在研究,科学和创新投资

影响变化

这是一系列的票据,以支持我们的政策立场的一个总结在RSS数据宣言,并于3月2018年,讨论我们所提倡的政策进行了更新,请与政策团队 policy@rss.org.uk

摘要

“政府应承诺在研究和创新方面的投资增加,以保持与其他领先的科学国家的步伐。这应该由10年的框架科学和创新的陪伴“。

502 Bad Gateway

We see statistics as a vanguard of valid science, which underpins the future performance of science and research. We therefore recommend that training and approaches to research conduct are strengthened so that they cut across disciplinary divides. Commissioners and funders should also seek to strengthen the application and innovation of statistical science, by opening up, as best they can, underlying data and methods, while cautiously dealing with issues such as data sensitivity. Strong collaborative infrastructure should be formed by UK Research and Innovation and the 研究 评议会s, to engage a wider range of businesses, NGOs and public bodies in statistical R&D.


nginx

在科学和研究方面的投资

“英国需要增加可用于能够研究基地,使数据的新发现,并在实际我们在科学的投资,以增加资金。”

2007 - 2013年间,欧盟的资助到英国学来约3十亿£i 并传播机构,个人和经济欠发达地区(包括康瓦尔,威尔士部分地区和苏格兰高地)之间。 [1] 承诺在秋季2016通过增减4.7十亿£2020年至2021年之前,科研投入承保此。我们注意到,不过,所提出的总体变化将保持低于国内生产总值的2.4%,OECD国家平均英国的投资。 [2]

Links between academia and industry could also be better supported: the Dowling Review concluded in 2015 that researchers’ access to industry projects and production of research inspired by industry uses need strong explicit support in the 研究 Excellence Framework. [3] Additional to this, a stronger collaborative infrastructure should engage a wider range of businesses, NGOs and public bodies in offering their own support for R&D. [4]



i
资金净额 - 英国之间对欧盟和欧盟对英国的资金流量差

在我们的研究基地统计

Data and statistical methods form the crucial support or building-blocks to establish findings and new discoveries for our whole research base. However, industry and universities alike report hard-to-fill vacancies in statistics and data analytics, and high and persistent demand for numerical and data-analytical skills.[5] 公共资金的卓越研究的重点线索,在一般情况下,资源集中在领先的研究机构,政府部长们观察到。 [6] 建立研究发现,影响和应用为整个研究基地的利益,所有的研究机构需要与数据很好地工作。我们认为这是跨领域的资金,以解决差距。

“统计作为一门学科是作为强大的科学发现和分析,并为新的基础在我们整个研究基地的关键‘数据科学’的应用程序。”