Xiaozhen Liu: Demonstration of Collaborative and Interactive Workflow-based Data Analytics in Texera

Abstract:

Collaborative data analytics is becoming increasingly important due to the higher complexity of data science, more diverse skills from different disciplines, more common asynchronous schedules of team members, and the global trend of working remotely. In this demo we will show how Texera supports this emerging computing paradigm to achieve high productivity among collaborators with various backgrounds. Based on our active joint projects on the system, we use a scenario of social media analysis to show how a data science task can be conducted on a user friendly yet powerful platform by a multi-disciplinary team including domain scientists with limited coding skills and experienced machine learning experts. We will present how to do collaborative editing of a workflow and collaborative execution of the workflow in Texera. We will then show the technical details of how we support these features in our system. First we will show how collaborative editing is achieved in Texera, then we will focus on data-centric features such as synchronization of operator schemas among the users during the construction phase, and monitoring and controlling the shared runtime during the execution phase.

Bio:

Xiaozhen Liu is a 2nd-year Ph.D. student in the Computer Science Department at UC Irvine. He received his B.E. in Computer Science from Southeast University, China. His current research interests include big data processing and collaborative data analytics systems.