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，自不久前以来一直在全球范围内获得发展势头，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上宣称领土并收集成果。提出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，弥合了理论与实践之间的差距，有助于确保好奇心驱动的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部门产生革命性的变化，包括ICT，金融，医疗服务，制造业，教育和自然资源。通过（a）更快、更可靠的信息共享和（B）提高运营效率和降低成本，基于大数据中无法获得的信息做出更准确、更明智的决策。

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.