目录|DIM第一期导览
Volume 1,Issue 1
由武汉大学信息管理学院、武汉大学信息资源研究中心主办，国际知名学术出版商德古意特(De Gruyter)出版的英文期刊Data and Information Manage-ment(DIM)旨在促进数据驱动下跨领域的信息管理研究。
主编：马费成、Gary Marchionini
执行主编：张晓娟
我们欣喜万分地欢迎读者们与第一期《数据与信息管理》（DIM）见面。新刊面世是一个研究社群生命中的重要时刻，正如呱呱落地的孩童之于家庭一般，此刊尚须广大读者的关注和鼓励。我们期待与全球的信息科学及相关社群合作，将DIM培育成数据与信息管理领域研究和实践的成熟工具。
您也许会问，现有期刊已琳琅满目，为何还要新添？因为，置身于两次“寒武纪大爆炸”般的创新洪流之中，多样性至关重要。首先，信息科学领域正在扩展，将数据生成、分析和管理技术应用于人类所有领域，特别是在构建跨学科的桥梁以解决复杂问题方面。重要的是，日益增长的全球数据和信息管理学者拥有了一席之地与发声平台。其次，学术思想与成果的分享奖励方式已变。DIM将提供一种可供选择、开放获取的出版模式，以促进学术分享与进步的最大化。
数据和信息管理是我们这个时代面临的重大挑战之一。数据无处不在，它容量大，速度快，变异性强，若加以适当管理则可迸发巨大的价值。然而，这是一个很大的假设。统计科学将开发新的方法来建模、聚合、总结和分析数据，计算机科学将开发新的算法来处理、存储、传输数据，并将统计进展应用到这些数据集上。作为信息科学家，我们要关注的不仅是数据和信息处理，还有相关的管理和社会问题:数据收集政策(如知情同意)、数据清理与确认(管理和错误记录、异常值和子集)、检索(如元数据本体、查询和结果呈现策略、用户行为)、保存(平衡每单位时间成本与风险因素策略，保存工作流程和数据)和使用(如隐私、安全、公平)。我们所关心的不仅仅是“大”数据，更在于“好”数据，以及数据如何体现信息又反过来推动人类知识进步。
欢迎诸位同仁向本刊投稿，我们深知审稿人责任是不可多得的资源，如果您愿意参与评议稿件，请联系我们。
让我们携手共建一个重视数据和信息管理及数字出版创新的社群，期待您的积极参与！
Editorial
Editors in Chief:
Feicheng Ma, Gary Marchionini,
Executive Editor-in-Chief:
Xiaojuan Zhang
Dear Readers:
It is our great pleasure to welcome readers to the first issue of the Data and Information Management (DIM). The launch of a new journal is a critical point in the life of a research community. Like the arrival of a new child into the family, a journal must be nurtured and encouraged. We look forward to working with the global information science and related community to grow this journal into a mature vehicle for data and information management research and practice.
We might ask, why more journals when so many already exist? We believe we are in the midst of two Cambrian explosions of innovation and maximizing variety is essential in such times. First, the field of information science is expanding to apply data generation, analysis, and management techniques to all areas of human endeavor, especially in ways that build bridges across disciplines to address complex problems. It is important that the growing global population of data and information management scholars have venues for their work and their voices. Second, we are seeing changes in the way that scholarly ideas and results are shared and rewarded. DIM will provide an alternative and open access model of publishing that will maximize scholarly sharing and progress.
Data and information management is one of the crucial challenges of our time. Data is everywhere and it is famously high volume, high velocity, high variability, and IF properly curated and managed, high VALUE. This is however, a big IF. Statistical sciences will develop new ways to model, aggregate, summarize, and analyze data and computer science will develop new algorithms to process, store, transmit data and apply the statistical advances to those data sets. As information scientists, it is up to us to focus on not only data and information processing but also the related management and social issues:policies for data collection (e.g., informed consent), data cleaning/assurance (policies for managing and documenting errors, outliers, and subsets), retrieval (e.g., metadata ontologies, query and result presentation strategies, user behaviors), preservation (policies for balancing cost per bit per unit time with risk factors, preserving work flows as well as data), and usage (e.g., privacy, security, fairness). We are most concerned with GOOD data rather than only BIG data, and how data manifests as information and in turn supports the advance of human knowledge.
We encourage you to send good papers to this journal and encourage your colleagues to do so. Please let us know if you are willing to review papers for the journal— we know that reviewer burden is a natural resource and we want to value it. We look forward to building a community that values the innovations in data and information management and in digital publishing and look forward to your active participation.
Sincerely!
Open Access：DIM免费向读者提供全文，并为作者提供全方位的增值服务和多元化的激励政策。除了享受高水准的同行评议、高品质的编辑加工、高集成的出版平台和高效率的网络传播，读者亦可免支付出版费，且稿件一经录用，由主办方支付稿酬。
另外，该刊将从首年发表的文章中评选六篇最优秀的论文，予以奖励。在线投稿系统：http://www.editorialmanager.com/dim/default.asp
01 DIM《数据与信息管理》
第一期目录
< Article 1 > The Contingency Effect of Relational Competency on the Relationship between Information Technology Competency and Firm PerformanceAuthors：Shaobo Wei,Kwok-Kee Wei
DOI: https://doi.org/10.1515/dim-2017-0003
（识别二维码直达原文）< Article 2 >Supporting Book Search: A Comprehensive Comparison of Tags vs. Controlled Vocabulary Metadata
Authors：Toine Bogers,Vivien Petras
DOI: https://doi.org/10.1515/dim-2017-0004
（识别二维码直达原文）
< Article 3 >
Data-driven Pattern Analysis of Acknowledgments in the Biomedical Domain
Authors：Juyoung An,Sieun Jeon,Teryn Jones,Min Song
DOI: https://doi.org/10.1515/dim-2017-0002
（识别二维码直达原文）
< Article 4 >Enhancing Clinical Decision Support Systems with Public Knowledge Bases
Authors：Danchen Zhang,Daqing He
DOI: https://doi.org/10.1515/dim-2017-0005
（识别二维码直达原文）
< Article 5 >A Three-way Interaction Model of Information Withholding: Investigating the Role of Information Sensitivity, Prevention Focus, and Interdependent Self-Construal
Authors：Yongqiang Sun,Dina Liu,Nan Wang
DOI: https://doi.org/10.1515/dim-2017-0007
（识别二维码直达原文）
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