{"title":"对 MINERVA 进行 FAIR 评估,以此为契机促进系统生物医学领域的开放科学和科学众包","authors":"Irina Balaur, Danielle Welter, Adrien Rougny, Esther Thea Inau, Alexander Mazein, Soumyabrata Ghosh, Reinhard Schneider, Dagmar Waltemath, Marek Ostaszewski, Venkata Satagopam","doi":"10.1101/2024.08.28.610042","DOIUrl":null,"url":null,"abstract":"The Disease Maps Project (https://disease-maps.org) focuses on the development of disease-specific comprehensive structured knowledge repositories supporting translational medicine research. These disease maps require continuous interdisciplinary collaboration, and they should be reusable and interoperable. Adhering to the Findable, Accessible, Interoperable and Reusable (FAIR) principles enhances the utility of such digital assets. We used the RDA FAIR Data Maturity Model and assessed the FAIRness of the Molecular Interaction NEtwoRk VisuAlization (MINERVA) Platform. MINERVA is a standalone webserver that allows users to manage, explore and analyze disease maps and their related data manually or programmatically. We exemplify the FAIR assessment on the Parkinson's Disease Map (PD map) and the COVID-19 Disease Map, which are large-scale projects under the umbrella of the Disease Maps Project, aiming to investigate molecular mechanisms of the Parkinson's disease and SARS-CoV-2 infection, respectively. We discuss the FAIR features supported by the MINERVA Platform and we outline steps to further improve the MINERVA FAIRness and to better connect this resource to other ongoing scientific initiatives supporting FAIR in computational systems biomedicine.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"21 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FAIR assessment of MINERVA as an opportunity to foster open science and scientific crowdsourcing in systems biomedicine\",\"authors\":\"Irina Balaur, Danielle Welter, Adrien Rougny, Esther Thea Inau, Alexander Mazein, Soumyabrata Ghosh, Reinhard Schneider, Dagmar Waltemath, Marek Ostaszewski, Venkata Satagopam\",\"doi\":\"10.1101/2024.08.28.610042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Disease Maps Project (https://disease-maps.org) focuses on the development of disease-specific comprehensive structured knowledge repositories supporting translational medicine research. These disease maps require continuous interdisciplinary collaboration, and they should be reusable and interoperable. Adhering to the Findable, Accessible, Interoperable and Reusable (FAIR) principles enhances the utility of such digital assets. We used the RDA FAIR Data Maturity Model and assessed the FAIRness of the Molecular Interaction NEtwoRk VisuAlization (MINERVA) Platform. MINERVA is a standalone webserver that allows users to manage, explore and analyze disease maps and their related data manually or programmatically. We exemplify the FAIR assessment on the Parkinson's Disease Map (PD map) and the COVID-19 Disease Map, which are large-scale projects under the umbrella of the Disease Maps Project, aiming to investigate molecular mechanisms of the Parkinson's disease and SARS-CoV-2 infection, respectively. We discuss the FAIR features supported by the MINERVA Platform and we outline steps to further improve the MINERVA FAIRness and to better connect this resource to other ongoing scientific initiatives supporting FAIR in computational systems biomedicine.\",\"PeriodicalId\":501213,\"journal\":{\"name\":\"bioRxiv - Systems Biology\",\"volume\":\"21 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"bioRxiv - Systems Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.08.28.610042\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.28.610042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FAIR assessment of MINERVA as an opportunity to foster open science and scientific crowdsourcing in systems biomedicine
The Disease Maps Project (https://disease-maps.org) focuses on the development of disease-specific comprehensive structured knowledge repositories supporting translational medicine research. These disease maps require continuous interdisciplinary collaboration, and they should be reusable and interoperable. Adhering to the Findable, Accessible, Interoperable and Reusable (FAIR) principles enhances the utility of such digital assets. We used the RDA FAIR Data Maturity Model and assessed the FAIRness of the Molecular Interaction NEtwoRk VisuAlization (MINERVA) Platform. MINERVA is a standalone webserver that allows users to manage, explore and analyze disease maps and their related data manually or programmatically. We exemplify the FAIR assessment on the Parkinson's Disease Map (PD map) and the COVID-19 Disease Map, which are large-scale projects under the umbrella of the Disease Maps Project, aiming to investigate molecular mechanisms of the Parkinson's disease and SARS-CoV-2 infection, respectively. We discuss the FAIR features supported by the MINERVA Platform and we outline steps to further improve the MINERVA FAIRness and to better connect this resource to other ongoing scientific initiatives supporting FAIR in computational systems biomedicine.