Purpose： In the open science era, it is typical to share project-generated scientific data by depositing it in an open and accessible database. Moreover, scientific publications are preserved in a digital library arc...Purpose： In the open science era, it is typical to share project-generated scientific data by depositing it in an open and accessible database. Moreover, scientific publications are preserved in a digital library archive. It is challenging to identify the data usage that is mentioned in literature and associate it with its source. Here, we investigated the data usage of a government-funded cancer genomics project, The Cancer Genome Atlas（TCGA）, via a full-text literature analysis.Design/methodology/approach： We focused on identifying articles using the TCGA dataset and constructing linkages between the articles and the specific TCGA dataset. First, we collected 5,372 TCGA-related articles from Pub Med Central（PMC）. Second, we constructed a benchmark set with 25 full-text articles that truly used the TCGA data in their studies, and we summarized the key features of the benchmark set. Third, the key features were applied to the remaining PMC full-text articles that were collected from PMC.Findings： The amount of publications that use TCGA data has increased significantly since 2011, although the TCGA project was launched in 2005. Additionally, we found that the critical areas of focus in the studies that use the TCGA data were glioblastoma multiforme, lung cancer, and breast cancer; meanwhile, data from the RNA-sequencing（RNA-seq） platform is the most preferable for use.Research limitations： The current workflow to identify articles that truly used TCGA data is labor-intensive. An automatic method is expected to improve the performance.Practical implications： This study will help cancer genomics researchers determine the latest advancements in cancer molecular therapy, and it will promote data sharing and data-intensive scientific discovery.Originality/value： Few studies have been conducted to investigate data usage by governmentfunded projects/programs since their launch. In this preliminary study, we extracted articles that use TCGA data from PMC, and we created a link between the full-text articles and the source data.展开更多
Purpose: The aim of this study is to develop and implement a quality-control system to ensure authority control of the different knowledge units for the Scientific & Technological Knowledge Organization Systems(ST...Purpose: The aim of this study is to develop and implement a quality-control system to ensure authority control of the different knowledge units for the Scientific & Technological Knowledge Organization Systems(STKOS).Design/methodology/approach: First, we analyzed quality-control requirements based on the construction of the STKOS Metathesaurus. Then we designed a quality-control framework, the task management and transfer mechanism, and a service model. Afterwards, we carried out the experiments to check the rules and algorithms used in the system. Finally, the system was developed, and gradually optimized during its service.Findings: The quality-control system supports collaborative knowledge construction, as well as consistency checks of knowledge units with different granularity levels, including terminologies, relationships, and concepts. The system can be flexibly configured.Research limitations: The system is oriented to an English-language knowledge organization system, and may not perform well with Chinese-language systems and ontologies.Practical implications: The system can be used to support the construction of a single knowledge organization system, as well as data warehousing and interoperable knowledge organization systems. Originality/value: The STKOS quality-control system not only focuses on content building for the knowledge system, but also supports collaborative task management.展开更多
基金supported by the National Population and Health Scientific Data Sharing Program of Chinathe Knowledge Centre for Engineering Sciences and Technology (Medical Centre)the Fundamental Research Funds for the Central Universities (Grant No.: 13R0101)
文摘Purpose： In the open science era, it is typical to share project-generated scientific data by depositing it in an open and accessible database. Moreover, scientific publications are preserved in a digital library archive. It is challenging to identify the data usage that is mentioned in literature and associate it with its source. Here, we investigated the data usage of a government-funded cancer genomics project, The Cancer Genome Atlas（TCGA）, via a full-text literature analysis.Design/methodology/approach： We focused on identifying articles using the TCGA dataset and constructing linkages between the articles and the specific TCGA dataset. First, we collected 5,372 TCGA-related articles from Pub Med Central（PMC）. Second, we constructed a benchmark set with 25 full-text articles that truly used the TCGA data in their studies, and we summarized the key features of the benchmark set. Third, the key features were applied to the remaining PMC full-text articles that were collected from PMC.Findings： The amount of publications that use TCGA data has increased significantly since 2011, although the TCGA project was launched in 2005. Additionally, we found that the critical areas of focus in the studies that use the TCGA data were glioblastoma multiforme, lung cancer, and breast cancer; meanwhile, data from the RNA-sequencing（RNA-seq） platform is the most preferable for use.Research limitations： The current workflow to identify articles that truly used TCGA data is labor-intensive. An automatic method is expected to improve the performance.Practical implications： This study will help cancer genomics researchers determine the latest advancements in cancer molecular therapy, and it will promote data sharing and data-intensive scientific discovery.Originality/value： Few studies have been conducted to investigate data usage by governmentfunded projects/programs since their launch. In this preliminary study, we extracted articles that use TCGA data from PMC, and we created a link between the full-text articles and the source data.
基金supported by the Ministry of Science and Technology of China(Grant No.:2011BAH10B02)
文摘Purpose: The aim of this study is to develop and implement a quality-control system to ensure authority control of the different knowledge units for the Scientific & Technological Knowledge Organization Systems(STKOS).Design/methodology/approach: First, we analyzed quality-control requirements based on the construction of the STKOS Metathesaurus. Then we designed a quality-control framework, the task management and transfer mechanism, and a service model. Afterwards, we carried out the experiments to check the rules and algorithms used in the system. Finally, the system was developed, and gradually optimized during its service.Findings: The quality-control system supports collaborative knowledge construction, as well as consistency checks of knowledge units with different granularity levels, including terminologies, relationships, and concepts. The system can be flexibly configured.Research limitations: The system is oriented to an English-language knowledge organization system, and may not perform well with Chinese-language systems and ontologies.Practical implications: The system can be used to support the construction of a single knowledge organization system, as well as data warehousing and interoperable knowledge organization systems. Originality/value: The STKOS quality-control system not only focuses on content building for the knowledge system, but also supports collaborative task management.
