Spatial Discovery of Linked Research Datasets and Documents at a Spatially Enabled Research Library

Current publishing practices in academia tend to result in datasets that are difficult to discover. This is because datasets are not well-integrated across academic domains and they are often not linked to the documents that reference them. For these reasons, discovering datasets across domains can be challenging; for example, discovering archeological observations and biological specimens using the same search is not widely supported, even if both datasets share a similar spatial extent, like Mesoamerica. It is also challenging to retrieve relevant documents that reference datasets; for example, retrieving a series of field reports that reference archeological observations is typically not supported. Our work develops an extensible method for: (1) geographically integrating collections across disciplinary repositories and (2) connecting datasets to related documents. We describe a collection of spatially-referenced researcher datasets, capturing their metadata elements and encoding them as linked open data. We then leverage existing library services to formalize links from datasets to documents. The system described in this work has been deployed, resulting in an experimental open data site for the UCSB campus. Results indicate that this system can be scaled-up with support from an institutional repository in the near future.     

An impulse to exploit: the behavioral turn in data-driven marketing

Industry advocates argue that by tailoring services and commercial solicitations to match media users’ personal interests, data-driven marketing benefits both consumers and businesses. This article shows, however, that advertisers and marketers who are taking up ideas and techniques from behavioral economics tell their clients a very different story about the aims and use of digital marketing and consumer surveillance. Listening in on this discourse demonstrates that some digital marketers conceptualize their own practices as forms of social control, appropriating concepts from behavioral economics to identify consumers’ cognitive and affective biases and target their vulnerabilities. Behavioral economics recognizes that economic decisions are not simply dictated by rational self-interest; rather, such choices depend on cognitive heuristics and habits, and can be manipulated through the design of “choice architecture.” This article discusses implications of the behavioral turn in data-driven marketing for critical advertising scholars, public advocates, and regulators.     

The more multidisciplinary the better? – The prevalence and interdisciplinarity of research collaborations in multidisciplinary institutions

Scientific research is increasingly relying on collaborations to address complex real-world problems. Many researchers, policymakers, and administrators consider a multidisciplinary environment an important factor for fostering research collaborations, especially interdisciplinary ones that involve researchers from different disciplines. However, it remains unknown whether a higher level of multidisciplinarity within an academic institution is associated with internal collaborations that are more prevalent and more interdisciplinary. Analyzing 90,000 publications by 2500 faculty members in over 100 academic institutions from three multidisciplinary areas, information, public policy, and neuroscience, we investigated the connection between multidisciplinarity and research collaborations. Based on social network analysis and text mining, our analysis suggests that more multidisciplinary institutions are not necessarily more collaborative, although they do feature collaborations that are more interdisciplinary. Our findings provide implications for academic administrators and policymakers to promote research collaborations and interdisciplinarity in academic institutions.     

基于多源数据的中国UNESCO名录遗产地可持续发展目标监测

SDG11.4.1将保护世界遗产的“保护支出”作为评价遗产可持续发展目标的指标,其处于有方法无数据的状态,亟需具体数据和测算案例支持。利用48处中国UNESCO名录遗产的统计数据对SDG11.4.1指标进行测度和分析,基于Landsat遥感数据对4处自然遗产人为干预度进行变化监测分析。结果表明：1)单位面积支出可作为测度自然保护地(世界自然遗产、混合遗产、地质公园和生物圈保护区)可持续发展状态的指标,但不适用于文化遗产的测度。2)从资金投入角度看：自然保护地年均投入400万元/km²可作为优质发展目标阈值,年均投入80万～400万元/km²可作为发展状态良好的阈值。3)人为干预度作为扩展指标可以反映自然遗产地的可持续保护状态和趋势,可进一步在中国及其他国家类似保护地进行推广应用。     

“健康中国2030”战略下健康数据协同治理体系研究

[目的/意义] 提升公民健康水平是经济社会发展到一定程度后的必然要求，健康数据协同治理体系的构建有助于从信息科学角度达成这一要求，治理体系需要以国家战略为宏观指导，全方位服务于公民健康水平提升的总体目标。[方法/过程] 通过对《"健康中国2030"规划纲要》文本精神的领会，在分析了各治理主体对健康信息治理需求的基础上，提出一种面向"健康中国2030"战略的健康数据协同治理体系，并针对关键环节提出保障措施。[结果/结论] 协调各层级、各部门与各利益主体的健康数据治理体系构建与保障，有助于在推动国家健康战略目标的同时实现健康数据的社会价值，拓展健康信息学的研究范畴。     

数据质量管理对数据共享的影响

数据质量对数据共享是个“双刃剑”：对数据质量要求太低,谬误散布可能误导用户;对数据质量要求 太高,数据生产者会因不堪重负对数据共享敬而远之。因此,探索一个数据生产者和数据用户都能接受的数据质量管 理机制对可持续的数据共享极为重要。文章用两个案例讨论了科研数据和政府业务数据质量管理方式对数据共享的影 响,并用第三个案例讨论了把科研数据转化为业务数据需要注意的原则：生产者和用户应该在关键问题上事先达成一 致意见,特别是,对数据质量验证需要遵循客观标准而非主观感觉。     

新一代学术交流生态系统的研究与构建——以北京大学为例

[目的/意义] 通过学术交流生态系统的研究与北京大学学术交流生态系统的初步构建,为高校与科研机构建设学术交流生态系统,推动学术交流和开放获取服务提供研究与实践参考经验。[方法/过程] 梳理学术交流概念、模式、功能与国内外研究发展情况,分析学术交流环境变化,指出开放获取、数据驱动研究范式、软件工具发展、社交媒体、教育教学新变革等因素驱动学术交流生态系统重构。介绍北京大学新一代学术交流生态系统的研究成果、架构设计、构建经验与服务效果,总结机构知识库、研究数据服务、开放出版、学者主页与研究支持服务等建设经验与效果。[结果/结论] 研究提出新一代学术交流生态系统,是以开放学术交流为目标,以学术资源数据汇集为基础,覆盖完整学术交流生命周期,提供研究准备、学术发现、研究与分析、写作、发布、传播与评价等学术交流全流程服务,并利用文献计量、数据挖掘、机器学习等新技术,为教学、科研、科研管理、学科评估等提供支持。总结研究成果和经验,为高校与科研机构建设学术交流生态系统提供有价值的研究与建设参考经验。推动学术交流发展,促进研究创新。     

多数据源协同下的专利分析系统构建

采用C/S架构,以C#+Sql Server组合设计构建了由专利数据监测、数据清洗、数据加工和数据挖掘等4个功能模块组构成的多数据源协同下的专利分析系统;详细阐述该系统架构、协同机制和主要功能;认为该系统能有效实现对中国、美国、欧洲、世界知识产权组织等国家或组织专利著录信息、法律状态信息、同族专利信息以及专利引文信息的智能化监测、采集、清洗、筛选、分类、标引、查询、统计、文本挖掘、信息可视化和自动生成报告等功能。     

企业竞争弱信号的特征提取与定量识别研究

[目的/意义] 针对当前对企业弱信号定量研究不足的现状,通过层次分析和隶属度函数构建新方法对其进行定量识别,为企业战略决策管理和危机预警提供服务。[方法/过程] 首先,基于波特的五力模型构建七力模型,结合实证分析提取企业竞争弱信号的特征;其次,结合层次分析法构建影响因素指标体系,并计算各指标的具体权重;最后,结合隶属度函数对弱信号进行定量识别。[结果/结论] 通过层次分析法和隶属度函数,构建了企业竞争弱信号的定量识别方法,为企业战略决策管理和危机管理提供服务。