{"id":17875826,"url":"https://github.com/constraintautomaton/introducing-collaborative-link-traversal-query-processing","last_synced_at":"2026-03-19T02:16:54.159Z","repository":{"id":165246012,"uuid":"617895845","full_name":"constraintAutomaton/Introducing-Collaborative-Link-Traversal-Query-Processing","owner":"constraintAutomaton","description":"Doctoral project proposal where I introduce Collaborative Link Data Query Processing, a paradigm where multiple query engines collaborate to improve query completeness and execution time in Link Traversal Query 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Introducing Collaborative Link Traversal Query Processing in the Context of Structured Decentralized Environments\nAvailable as a web page at https://constraintautomaton.github.io/Introducing-Collaborative-Link-Traversal-Query-Processing/\n## Abstract\nDecentralized web environments aim to give users data autonomy and control.\nData sovereignty focus on two aspects: privacy and provider choice.\nHowever, the concept remains incomplete if it fails to incorporate the actual utilization of the data.\nSpecifically, in the context of application functionality,\ndata sovereignty can be relinquished to the owner of the computational units or applications.\nThe exploration and retrieval of information are core functionalities of web-based social\napplications because it is from those mechanisms that shared experiences to foster interactions are created.\nA promising example of web discovery techniques is Link Traversal Query Processing (LTQP),\na SPARQL query paradigm that aims at exploring the web to answer queries by following the links between documents.\nIn my doctoral research, I introduce Collaborative Link Data Query Processing,\na paradigm where multiple query engines collaborate to improve query result completeness and execution performance in LTQP.\nI divide the research on the cooperation of query engines into two parts: 1) Improving the completeness of results, by exploring more of the search space,\nand 2) reducing the potentially long query execution time by caching results.\nTo validate this proposal, I will develop a prototype and evaluate it using existing benchmarks.\nBased on my analysis of the state of the art,\nprevious studies have made contributions to collaborative SPARQL query execution and RDF peer-to-peer caching.\nHowever, there is currently a research gap regarding the investigation of such systems in\nthe context of LTQP within a structured decentralized environment.\n\n## Editing the article\n### Development mode\n```\nbundle install\nbundle exec guard\n```\n\n### Build\n```\nbundle install\nbundle exec nanoc compile\n```\n\nView on http://localhost:3000/\n\n## License\nThe code is licensed under the CC-BY-4.0 license. See the [LICENSE](LICENSE) file for details.\n\n**This article makes use of the [ScholarMarkdown](https://github.com/rubensworks/ScholarMarkdown/) framework.**\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fconstraintautomaton%2Fintroducing-collaborative-link-traversal-query-processing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fconstraintautomaton%2Fintroducing-collaborative-link-traversal-query-processing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fconstraintautomaton%2Fintroducing-collaborative-link-traversal-query-processing/lists"}