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My Research – Choosing the right data

My Research – Choosing the right data

Web-based search tool filtering recipes online based on 14 allergen groups.

To support this research project, a wide range of qualitative and quantitative data types can be utilised using a qualitative, quantitative or mixed-method approach (Urban, JB, & van EBM, 2017).

Qualitative Data is any descriptive data that deals with actual words, stories, pictures or videos, and gives an extra depth and user insight. This could be:

  • user interviews,
  • surveys,
  • user feedback,
  • observations of users and their behaviour during any testing stages.

This type of data complements quantitative data and helps explain ‘how’ and ‘why’ the tool works by capturing both experiential and cognitive aspects.

Quantitative Data is any numerical and measurable data, such as weight or rankings on a scale. This type of data allows for objective evidence of performance and statistical tests and includes:

  • Task success rate,
  • Error rate,
  • Task completion time,
  • System Usability Scale score – SUS.

Considering the nature and technical aspects of the web-based search tool being developed in this project, the mixed-method approach is the most appropriate.

This approach will provide strong statistical evidence supported by user experience insights
and a deeper understanding of the performance of the algorithms used in the tool. The most accurate combination of data types is as follows:

Primary Data to support the tool’s performance during all stages of development:

  1. Quantitative Data for efficiency and usability scores, including task completion time, Task success rate, error rate, System Usability Scale, and number of recipes retrieved during each search session.
  2. Textual data for processing and storage in a database, including titles of recipes, lists of ingredients, instructions and keywords for allergen classification.
  3. Qualitative Data for user experience analysis and insight, including user interviews, surveys, and observations on click patterns, errors in navigation, or user-hesitation or confusion patterns during usability testing.

Secondary Data to give an understanding of existing search tools, highlight the areas of focus, any issues that require improvement and identify potential risks:

  1. Pre-existing qualitative data collected during the literature review on existing web-based search tools for recipe finding interface and their performance, user satisfaction and trust, and compliance with Food Information Regulation and labelling practices.
  2. Pre-existing quantitative data from market research and publications on usability and efficiency statistics for existing recipe search tools.

As well as the above data types, the following data will be produced during the development of the tool:

  • The Textual Data – all recipe titles, instructions and ingredient lists collected by web-scraping and stored in a database, used primarily for algorithmic processing in the classification and allergen detection.
  • The Processed Data – data generated from the Raw data by cleaning and normalisation, such as allergen classification and recipe categorisation.
  • The Metadata – structured data to describe the main collected data and enhance the organisation, discovery, and data quality management (Lu, 2024), such as the source of the website, URLs, data and time of scraping, type of cuisine etc, used for faceted search filtering and for analysis.
  • The data generated by the system – any scraped recipes logs, errors, search query metadata.
  • The data collected from usability testing, such as the click patterns, errors or patterns in user behaviour – helpful in refining the UI/UX.

References:

Lu, T. (2024) What is Metadata? A Guide to Understanding Data About Data [online] Available from: https://www.datacamp.com/blog/what-is-metadata?utm_cid=19589720821&utm_aid=186331391909&utm_campaign=230119_1-ps-other~dsa~tofu_2-b2c_3-emea_4-prc_5-na_6-na_7-le_8-pdsh-go_9-nb-e_10-na_11-na&utm_loc=9045798-&utm_mtd=-c&utm_kw=&utm_source=google&utm_medium=paid_search&utm_content=ps-other~emea-en~dsa~tofu~blog~data-governance&gad_source=1&gad_campaignid=19589720821&gbraid=0AAAAADQ9WsEQdQdAPhoaaVNxHDuPlABdt&gclid=Cj0KCQiAoZDJBhC0ARIsAERP-F_mh2MmSN8jrTjDW2HSweB2GQGKh6oxv9ln5weZb491pWstaLwZYdcaAn9vEALw_wcB [Accessed: 21 November 2025]

Urban, JB, & van, EBM 2017, Designing and Proposing Your Research Project, American Psychological Association, Washington, D. C.. Available from: ProQuest Ebook Central. [Accessed: 20 November 2025].

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