Understanding the Information Research Process of Experienced Online Information Researchers to Inform Development of a Scholars Portal
Bibliographic record
Abstract
Objective - The main purpose of this study was to understand the information research process of experienced online information researchers in a variety of disciplines, gather their ideas for improvement and as part of this to validate a proposed research framework for use in future development of Ontario’s Scholars Portal. Methods - This was a qualitative research study in which sixty experienced online information researchers participated in face-to-face workshops that included a collaborative design component. The sessions were conducted and recorded by usability specialists who subsequently analyzed the data and identified patterns and themes. Results - Key themes included the similarities of the information research process across all disciplines, the impact of interdisciplinarity, the social aspect of research and opportunities for process improvement. There were many specific observations regarding current and ideal processes. Implications for portal development and further research included: supporting a common process while accommodating user-defined differences; supporting citation chaining practices with new opportunities for data linkage and granularity; enhancing keyword searching with various types of intervention; exploring trusted social networks; exploring new mental models for data manipulation while retaining traditional objects; improving citation and document management. Conclusion – The majority of researchers in the study had almost no routine in their information research processes, had developed few techniques to assist themselves and had very little awareness of the tools available to help them. There are many opportunities to aid researchers in the research process that can be explored when developing scholarly research portals. That development will be well guided by the framework ‘discover, gather, synthesize, create, share.’
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.066 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".