{"doi":"10.12688/f1000research.110355.1","title":"Implementation and assessment of an end-to-end Open Science &amp; Data Collaborations program","abstract":"<ns4:p>As research becomes more interdisciplinary, fast-paced, data-intensive, and collaborative, there is an increasing need to share data and other research products in accordance with Open Science principles. In response to this need, we created an Open Science &amp; Data Collaborations (OSDC) program at the Carnegie Mellon University Libraries that provides Open Science tools, training, collaboration opportunities, and community-building events to support Open Research and Open Science adoption. This program presents a unique end-to-end model for Open Science programs because it extends open science support beyond open repositories and open access publishing to the entire research lifecycle. We developed a logic model and a preliminary assessment metrics framework to evaluate the impact of the program activities based on existing data collected through event and workshop registrations and platform usage. The combination of these evaluation instruments has provided initial insight into our service productivity and impact. It will further help to answer more in-depth questions regarding the program impact, launch targeted surveys, and identify priority service areas and interesting Open Science projects.</ns4:p>","journal":"F1000Research","year":2022,"id":47176,"datarank":0.23898751230246396,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.031043358134480323,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.031043358134480323,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":3,"citers_with_citation_signal":2,"citers_with_endowment":2,"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":217741,"name":"Melanie Gainey","orcid":"0000-0002-4782-9647","position":1,"is_corresponding":false},{"id":217742,"name":"Patrick Campbell","orcid":null,"position":2,"is_corresponding":false},{"id":217743,"name":"Sarah Young","orcid":"0000-0002-8301-5106","position":3,"is_corresponding":false},{"id":217744,"name":"Katie Behrman","orcid":"0000-0002-9351-0354","position":4,"is_corresponding":false},{"id":217740,"name":"Huajin Wang","orcid":"0000-0003-0121-4257","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Implementation and assessment of an end-to-end Open Science &amp; Data Collaborations program","abstract":"<ns4:p>As research becomes more interdisciplinary, fast-paced, data-intensive, and collaborative, there is an increasing need to share data and other research products in accordance with Open Science principles. In response to this need, we created an Open Science &amp; Data Collaborations (OSDC) program at the Carnegie Mellon University Libraries that provides Open Science tools, training, collaboration opportunities, and community-building events to support Open Research and Open Science adoption. This program presents a unique end-to-end model for Open Science programs because it extends open science support beyond open repositories and open access publishing to the entire research lifecycle. We developed a logic model and a preliminary assessment metrics framework to evaluate the impact of the program activities based on existing data collected through event and workshop registrations and platform usage. The combination of these evaluation instruments has provided initial insight into our service productivity and impact. It will further help to answer more in-depth questions regarding the program impact, launch targeted surveys, and identify priority service areas and interesting Open Science projects.</ns4: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":"36545378","pmcid":null,"openalex_id":"https://openalex.org/W4229077818","authors":[],"funders":[{"funder_name":"Office of Advanced Cyberinfrastructure","grant_id":"1839014","title":"Challenges and Opportunities in Scientific Data Discovery and Reuse in the Data Revolution: Harnessing the Power of AI"}],"total_grants":1,"fwci":0.934,"citation_percentile":0.79362803,"influential_citations":0,"citation_trend":[{"year":2024,"count":1},{"year":2025,"count":2}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://f1000research.com/articles/11-501/v1/pdf","host_type":"journal"},{"url":"https://f1000research.com/articles/11-501/v1/pdf","host_type":"publisher"},{"url":"https://f1000research.com/articles/11-501/v1/xml","host_type":"publisher"},{"url":"https://f1000research.com/articles/11-501/v1/iparadigms","host_type":"publisher"},{"url":"https://doi.org/10.12688/f1000research.110355.1","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/36545378","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9748376","host_type":"repository"},{"url":"https://doi.org/10.12688/f1000research.110355.2","host_type":""},{"url":"http://dx.doi.org/10.12688/f1000research.110355.2","host_type":""}],"fields_of_study":["Research Data Management Practices","Scientific Computing and Data Management","scientometrics and bibliometrics research","05 social sciences","0509 other social sciences"],"mesh_terms":["Humans","Universities","Benchmarking","Open Access Publishing"],"keywords":["Open science","Open data","Service (business)","Computer science","Data science","Open research","Productivity","Publishing","Open peer review","Engineering management","e-Science","Knowledge management","Open source","World Wide Web","Engineering","Business","Plant biology","Political science","Software","Benchmarking","Case Study","Universities","Open Access Publishing","Humans"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Industry, innovation and infrastructure"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-17T12:44:01.943490Z","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":[]}