GetPortalImpactFactorByIdResp(projectId=1, id=1d5b18853, cover=, fullname=Data, abbr=DATA, pyear=暂无数据, frequence=null, articleNumbers=699, citedSelf2015=null, acceptanceRate=null, submissionToAcceptance=null, averageReviewTime=暂无数据, reviewFee=null, pageFee=null, publishedRatio=2023年中国人文章占该期刊总数量暂无数据 (2022年为100.00%), issn=2306-5729, greenSci=https://www.greensci.net/search?kw=2306-5729, scijournal=https://www.scijournal.org/impact-factor-of-DATA.shtml, medsciHotlightString=null, medsciHotlightRealtime=0.389, medsciHotlight=0.095, medsciHotlight5year=0.0, citescore=3.5, hIndex=18, impactFactor=2.6, orgnization=MDPI AG, orgnizationUrl=https://www.mdpi.com, country=Switzerland, countryCn=瑞典, isOa=1, isOaString=是, sciScie=null, bigclassCas=null, smallclassCas=, website=https://www.mdpi.com/journal/data, websiteHits=100, guideForAuthor=https://www.mdpi.com/journal/data/instructions, guideForAuthorHits=62, submitWebsite=https://susy.mdpi.com/user/manuscripts/upload?form[journal_id]=176, submitWebsiteHits=97, content=<p style="color: #222222;"><img class="img-fixed" src="https://img.medsci.cn/images/20221009/4e62a10e8052486dbde82d901e7ddb97.jpg" alt="Dataset_Papers_Overview" width="600" /></p> <h2 style="color: #1a1a1a;">Rationale for <em>Data</em></h2> <p style="color: #222222;">One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data are of paramount importance to scientific progress, yet most research data remain private. Enhancing the transparency of the processes applied to collect, treat and analyze data will help to render scientific research results reproducible and thus more accountable. The datasets themselves should also be accessible to other researchers, so that research publications, dataset descriptions, and the actual datasets can be linked. The journal Data provides a forum to publish methodical papers on processes applied to data collection, treatment and analysis, as well as for data descriptors publishing descriptions of a linked dataset.</p> <h2 style="color: #1a1a1a;">Aims</h2> <p style="color: #222222;"><em>Data </em>(ISSN 2306-5729) is a unique international, scientific open access journal on ʻdata in scienceʼ. It provides a forum for data scientists as well as for scientists working with data. The journal publishes two sections:</p> <blockquote style="color: #222222;"><strong>Methods</strong>: the <em>Methods</em> section publishes research articles, review papers and technical notes on methods for collecting, processing (treating), managing, storing and analyzing scientific and scholarly data. Related source code, if available, can be deposited as supplementary material.</blockquote> <blockquote style="color: #222222;"><strong>Data Descriptors</strong>: the <em>Data Descriptors</em> section publishes descriptions of scientific and scholarly datasets (one dataset per paper). Described datasets need to be publicly deposited prior to publication, preferably under an open license, thus allowing others to re-use the dataset. Small datasets might also be published as supplementary material to the dataset paper in the journal Data. The link to the publicly hosted version of the dataset must be given in the paper. Data descriptors therefore provide easy citability, traceability and accountability of datasets used in scientific research. Research articles published elsewhere based on the data can link back to the data descriptors via a standard reference and DOI number. Data descriptors are published under a CC BY license, thus allowing the reuse of the descriptions in other research papers without copyright infringement.</blockquote> <h2 style="color: #1a1a1a;">Subject Areas</h2> <p style="color: #222222;">Datasets and descriptions:</p> <ul style="color: #222222;"> <li>description of data and the methodologies used in the collection and treating of scholarly or scientific research data and experimental data</li> </ul> <p style="color: #222222;">Data in applications:</p> <ul style="color: #222222;"> <li>data in natural sciences</li> <li>data in healthcare and medicine</li> <li>data in finance, business and economics</li> <li>research data, experimental data</li> </ul> <p style="color: #222222;">Data-related processes:</p> <ul style="color: #222222;"> <li>data collection and data acquisition</li> <li>data processing</li> <li>data analysis</li> <li>data maintenance and data integrity</li> <li>data curation</li> <li>data management systems</li> <li>data compression</li> </ul>, totalCites=1818, brief=DATA杂志暂不明确行业，暂不明确子行业的级别不明杂志, articleType=本刊接收类型不明, medsciHeat=<span style="color: #000000;">黑</span>, medsciComment=杂志水平一般，也很冷门，关注人少，审稿周期可能也不一定快，如果文章质量不佳，或时间不紧的话，可以考虑考虑。, medsciExplanation=MedSci期刊指数是根据中国科研工作者（含医学临床，基础，生物，化学等学科）对SCI杂志的认知度，熟悉程度，以及投稿的量等众多指标综合评定而成。当然，具体的，您还可以结合“<a href='https://www.medsci.cn/sci/submit.do?id=1d5b18853'>投稿经验系统</a>”，进行综合判断，这更是大家的实战经验，值得分享和参考。<br> 注意，上述MedSci期刊指数采用MedSci专利技术，由计算机系统自动计算，并给出建议，存在不准确的可能，仅供您投稿选择杂志时参考。, tags=null, citeScoreList=null, medsciIndexList=[GetImpactFactorMedsciIndexListResponse(year=2022, medsciHotlight=0.133), GetImpactFactorMedsciIndexListResponse(year=2023, medsciHotlight=0.287), GetImpactFactorMedsciIndexListResponse(year=2024, medsciHotlight=0.389)], citeScoreGradeList=[], totalJcrAreaList=[], pmcUrl=https://www.ncbi.nlm.nih.gov/nlmcatalog?term=2306-5729[ISSN], pubmedUrl=https://www.ncbi.nlm.nih.gov/pubmed?cmd=search&term=Data[ta], article_number=181, article_number_cn=3, earlyWarning=null, linkOutUrl=null, isJournalMember=false, unscrambleContent=null, dayViewCount=false, endexampletyle=暂无数据)