Research / Science / Development

Stefan Hornbostel
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引用次数: 0

Abstract

As in other societal realms also in research, science, and development governments and parliaments increasingly have to legitimize their actions and want to base their future activities on informed decisions. Consequently, performance measures, benchmarking, comparative analysis, “foresight studies” are increasingly asked for. Ranking, ratings and evaluations are introduced throughout the system supposedly providing on the one hand the requested transparency and at the same time acting as stimuli to improve the performance. However, to date central questions relating to the underlying methodologies and indicators used are unanswered. These questions concern the availability and appropriateness of the data, indicator construction and methodologies on the one hand, tackle issues as how to deal with effects due to disciplinary, sectoral, regional or national differences, and concern the intended and unintended effects of the instruments used. In the contribution these issues are described and discussed in more detail. In Germany so far infrastructural deficiencies e.g. the fragmentation of research groups addressing those issues prevent adequately addressing the open research questions. Behind this background the two most important tasks identified are them the development of a decentralized data collection system enabling standard definitions and the development of a competitive research infrastructure.
研究/科学/发展
正如在其他社会领域一样,在研究、科学和发展领域,政府和议会越来越需要使他们的行为合法化,并希望将他们未来的活动建立在知情的决策基础上。因此,越来越需要业绩衡量、基准、比较分析和“前瞻研究”。在整个系统中引入了排名、评级和评估,据说一方面提供了所要求的透明度,同时作为提高绩效的刺激。然而,迄今为止,与所使用的基本方法和指标有关的核心问题尚未得到解答。这些问题一方面涉及数据的可得性和适当性、指标结构和方法,处理如何处理由于学科、部门、区域或国家差异造成的影响等问题,并涉及所使用工具的预期和非预期影响。在贡献中,对这些问题进行了更详细的描述和讨论。在德国,到目前为止,基础设施的不足,如研究小组的分散,阻碍了对开放研究问题的充分解决。在此背景下,确定了两项最重要的任务:开发一个分散的数据收集系统,实现标准定义和开发具有竞争力的研究基础设施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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