The very first step in talking about data is to ask yourself "What is data'?
There are many definitions of data and it comes in a variety of types and forms. A definition from the OECD, 2007 is:
'factual records (numerical scores, textual records, images and sounds) used as primary sources for scientific research, and that are commonly accepted in the scientific community as necessary to validate research findings."
Data may be gathered from raw or primary sources (obtained directly from a measurement or collection) or it could be extracted from a larger primary dataset and 'cleaned up', for use in another project. Data is primarily used to support or validate a research projects findings.
The following table outlines some of the common types and formats that can represent data - this is not an exhaustive list!
|Data formats||Data Types|
|Documents (Text, pdf, MS Word)||Results from clinical trials|
|Spreadsheets (MS Excel)||Measurements collected from fieldwork|
|Questionnaires, surveys, transcripts||Questionnaire responses|
|Slides, samples, specimens||Images|
|Diaries, journals and notebooks||Social media data (Tweets)|
|Raw data generated from software||Transcripts|
|Log files and schemas from software||Software programme outputs|
Source: Exploring research data management
When you decide to undertake any kind of research you will need to consider how you will create, find, organise, store, share and preserve the data for the project. Once the project is finalised thought for the ongoing access and availability should also be considered.
Research Data Management should begin with the commencement of the research project and continue throughout the research lifecycle.
If you intend to use NT Health data in your research project the Data Governance NT Health Framework and Data Standards will assist you in understanding how NT Health have created best practice standards for ensuring long term preservation and access of health data. With this in mind, you can plan to manage the data from your own project and ensure it remains secure, accessible and viable into the future.
Managing your research data is important for the following reasons:
No one should ever embark on a major journey without a plan. This should also be the case when you decide to take on a research project. Thinking ahead and planning is an important first step in considering all the possible details that will impact the process and its eventual completion.
In Exploring Research Data Management, Cox and Verbaan (2018, p.116) assert that a data management plan has the potential to improve research data management as long as the following concepts are considered:
There are many data management plans available through reputable research organisations that can give you guidance about what is expected in preparing your own data management plan. We recommend you look at the following sites and documents and adapt one that will suit the research project that you are undertaking
Clinical Research Data Management Templates
|NHMRC Management of Data and Information in Research > View|
|Medical Research Council (MRC) Template for a Data Management Plan > View|
|National Cancer Institute Master Data Management Plan Template > View|
|NIH NIDCR’s Clinical Data Management Plan Template > View|
Non-Clinical Research Data Management Templates
|Australian National Data Service (ANDS) Data Management Plans > View|
|Australian Research Data Commons - Data Management Plans > View|
This short video takes a look at the what, why and how of a data management plan
MANTRA is a free online self-paced course that will help you understand all the necessary components to manage your digital data successfully.