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<span><p><em><strong>Insights from a Recent Survey</strong></em></p><p><strong>Context</strong></p><p>Knowledge Organisation Systems (KOSs), such as term lists, thesauri, taxonomies, and ontologies, play a fundamental role in categorising, managing, and retrieving information.</p><p>Within the research ecosystem, KOSs are utilised for structuring research areas and their relationships, primarily aiming to organise and enhance retrievability of research articles, academic courses, patents, books, scientific venues, domain experts, grants, software, experiment materials, and several other relevant research outputs.</p><p>These structured representations of research areas, widely embraced by many academic fields, have proven effective in empowering AI-based systems to:</p><ul><li>Enhance the retrievability of relevant documents.</li><li>Enable advanced analytic solutions to quantify the impact of academic research.</li><li>Analyse and forecast research dynamics.</li></ul><p><strong>Insights from a recent survey paper</strong></p><ul><li>45 KOSs of academic disciplines analysed according to five main dimensions: <ul><li>Scope.</li><li>Structure.</li><li>Curation.</li><li>Usage.</li><li>Links to other KOSs.</li></ul></li><li>Results reveal a highly heterogeneous scenario in terms of scope, scale, quality, and usage, underscoring the need for more integrated solutions to represent research knowledge across academic fields.</li><li>Ongoing research efforts aiming to bridge this gap.</li><li>Implications and an exploration of solutions to the challenges identified.</li></ul></span>
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Angelo Salatino
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