It is important to complete the following steps before collecting data:
1. Search for any existing data (secondary data) related to you subject or your project:
Search the web or data repositories.
2. Decide what file naming conventions, file structure and documentation methods you will use for your data
It is important to document the context and methodology of your data collection. Documentation should cover how data were collected, when and where they were created, organisation of the files, access, quality control, etc. Text files are often used to describe contextual information. Documenting data ensures research data will be discoverable and useable. Metadata is often used in documentations for managing data.
Metadata is a set of data describes other data. It provides information about an item or the content of a collection. Metadata is used for resource discovery, providing searchable information, a bibliographic record for citation, or for online data browsing.
Metadata used for data or data collection usually contain the purpose, authors, timeframe, location, and subjects/keywords.
Use a vocabulary to describe your data:
Accessibility and long term preservation are two key points for considering data file formats. Open, unencrypted and uncompressed file formats are easier to be preserved.
A file name should be short and descriptive. Version control is a system of keeping, tracking and recording changes to files. It ensures that the most recent file can be easily identified, and there is an audit trail of changes.
Organising your files in a hierarchical file structure and chronological subfolders may help you better manage your files.
Software Carpentry's video provides some good advice on file structure, version control, metadata and documentations.
Quality control activities ensure that the data is reliable, valid and reproducible.
Quality checking during data collection:
Quality checking after data collection:
Māori data are data that are produced by Māori, and data that are about Māori and the environments we have relationships with. Data are a living tāonga and are of strategic value to Māori. Māori data include but are not limited to:
Data from government agencies, organisations and/or businesses
Data about Māori that are used to describe or compare Māori collectives
Data about Te Ao Māori that emerges from research