Data Workload Generator for Research on Big Data and Network Science

大数据和网络科学是一个战略研究方向，自最近以来一直在全球范围内获得势头，来自学术界和工业界的许多研究小组竞相在这片肥沃的处女地占据地盘并收集成果。拟议的数据工作负载生成硬件和软件对于大数据和网络科学领域发明的解决方案算法的经验评估至关重要，弥合了理论和实践之间的差距，有助于确保好奇心驱动型研究也与行业和潜在客户密切相关。来自大数据和网络科学研究的成功理论和算法预计将对加拿大的许多行业产生革命性的变化，包括通过(A)更快、更强大的信息共享和(B)基于大数据信息的更准确、更知情的决策，提高其运营效率并削减成本，这些行业包括ICT、金融、医疗服务、制造、教育和自然资源。

Big data and network science is a strategic research direction that has been gaining worldwide momentum since the rather recent past, with many research groups from academia and industry racing to claim territory and glean results in this fertile virgin land. The proposed data workload generating hardware and software are together critical for empirical evaluations of solution algorithms invented in the area of big data and network science, bridging the gap between theory and practice, helping make sure that curiosity-driven research is also strongly relevant to industry and potential customers. Successful theories and algorithms from research on big data and network science are expected to make revolutionary changes to a number of sectors in Canada, including ICT, finance, medical services, manufacturing, education, and natural resources, by increasing their operation efficiency and cutting cost through both (a) faster and more robust information sharing and (b) more accurate and informed decision making based on information from big data that is otherwise not available.