多学科融合对我国情报学教育的影响

当前,情报学在研究内容和研究方法上不断向多学科融合方向迈进。多学科融合对我国的情报学教育产生了广泛而深远的影响。情报学教育工作者在新的环境面前,既要重视维护情报学的学科地位,也要重视推进教育模式的创新、加强教育资源的合理配置。     

基于数据库联邦方式的多数据源集成检索系统

介绍了多数据源集成检索系统的产生背景和实现方式，分析了基于数据库联邦方式的多数据源集成检索系统的体系框架和异构问题，对国外的基于数据库联邦方式的多数据源集成检索系统进行了介绍和比较分析。     

知识管理与图书馆学、情报学专业教育

随着知识社会的到来，图书馆学、情报学的研究呈现出知识化趋向，以知识为中心的图书馆学情报学学科体系正在形成．图书馆学情报学专业教育也将围绕知识和知识管理进行整合与调整。     

我国情报学学科发展的创新机制及创新领域研究

创新是一个学科良性发展的必然要求。本文主要对情报学学科发展的创新要求和创新任务,创新的动力机制和模型,以及在创新动力作用下的创新领域等方面进行研究     

Modellierung und kartographische Visualisierung von Geodaten mit XML-basierten Sprachen

Zusammenfassung Mit den XML-basierten Sprachen GML, XSLT und SVG lassen sich Geodaten nicht nur anwendungsorientiert modellieren, sondern auch karten?hnlich visualisieren. In dieser Fallstudie zeigen wir das, indem wir realistische Geodatenbest?nde der Landesvermessungs?mter zun?chst mit der Geography Markup Language (GML) nachmodellieren. So mit GML strukturierte Daten werden dann mit der Extensible Stylesheet Language for Transformation (XSLT) auf Elemente der Sprache Scalable Vector Graphics (SVG) abgebildet. Dabei wird der Prozess der kartografischen Visualisierung durch XSLT-Konstrukte modelliert und auch gleichzeitig implementiert. Als Ergebnis erhalten wir Grafiken, die den entsprechenden Karten der Landes?mter zumindest nicht un?hnlich sind.

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Using the XML-based languages GML, XSLT and SVG, we modeled German geo data and also visualized it in map-like graphics. This case study shows the feasibility of that approach, by modelling the data with the Geography Markup Language (GML). Then, the GML-structured data is mapped with the Extensible Stylesheet Language for Transformation (XSLT) to elements of the language Scalable Vector Graphics (SVG). The process of cartographical visualization is thus modelled through XSLT-constructs and at same time also implemented. The results are graphics, which share close ressemblance to the corresponding maps of the official offices.

CR Subject Classification I.3.3,I.3.5,I.6.5,I.7.2,J.2     

Enhancing Research Impact in Heritage Conservation

This paper examines how research impact is defined, measured, and generated – with a view to understanding how it can be enhanced within heritage conservation. It examines what is meant by ‘impact’ and how it can be promoted within heritage science through effective inter-disciplinary collaboration. Following a general examination of the current discourse concerning research impact, the study examined: (i) active research networks within heritage science; (ii) research planning and evaluation practices within heritage science; and (iii) the experiences of users (i.e. conservators and other heritage professionals) within research collaborations. Terminologies surrounding the notion of impact and the various phases of the research process were reviewed – from the initial identification of a knowledge gap to the eventual application of new findings in practice. Next, the reach and diversity of research collaborations (as identified through publication co-authorship) were studied to characterise the inter-disciplinary nature of heritage science and its connectedness to users. Findings showed substantial growth in international research collaborations over recent years, predominantly involving academic- and research-oriented institutions – although the engagement of heritage institutions has proportionally decreased. In addition, a worldwide survey of institutional planning and evaluation practices revealed a general reliance on processes driven by the interests of researchers – the systematic consideration of stakeholder opinion and evaluation of research outcomes being less common. Finally, a series of semi-structured interviews with senior heritage professionals explored their experience of collaborative research. The results identified key areas where strategic support is needed to promote user participation and enhance impact. These include training for research readiness, engagement, and impact for both researchers and users; better methods for needs and outcome assessment; affordable open access options and greater diversity of knowledge exchange opportunities. Finally, the need for ethical guidelines for responsible research, and greater emphasis on non-academic impact within research rating systems are discussed.     

科研领域重点研究方向判别方法研究

[目的/意义] 判别重点研究方向对科研管理和科技政策的制定有着重要参考价值,已有的定量方法多是根据创新性、新颖性以及增长性等特征属性设计指标进行识别、推荐,本研究进一步利用研究方向间的关联关系,从网络拓扑结构和特征属性两个维度判别重点研究方向。[方法/过程] 在构建领域文献引用网络的基础上,利用大规模网络聚类算法识别研究方向,并构建研究方向关联网络,利用网络重要节点识别算法从网络拓扑结构的角度判别重点研究方向,同时结合新颖性、增长性和H指数三个特征属性指标,构建了重点研究方向遴选指标体系。[结果/结论] 对纳米科技领域进行实证分析,经专家判读,认为加权PageRank、Gefura以及增长性指标更加具有客观性、全面性和稳定性,通过综合运用三个指标遴选出208个纳米科技领域的重点研究方向。     

我国促进大数据发展政策工具选择体系结构及其优化策略研究

[目的/意义]探究我国为实现促进大数据发展的政策目标而构建的政策工具选择体系结构,揭示大数据政策工具选择中存在的问题,为优化我国促进大数据发展政策工具选择提供建议。[方法/过程]构建由63项聚焦大数据发展的政策文本构成的政策样本集,运用内容分析法,对样本集中包含的政策工具进行编码。建立包含基础资源维度、技术维度和领域维度的政策工具选择三维分析框架,通过编码映射,建立其与政策工具编码的关联。从领域维度,使用层次聚类分析法,对样本政策文本进行聚类分析。[结果/结论]政策工具编码分析结果显示,我国大数据政策工具选择中存在缺乏长期规划,政策及政策工具协同不足,政策工具选择欠丰富;政策工具选择结构失衡;需求表达模糊,难以定位关键政策及政策工具等问题。应加强战略规划和发展理念指引,重视政策及政策工具协同,规避公共风险,构建需求驱动和问题导向的政策工具选择体系结构,创新设计与应用关键政策工具。     

UNIMARC Format Relevance: Maintenance or Replacement?

This article presents an empirical study focused on a qualitative analysis of the UNIMARC format. An analysis of the structural quality of the data provided by the format is evaluated to determine its current suitability for meeting the requirements and trends in data architecture for the information network and the Semantic Web. Driven by a set of quality characteristics that identify weaknesses in the data schema that cannot be bridged by simply converting data to MARC XML or RDF/XML, we conclude that the UNIMARC format is not compliant with the current metadata schema desiderata and must be replaced.