authors of these articles have already gathered primary and secondary sources and data into one location based on a similar topic. Most systematic review studies will have inclusion and exclusion criteria in their methods and will filter works that do not meet a specific standard. A meta-analysis is another example of tertiary data collection and is defined by pooling statistics systematically from journal articles (Garrard, 2007). 
Advantages and Disadvantages of Secondary and Tertiary Data Sources
The use of secondary data sources has a variety of advantages. These include peer reviews that insure quality, expert perspective and insight. Secondary data collection can be more financial and labor efficient than going through the planning and execution of your own research intervention and data analysis (Tantawi, 2017). Disadvantages of secondary research is that there is no control over the quantitative component (experiment) or a qualitative component (survey questions). This is seen more in qualitative data in which an author may not have described the survey methods or structured the question appropriate leaving too much subjective bias in the data (Tantawi, 2017; Irwin, 2013).
There is value in using tertiary data. When first starting the literary review process, tertiary data sources offer quick and easy access to enormous amounts of digitalized information that can be gather and deposited into one database (Garrard, 2007). For example, statistical compendiums like the Annual Disability Statistics Compendium. The disadvantage to using tertiary data is that it may be over simplistic or misrepresent information. Relying on tertiary data may result in loosing insight into the research topic (Garrard, 2007).
Data Access and Management
The collection and use of secondary data can be defined as published or unpublished and also defined as private and public (Tantawi, 2017; Tripathy, 2013) Published secondary data can be collected from government and federal databases, like Centers for Medicare and Medicaid Services (CMS). Secondary data can also be collected from published journal articles and scientific reports. An example of unpublished sources wound be a university professor’s correspondence. Care must be taken when evaluating the quality of the data, including a check for reliability, validity, bias, and appropriateness for answering a researcher’s hypothesis (Tripathy, 2013; Bevan, et al., 2013).  
Having access to protocols methods via permission from the primary researchers is essential in determining adequacy of the data. Having access permissions to the raw dataset is what allows for the secondary researchers to perform their own analysis on the original data (Tripathy, 2013; Irwin, 2013). In addition, if informed consent signed by the subject did not included access of their personal information or private health information by anyone other than the primary investor or co-investigator for the primary study, then the secondary data set may require the subject to consent again for secondary data access (Irwin, 2013; Heaton, 2008).

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With tertiary data collections from systematic reviews, data is extracted into tables and compared to the research question by listing out descriptive characteristics of the studies. In a meta-analysis, comparable data is pooled into one summary statistic from similar studies. Computer software program can analyze the data into a confidence interval and are weighted based on population size of the contributing studies (Garrard, 2007).
Research data management involves collection, processing, storing, sharing, and ownership of research data throughout the life of the study and after the study ends. Data ownership pertains to who has the legal rights to the data and who retains the data after the study ends. It is important to understand who can possess and publish data. Ownership is dependent on funding, affiliations and sources of the research itself (Garrard, 2007; Office of Research Integrity, 2006). When there is a sponsoring university, the primary investigator becomes the steward for the data and can control if the data gets published and copyrights of any research contingent on review. A funding from federal grants, private sponsors, and non-profit associations may have stipulations on how the data will be used and retained. In the private sector, it is usually assumed that the data will belong to the business. Study subjects may also have an interest in the data being collected. Whether or not a subject can have access to their own data or a summarization of data analyzed from the study should be detailed out in the informed consent (Office of Research Integrity, 2006; Tripathy, 2013).
Data storage pertains to where and the amount of data to be stored so the methods can be reproducible. Using electronic data management storage is a low cost, easy way to archive data (Office of Research Integrity, 2006). Data storage security includes the use of encrypted serves, computers, and file with limited access by key study personnel. Some institutions use a data protection database software program, especially if the primary investigator cannot secure a locked office (Office of Research Integrity, 2006).
Conclusion
The literature review process is an essential component of a research study’s development. It is up to the research team to select appropriate resources (secondary or tertiary) and raw data to assist in answering their research question. Every researcher must make sure they consider the following when evaluating datasets: adequacy, reliability, and validity for answering the research question. In addition, there are ethical and legal standards for handling data. The research team should answer the following: Is the data open access or private? Does the data involve human subjects? Does the data de-identify human subject private information? Are there restrictions on the data’s use? Is a secondary informed consent required to access the data?
References

Garrard, J. (2007). Chapter 2: Basic Concepts. Health science literature review made easy: The matrix method (2nd ed., pp.30-32). Sudbury, MA: Jones and Bartlett Publishers.
Tantawi, R. (2017). Secondary data. Salem Press Encyclopedia. Retrieved from       Retrieved from http://prx-sa.lirn.net/login?url=http://search.ebscohost .com/login.aspx ?direct=true&db=ers&AN=90558446&site=eds-live.
Tripathy J. P. (2013). Secondary Data Analysis: Ethical Issues and Challenges. Iranian Journal of Public Health, 42(12), 1478-9.
Bevan, S. et al. (2013). Understanding selection bias, time-lags and measurement bias in secondary data sources: Putting the Encyclopedia of Associations database in broader context. Social Science Research, 42(6), 1750–64. Print.
Irwin, S. (2013). Qualitative secondary data analysis: Ethics, epistemology and context. Progress in Development Studies, 13(4), 295–306. Print.
Heaton, J. (2008). Secondary analysis of qualitative data: An overview. Historical Social Research, 33(3), 33-45.
Office of Research Integrity, U.S. Department of Health and Human Services (2006). Guidelines for responsible data management in scientific research. Retrieved from https://ori.hhs.gov/education/products/clinicaltools/data.pdf