Rethinking Qualitative Data: AI and Data Types

According to LSE Impact on 10 August 2026, qualitative data includes transcripts plus contextual materials such as silences, fieldnotes, and spatial arrangements; those materials become evidence when they are systematically recorded and compared.

• 1. LSE Impact published the essay on 10 August 2026 and named pauses, hesitations, and spatial arrangements as forms of qualitative evidence.
• 2. The LSE author, Sezai Doruk Soyata, warns on 10 August 2026 that "a transcript can tell us what was said, but it rarely captures the full situation in which something was said."
• 3. Researchers should keep clear audit trails and explain how fieldnotes and absences were turned into findings, as advised by LSE Impact on 10 August 2026.

The LSE Impact essay on 10 August 2026 reframes qualitative data to include non-textual signals as analyzable evidence.

According to the LSE Impact piece, an interview is not only a container of answers but also a social encounter that produces hesitations, laughter, topic shifts and silences that can be analytically meaningful when recorded consistently.

According to the LSE Impact essay, fieldnotes convert observation into evidence by documenting who was present, how a space felt, and what changed after conversations, and the author uses ethnographic examples from Turkey to show how décor and menu design conveyed religious atmospheres without explicit statements.

"An interview is not simply a container for answers, " wrote Sezai Doruk Soyata in LSE Impact on 10 August 2026, and Soyata adds that researchers must ask why and when nonverbal moments occur and whether they repeat across cases.

Researchers should treat qualitative data types as broader than text and plan workflows that capture context before automated processing.

According to LSE Impact on 10 August 2026, failing to record hesitations or spatial cues can strip analysis of evidence that supports claims, so teams must create protocols to capture fieldnotes, audio/video metadata, and researcher reflections.

According to the LSE Impact essay, transparency matters: researchers should explain how absences or silences were judged analytically significant, and where full sharing is impossible they should document what cannot be shared and why.

A practical step is to build an audit trail: record when fieldnotes were written, link them to timestamps in recordings, and flag analytic memos that explain interpretation choices.

The LSE Impact essay on 10 August 2026 reminds researchers that qualitative data types go beyond transcripts to include silences, spatial arrangements and fieldnotes, and teams must document how these materials become evidence.

Practically, research teams should build protocols to timestamp and link fieldnotes to recordings, keep exportable audit trails, and combine human judgement with AI tools for transcription and synthesis.

If you want to pilot a workflow that preserves contextual signals during automated analysis, try integrating transcription, timestamping and thematic synthesis with an AI platform designed for qualitative research like Evidano.

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