Identifying Scientific Project-generated Data Citation from Full-text Articles： An Investigation of TCGA Data Citation

• 作者: Hongyu Kang Jiao Li Qing Qian Si Zheng Zhen Hou
• 来源期刊: 数据与情报科学学报：英文版
• 学科: 社会科学
• 关键词: 科学的数据 全文广告 开启出入口 PUBMED 中心的 数据传唤
• 年，卷（期）: 2016,（2）
• 页码范围: 32-44
• 页数: 13页
• 分类号: G35

摘要

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 sourc