Creativity@Home: Collaborative Performance Analytics

该提案源于通过EPSRC试行的创意@home计划进行的讨论。这些讨论集中在三个注定会相互影响的主要社会趋势上--信息爆炸、移动的计算的出现以及社交网络和开放式创新的增长。显然，这三大趋势带来了新的机遇，但也带来了重大挑战。第一个问题是如何理解当今组织可获得的大量数据。世界正变得更加工具化-组织正在收集更细分的数据。信用卡和会员卡等服务允许银行和零售商获取个性化数据。每部移动的手机都会传输位置数据，而每部安全摄像头都会记录活动数据。产品越来越工具化。汽车和飞机上的传感器不断传输有关产品性能和可靠性的数据。每次访问一个网站都会留下足迹。数据包含在发布到Facebook的每张照片和发布到Twitter的每条推文中!组织面临的挑战是如何利用这些数据并从中提取洞察力。今天的背景意味着这一挑战因三个因素而变得复杂-（i）简单的数据量，（ii）80%的数据是非结构化的，（iii）大部分数据存在于断开连接的源文件中-数据库，Excel电子表格和个人网站。这一提议的基础理论是，移动的计算和社交网络技术的并行发展，包括开放式创新，可能为从数据中获取洞察力的挑战提供解决方案。虽然理解数据的简单挑战并不新鲜，但这一提议的新颖之处在于将移动的技术与社会分布式工作方式结合起来，探索我们称之为协作性能分析的潜力。协作绩效分析建立在开放式创新和社会分布式工作方式的基础上。它提出了一个问题-组织如何向更广泛的社区开放他们的性能数据，并让他们参与分析过程。显然，一个先决条件是，更广泛的社区必须获得能够实现社会分布式工作的技术。因此，这一建议的主旨-我们应该把移动的技术与社交网络应用程序结合起来，以实现协作性能分析。为了探索这一概念，本提案解释了我们打算如何创建一个演示场景，以说明协作性能分析的潜力。

This proposal stems from discussions that took place through the creativity@home scheme piloted by the EPSRC. These discussions centered on three major societal trends that are destined to influence each other - the explosion of information, the emergence of mobile computing and the growth in social networking and open innovation. Clearly these three major trends open up new opportunities, but they also pose significant challenges. The first of which is how to make sense of the copious quantity of data available to organizations today.The world is becoming more instrumented - organizations are collecting data at ever more disaggregated levels. Services, such as credit and loyalty cards, allow banks and retailers to capture individualized data. Every mobile phone transmits location data, while every security camera records activity data. Products are increasingly instrumented. Sensors in cars and planes continuously transmit data on product performance and reliability. Every visit to a website leaves a footprint. Data is contained in every photo posted to Facebook and every tweet made to Twitter!A challenge for organizations is how to harness these data and extract insight from them. Today's context means that this challenge is complicated by three factors - (i) the simple volume of data, (ii) the fact that 80% of this data is unstructured and (iii) the fact that much of the data lies in disconnected source files - databases, excel spreadsheets and individual websites.The thesis that underlies this proposal is that parallel developments in mobile computing and social networking technologies, including open innovation, may offer a solution to the challenge of extracting insight from data. For while the simple challenge of making sense of data is not new, the novelty in this proposal lies in bringing together mobile technologies, with socially distributed ways of working, to explore the potential of what we are calling collaborative performance analytics. Collaborative performance analytics builds on the ideas of open innovation and socially distributed ways of working. It asks the question - how might organizations open up their performance data to a wider community and engage them in the analytics process. Clearly a pre-requisite would be for the wider community to have to have access to technologies that enable socially distributed working. Hence the thrust of this proposal - that we should bring together mobile technologies, with social networking applications to enable collaborative performance analytics. To explore this concept this proposal explains how we intend to create a demonstrator scenario to illustrate the potential of collaborative performance analytics.