Re-SearchTerms: A Shiny app for exploring terminology variations in psychology and metascience

The wording of definitions for terms in open scholarship and research practices may be inconsistent, making it difficult for researchers to understand and apply them accurately. This hinders clear and effective communication in research. To address this, we developed “Re-SearchTerms”, a Shiny app that encourages researchers to revisit and critically examine the meanings of common research terms related to open scholarship and research practice used in diverse research contexts. This interactive platform enables the exploration and comparison of definitions from multiple sources, prompting users to reflect on the nuanced meanings and contexts of key terms. Our dataset includes 2211 definitions of 216 concepts related to open scholarship, research practices, statistical analysis, and philosophy-of-science terminology. Definitions are sourced from academic texts, the crowdsourced FORRT glossary (Parsons et al., 2022), and Wiktionary (Meyer, 2018). Using natural language processing (NLP) techniques, Re-SearchTerms visualises term relationships based on word co-occurrences and sentence embeddings, allowing users to investigate co-occurrence patterns and explore concept-level networks. Moreover, we identify concepts with high and low semantic consistencies based on their definitions. Low similarity suggests variability in how researchers define and potentially understand a given term. This finding underscores the need for researchers to pay closer attention to the use of concepts, especially those with low consistency. Our app helps researchers make deliberate and informed choices when defining and interpreting key terms. Our adaptive framework can be applied to other datasets of research concepts, enabling researchers to examine and select terminology, especially in interdisciplinary fields.