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Zhang Z, Zhao W, Xiao J, Bao Y, Wang F, Hao L, Zhu J, Chen T, Zhang S, Chen X, Tang B, Zhou Q, Wang Z, Dong L, Wang Y, Ma Y, Wang F, Zhang Z, Wang Z, Chen M, Tian D, Li C, Dong L, Teng X, Tang B, Du Z, Yuan N, Zeng J, Zhang Z, Wang J, Shi S, Zhang Y, Wang Q, Pan M, Qian Q, Song S, Niu G, Li M, Xia L, Zou D, Zhang Y, Sang J, Li M, Zhang Y, Wang P, Wang F, Zhang Y, Gao Q, Xiao J, Hao L, Liang F, Li M, Zou D, Li R, Liu L, Cao J, Sang J, Zou D, Li M, Abbasi AA, Shireen H, Wang P, Zhang Y, Li Z, Wang Q, Xia L, Xiong Z, Jiang M, Guo T, Li Z, Zhang H, Pan M, Ma L, Li M, Niu G, Xia L, Zou D, Zhang Y, Sang J, Li Z, Gao R, Li R, Zhang T, Bao Y, Zhang Z, Tang B, Zhou Q, Dong L, Li W, Zhang X, Lan L, Zhai S, Bao Y, Zhang Y, Wang G, Zhao W, Sang J, Wang Z, Zou D, Zhang Y, Hao L, Bao Y, Zhang Z, Zhao W, Xiao J, Lan L, Xue Y, Sun Y, Yu L, Zhai S, Sun M, Chen H, Zhang Z, Zhao W, Xiao J, Bao Y, Song S, Hao L, Li R, Ma L, Wang Y, Tang B, Chen M, Hu H, Guo AY, Lin S, Xue Y, Wang C, Xue Y, Ning W, Xue Y, Zhang Y, Xue Y, Luo H, Gao F, Guo Y, Xue Y, Zhang Q, Guo AY, Zhou J, Xue Y, Huang Z, Cui Q, Miao YR, Guo AY, Ruan C, Xue Y, Yuan C, Chen M, Jinpu J, Gao G, Xu H, Xue Y, Li Y, Li CY, Tang Q, Guo AY, Peng D, Deng W. Database Resources of the BIG Data Center in 2019. Nucleic Acids Res 2019; 47:D8-D14. [PMID: 30365034 PMCID: PMC6323991 DOI: 10.1093/nar/gky993] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 10/08/2018] [Accepted: 10/10/2018] [Indexed: 01/23/2023] Open
Abstract
The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of multi-omics data generated at unprecedented scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. Resources with significant updates in the past year include BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Science Wikis (a catalog of biological knowledge wikis for community annotations) and IC4R (Information Commons for Rice). Newly released resources include EWAS Atlas (a knowledgebase of epigenome-wide association studies), iDog (an integrated omics data resource for dog) and RNA editing resources (for editome-disease associations and plant RNA editosome, respectively). To promote biodiversity and health big data sharing around the world, the Open Biodiversity and Health Big Data (BHBD) initiative is introduced. All of these resources are publicly accessible at http://bigd.big.ac.cn.
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Knowledge categorization affects popularity and quality of Wikipedia articles. PLoS One 2018; 13:e0190674. [PMID: 29293627 PMCID: PMC5749832 DOI: 10.1371/journal.pone.0190674] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 12/19/2017] [Indexed: 11/19/2022] Open
Abstract
The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia-an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system.
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Zhang Z, Sang J, Ma L, Wu G, Wu H, Huang D, Zou D, Liu S, Li A, Hao L, Tian M, Xu C, Wang X, Wu J, Xiao J, Dai L, Chen LL, Hu S, Yu J. RiceWiki: a wiki-based database for community curation of rice genes. Nucleic Acids Res 2013; 42:D1222-8. [PMID: 24136999 PMCID: PMC3964990 DOI: 10.1093/nar/gkt926] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Rice is the most important staple food for a large part of the world’s human population and also a key model organism for biological studies of crops as well as other related plants. Here we present RiceWiki (http://ricewiki.big.ac.cn), a wiki-based, publicly editable and open-content platform for community curation of rice genes. Most existing related biological databases are based on expert curation; with the exponentially exploding volume of rice knowledge and other relevant data, however, expert curation becomes increasingly laborious and time-consuming to keep knowledge up-to-date, accurate and comprehensive, struggling with the flood of data and requiring a large number of people getting involved in rice knowledge curation. Unlike extant relevant databases, RiceWiki features harnessing collective intelligence in community curation of rice genes, quantifying users' contributions in each curated gene and providing explicit authorship for each contributor in any given gene, with the aim to exploit the full potential of the scientific community for rice knowledge curation. Based on community curation, RiceWiki bears the potential to make it possible to build a rice encyclopedia by and for the scientific community that harnesses community intelligence for collaborative knowledge curation, covers all aspects of biological knowledge and keeps evolving with novel knowledge.
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Affiliation(s)
- Zhang Zhang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Fuyang, Zhejiang 311400, China, School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China and College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
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