Discuss the significance of tracking systems for data management

Discuss the significance of tracking systems for data management

Based on this week’s readings:

A blue and white poster with text  Description automatically generatedDiscuss the significance of tracking systems for data management. How does this work, are there any benefits, and what are some issues to keep in mind?

To efficiently manage data, it is imperative to have a strong understanding of numerous aspects related to data management. This comprises tracking information such as business clustering, data system catalog, report catalog, data flow catalog, lineage, data requests, reference data, data quality, data ownership and domains, documents, policy attributes, change management, and external data standards and reporting. 

Data management includes the organization, storage, and retrieval of data within a group. It is central for businesses to have an organized approach to handling their data in order to safeguard efficiency, accuracy, and compliance. This week we will explore the key aspects of understanding and tracking data management and the different platforms that are currently in the market. As always- the devil is in the details- we will look at their benefits and risks.

Looking forward to a great week!

Data Collection, Testing, and Observation/Data Collection Interviewing

Greetings class,

Welcome to week 4 where things begin to become interesting. This week’s lesson will cover chapters 12-13 and The Belmont Report and will focus on participant recruitment and data collection. Topics covered include recruitment, retention, preparation for collecting data, and interviewing individuals and groups. Structured, semi-structured, and unstructured interviews are also covered. 

After completing this lesson, you are expected to:

·      Describe the ten steps for participant recruitment.

·      Define testing and observation as they relate to data collection.

·      Explain how to interview for data collection. 

As you continue to advance this week, please keep in mind the information you obtained last week which focused on ethical issues, consents, as well as participant recruitment. Remember these conditions must be met prior to engaging in research studies, especially where human subjects are involved. So, with that being said, let’s think about data and its management.

What is data?

Basically, data or the plural form is called “datum.” Essentially data are pieces of information or facts that are collected for a research study. This is carried out through data collection procedures. Ideally, collected data procedures are one that captures the information in a way that is relevant, credible, accurate, truthful, and sensitive. The method in which data is collected should be objective (free of bias) and systematic. It must be appropriate to the problem, the hypothesis, the setting, and the population.

What is research data management?

Research data management (or RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the everyday management of research data during the lifetime of a research project (for example, using consistent file naming conventions). It also involves decisions about how data will be preserved and shared after the project is completed (for example, depositing the data in a repository for long-term archiving and access).

Data management planning and things to consider.

An important first step in managing your research data is planning. To get you started thinking about data management planning, here are some of the issues you need to consider:

· Your institution’s and funding agency’s expectations and policies

· In many cases, you need Institutional Review Board (IRB) permission prior to the collection of data

· Whether you collect new data or reuse existing data

· The kind of data collected and its format

· The quantity of data collected

· Whether versions of the data need to be tracked

· Storage of active data and backup policy and implementation

· Storage and archiving options and requirements

· Organizing and describing or labeling the data

· Data access and sharing

· Privacy, consent, intellectual property, and security issues

· Roles and responsibilities for data management on your research team

· Budgeting for data management


What is Data?


What is data management – and why do you need it in interdisciplinary life sciences?


Tests of Function, Physical Assessment Measures, and Biological Tests are types of data testing

Testing of Data (Suggestions for Improvement)

· Make sure everyone is looking at the same requirements.

· Write a test plan.

· Decide what to test.

· Decide where to test.

· Decide how much to test.

· Keep an eye out for odd things.

· Stay focused on what you are trying to test.

Website Link – Testing:

This link features a publication by Karis Van Valin 11/27/2017 where he expands on the suggested data testing improvement techniques.



According to the literature, observations are a way of collecting data through monitoring/watching. The observation data collection method is classified as a participatory study because the researcher has to immerse himself/herself in the setting where her respondents are while taking notes and/or recording.

Video: Research Methods: Observations


Video: Types of Observations



Interviews can be defined as a qualitative research technique that involves “conducting intensive individual interviews with a small number of respondents to explore their perspectives on a particular idea, program or situation.”

Boyce, C. & Neale, P. (2006). Conducting in-depth interviews: A guide for designing and conducting in-depth interviews, Pathfinder International Tool Series

Video: Qualitative analysis of interview data: A step-by-step guide


Video: Unstructured, Semi-Structured and Structured Interviews


*Remember APA guidelines regarding references and citations in your discussion posts.


Contact the Writing Lab Director:

Prof. Ileana Torres

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Dr. Pupo