{"id":{"repo_id":"salford","oai_identifier":"oai:salford-repository.worktribe.com:1369183"},"canonical_url":"https://search.dev.ndltd.org/etd/salford/oai:salford-repository.worktribe.com:1369183","repository":{"repo_id":"salford","name":"U. of Salford","base_url":"https://salford-repository.worktribe.com/oaiprovider"},"display":{"title":"Semantics-enriched workflow creation and management system with an application to document image analysis and recognition","abstract":"Scientific workflow systems are an established means to model and execute experiments or processing pipelines. Nevertheless, designing workflows can be a daunting task for users due to the complexities of the systems and the sheer number of available processing nodes, each having different compatibility/applicability characteristics. This Thesis explores how concepts of the Semantic Web can be used to augment workflow systems in order to assist researchers as well as non-expert users in creating valid and effective workflows. A prototype workflow creation/management system has been developed, including components for ontology modelling, workflow composition, and workflow repositories. Semantics are incorporated as a lightweight layer, permeating all aspects of the system and workflows, including retrieval, composition, and validation. Document image analysis and recognition is used as a representative application domain to evaluate the validity of the system. A new semantic model is proposed, covering a wide range of aspects of the target domain and adjacent fields. Real-world use cases demonstrate the assistive features and the automated workflow creation. On that basis, the prototype workflow creation/management system is compared to other state-of-the-art workflow systems and it is shown how those could benefit from the semantic model. The Thesis concludes with a discussion on how a complete infrastructure based on semantics-enriched datasets, workflow systems, and sharing platforms could represent the next step in automation within document image analysis and other domains.","abstract_html":"Scientific workflow systems are an established means to model and execute experiments or processing pipelines. Nevertheless, designing workflows can be a daunting task for users due to the complexities of the systems and the sheer number of available processing nodes, each having different compatibility/applicability characteristics. This Thesis explores how concepts of the Semantic Web can be used to augment workflow systems in order to assist researchers as well as non-expert users in creating valid and effective workflows. A prototype workflow creation/management system has been developed, including components for ontology modelling, workflow composition, and workflow repositories. Semantics are incorporated as a lightweight layer, permeating all aspects of the system and workflows, including retrieval, composition, and validation. Document image analysis and recognition is used as a representative application domain to evaluate the validity of the system. A new semantic model is proposed, covering a wide range of aspects of the target domain and adjacent fields. Real-world use cases demonstrate the assistive features and the automated workflow creation. On that basis, the prototype workflow creation/management system is compared to other state-of-the-art workflow systems and it is shown how those could benefit from the semantic model. The Thesis concludes with a discussion on how a complete infrastructure based on semantics-enriched datasets, workflow systems, and sharing platforms could represent the next step in automation within document image analysis and other domains.","abstract_has_math":false,"creators":["Clausner, C"],"institution":null,"degree_name":null,"degree_level":"Doctoral (Level 8)","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026","date_published":"2026","updated_at":"2026-07-24T04:26:23Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:salford-repository.worktribe.com:1369183"],"render_values":[{"text":"oai:salford-repository.worktribe.com:1369183","href":null,"code":true}]},{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000-0001-6041-1002"],"render_values":[{"text":"0000-0001-6041-1002","href":"https://orcid.org/0000-0001-6041-1002","code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.sponsor","label":"Sponsor","values":["University of Salford"]},{"key":"dc:creator","label":"Author","values":["Clausner, C"]},{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000-0001-6041-1002"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2026-07-24"]},{"key":"dc:date.issued","label":"Date","values":["2026"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://salford-repository.worktribe.com/output/1369183"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral (Level 8)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:salford-repository.worktribe.com:1369183"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://salford-repository.worktribe.com/1369183/1/PhD%20Thesis%20Christian%20Clausner%20-%20Master%20file.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Scientific workflow systems are an established means to model and execute experiments or processing pipelines. Nevertheless, designing workflows can be a daunting task for users due to the complexities of the systems and the sheer number of available processing nodes, each having different compatibility/applicability characteristics. This Thesis explores how concepts of the Semantic Web can be used to augment workflow systems in order to assist researchers as well as non-expert users in creating valid and effective workflows. A prototype workflow creation/management system has been developed, including components for ontology modelling, workflow composition, and workflow repositories. Semantics are incorporated as a lightweight layer, permeating all aspects of the system and workflows, including retrieval, composition, and validation. Document image analysis and recognition is used as a representative application domain to evaluate the validity of the system. A new semantic model is proposed, covering a wide range of aspects of the target domain and adjacent fields. Real-world use cases demonstrate the assistive features and the automated workflow creation. On that basis, the prototype workflow creation/management system is compared to other state-of-the-art workflow systems and it is shown how those could benefit from the semantic model. The Thesis concludes with a discussion on how a complete infrastructure based on semantics-enriched datasets, workflow systems, and sharing platforms could represent the next step in automation within document image analysis and other domains."]},{"key":"dc:title","label":"Title","values":["Semantics-enriched workflow creation and management system with an application to document image analysis and recognition"]}]}],"canonical_facts":{"dc:contributor.sponsor":["University of Salford"],"dc:creator":["Clausner, C"],"dc:creator.authoridentifier":["0000-0001-6041-1002"],"dc:date":["2026-07-24"],"dc:date.issued":["2026"],"dc:description.abstract":["Scientific workflow systems are an established means to model and execute experiments or processing pipelines. Nevertheless, designing workflows can be a daunting task for users due to the complexities of the systems and the sheer number of available processing nodes, each having different compatibility/applicability characteristics. This Thesis explores how concepts of the Semantic Web can be used to augment workflow systems in order to assist researchers as well as non-expert users in creating valid and effective workflows. A prototype workflow creation/management system has been developed, including components for ontology modelling, workflow composition, and workflow repositories. Semantics are incorporated as a lightweight layer, permeating all aspects of the system and workflows, including retrieval, composition, and validation. Document image analysis and recognition is used as a representative application domain to evaluate the validity of the system. A new semantic model is proposed, covering a wide range of aspects of the target domain and adjacent fields. Real-world use cases demonstrate the assistive features and the automated workflow creation. On that basis, the prototype workflow creation/management system is compared to other state-of-the-art workflow systems and it is shown how those could benefit from the semantic model. The Thesis concludes with a discussion on how a complete infrastructure based on semantics-enriched datasets, workflow systems, and sharing platforms could represent the next step in automation within document image analysis and other domains."],"dc:identifier":["oai:salford-repository.worktribe.com:1369183"],"dc:identifier.uri":["https://salford-repository.worktribe.com/1369183/1/PhD%20Thesis%20Christian%20Clausner%20-%20Master%20file.pdf"],"dc:language":["en"],"dc:relation.isreferencedby":["https://salford-repository.worktribe.com/output/1369183"],"dc:title":["Semantics-enriched workflow creation and management system with an application to document image analysis and recognition"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral (Level 8)"]},"updated_at":"2026-07-24T04:26:23Z"}