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Thesis
Peer Reviewed

Texera: A System for Collaborative and Interactive Data Analytics Using Workflows

Wang, Zuozhi
Advisor(s): Li, Chen

UC Irvine Electronic Theses and Dissertations (2023)

In the world of data analytics, domain experts, such as public health scientists and medical researchers, play a crucial role as their domain knowledge can unlock valuable insights from data. However, they face several challenges in the current landscape of data analytics tools. They often lack the technical skills necessary to analyze large datasets, requiring collaboration with technical experts who may not have relevant domain knowledge. Moreover, when processing large volumes of data, the execution times can be lengthy, and non-technical users are left in the dark without feedback.

Over the past six years, our team has been developing Texera, a workflow-based data analytics system specifically designed to enable non-technical users to perform data analytics tasks with ease by promoting seamless collaboration and responsive interactions. Texera enables multiple users to collaboratively construct workflows, offering an experience similar to that of Google Docs and Overleaf. Furthermore, Texera allows users to interact with the workflow execution, enabling them to pause/resume workflows, inspect execution states, and modify logic as needed.

In this thesis, we first present an overview of the Texera system in Chapter 2, discussing the design choices and the associated tradeoffs of several key components within Texera that enable these powerful features of real-time collaborations and user interactions. Following this, in Chapter 3, we explore a specific use case of user interaction: modifying the logic of operators in a workflow, also referred to as reconfigurations. We develop an algorithm called Fries, which can schedule these reconfigurations with minimal delay while maintaining transactional guarantees, particularly when a reconfiguration involves multiple operators. In Chapter 4, we shift our focus to incremental data processing, as Texera uses progressive computation to deliver early results to users. We present Tempura, a cost-based optimization framework designed for incremental processing. As a general framework, Tempura can support various incremental computation requirements for many different applications and use cases even beyond Texera's scope. Tempura can select the best incremental computation plan based on the specific query and data involved. In Chapter 5, we conclude this thesis and discuss future work.

Cover page: Texera: A System for Collaborative and Interactive Data Analytics Using Workflows

Creative Commons 'BY' version 4.0 license

Article

How the Experience of California Wildfires Shapes Twitter Climate Change Framings

UC Irvine Previously Published Works (2023)

Abstract: Climate communication scientists search for effective message strategies to engage the ambivalent public in support of climate advocacy. The personal experience of wildfire is expected to render climate change impacts more concretely, pointing to a potential message strategy to engage the public. This study examined Twitter discourse related to climate change during the onset of 20 wildfires in California between years 2017-2021. We content analyzed tweets geographically and temporally proximal to the occurrence of wildfires to discover framings and examined how mean frequencies in climate framings changed before and after fires. Results identified three predominant climate framings: making explicit links between wildfire and climate change, suggesting climate actions, and attributing climate change to adversities besides wildfires. Mean tweet frequencies linking wildfire with climate change and attributing adversities increased significantly after the onset of fire while urging climate action tweets did not. Temporal analysis of tweet frequencies of tweets linking wildfires to climate change showed that discussion increased after the onset of a fire but persisted typically no more than one to two weeks. External real-world events happening simultaneously during wildfires also triggered climate discussions. Our findings contribute to identifying how the personal experience of wildfire shapes Twitter discussion related to climate change, and how these narratives change over time before and after wildfires, leading to insights into critical time points after wildfire for implementing message strategies to increase public engagement on climate change impacts and policy.

Cover page: How the Experience of California Wildfires Shapes Twitter Climate Change Framings

Article
Peer Reviewed

How the experience of California wildfires shape Twitter climate change framings

UC Irvine Previously Published Works (2024)

Climate communication scientists search for effective message strategies to engage the ambivalent public in support of climate advocacy. The personal experience of wildfire is expected to render climate change impacts more concretely, pointing to a potential message strategy to engage the public. This study examined Twitter discourse related to climate change during the onset of 20 wildfires in California between the years 2017 and 2021. In this mixed method study, we analyzed tweets geographically and temporally proximal to the occurrence of wildfires to discover framings and examined how frequencies in climate framings changed before and after fires. Results identified three predominant climate framings: linking wildfire to climate change, suggesting climate actions, and attributing climate change to adversities besides wildfires. Mean tweet frequencies linking wildfire to climate change and attributing adversities increased significantly after the onset of fire. While suggesting climate action tweets also increased, the increase was not statistically significant. Temporal analysis of tweet frequencies for the three themes of tweets showed that discussion increased after the onset of a fire but persisted typically no more than 2 weeks. For fires that burned for longer periods of more than a month, external events triggered climate discussions. Our findings contribute to identifying how the personal experience of wildfire shapes Twitter discussion related to climate change, and how these framings change over time during wildfire events, leading to insights into critical time points after wildfire for implementing message strategies to increase public engagement on climate change impacts and policy.