{"doi":"10.1007/s42979-022-01444-y","title":"SciModeler: A Toolbox for Consolidating Scientific Knowledge within the Field of Health Behavior Change","abstract":"<jats:title>Abstract</jats:title><jats:p>Science aims to build and advance general theories from empirical data. This process is complicated by the immense volume of empirical data and scientific theories in some domains, for example in the field of health behavior change. Especially, a systematic mapping between empirical data and theoretical constructs is lacking. We propose a toolbox to establish that mapping. We adopted a modeling approach based on literature surveys to elicit requirements and to derive a metamodel. We adopted a graph-based database system to implement the metamodel, and designed a web-based tool for importing data from annotated text documents. To evaluate that toolbox (named <jats:italic>SciModeler</jats:italic>), we have conducted a case study within the field of health behavior change to record three scientific theories, three empirical studies, and the mapping in-between. We have documented how <jats:italic>SciModeler</jats:italic> aids closing gaps between empirical data and theoretical constructs. We have demonstrated that this enables new types of analyses by sharing example queries for (1) refining scientific theories, (2) exploring promising intervention strategies for a specific context, and (3) checking the potential impact of an intervention platform in a specific context. Our supplementary materials promote replication of these results. <jats:italic>SciModeler</jats:italic> can support the consolidation of scientific knowledge in the field of health behavior change, and we suggest that it may be applied within other fields, as well. An important direction for future work is promoting online collaboration on <jats:italic>SciModeler</jats:italic> graphs.</jats:p>","journal":"SN Computer Science","year":2022,"id":625314,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1616977,"name":"Pieter Van Gorp","orcid":null,"position":1,"is_corresponding":false},{"id":1616976,"name":"Raoul Nuijten","orcid":"0000-0003-0125-7708","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"SciModeler: A Toolbox for Consolidating Scientific Knowledge within the Field of Health Behavior Change","abstract":"<jats:title>Abstract</jats:title><jats:p>Science aims to build and advance general theories from empirical data. This process is complicated by the immense volume of empirical data and scientific theories in some domains, for example in the field of health behavior change. Especially, a systematic mapping between empirical data and theoretical constructs is lacking. We propose a toolbox to establish that mapping. We adopted a modeling approach based on literature surveys to elicit requirements and to derive a metamodel. We adopted a graph-based database system to implement the metamodel, and designed a web-based tool for importing data from annotated text documents. To evaluate that toolbox (named <jats:italic>SciModeler</jats:italic>), we have conducted a case study within the field of health behavior change to record three scientific theories, three empirical studies, and the mapping in-between. We have documented how <jats:italic>SciModeler</jats:italic> aids closing gaps between empirical data and theoretical constructs. We have demonstrated that this enables new types of analyses by sharing example queries for (1) refining scientific theories, (2) exploring promising intervention strategies for a specific context, and (3) checking the potential impact of an intervention platform in a specific context. Our supplementary materials promote replication of these results. <jats:italic>SciModeler</jats:italic> can support the consolidation of scientific knowledge in the field of health behavior change, and we suggest that it may be applied within other fields, as well. An important direction for future work is promoting online collaboration on <jats:italic>SciModeler</jats:italic> graphs.</jats:p>","is_dataset_classified":null,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W4308792291","authors":[],"funders":[{"funder_name":"ZonMw","grant_id":"443001101","title":null}],"total_grants":1,"fwci":0.3963,"citation_percentile":0.60106707,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":2}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://link.springer.com/content/pdf/10.1007/s42979-022-01444-y.pdf","host_type":"journal"},{"url":"https://link.springer.com/content/pdf/10.1007/s42979-022-01444-y.pdf","host_type":"publisher"},{"url":"https://link.springer.com/article/10.1007/s42979-022-01444-y/fulltext.html","host_type":"publisher"},{"url":"https://doi.org/10.1007/s42979-022-01444-y","host_type":"journal"},{"url":"https://research.tue.nl/en/publications/f0007b46-f559-4aad-bab9-8ca8c69f7b82","host_type":"repository"},{"url":"https://research.tue.nl/files/231597982/s42979_022_01444_y.pdf","host_type":"repository"},{"url":"https://research.tue.nl/nl/publications/f0007b46-f559-4aad-bab9-8ca8c69f7b82","host_type":"repository"},{"url":"https://pure.tue.nl/ws/files/231597982/s42979_022_01444_y.pdf","host_type":"repository"}],"fields_of_study":["Digital Mental Health Interventions","Mobile Health and mHealth Applications","Behavioral Health and Interventions"],"mesh_terms":[],"keywords":["Toolbox","Computer science","Metamodeling","Data science","Field (mathematics)","Empirical research","Context (archaeology)","Knowledge management","Management science","Software engineering","Engineering"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Partnerships for the goals"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-04T06:25:37.854367Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}