Presented by:

Yasin Silva

from Arizona State University

Yasin N. Silva is an associate professor of computer science in the School of Mathematical and Natural Sciences at Arizona State University. Dr. Silva’s research focuses on innovative ways to analyze and process data. His specific areas of interest include: block-based systems for database querying, social media analysis, online misbehavior detection, social computing, cyberbullying detection in social networks, big data, scalable database systems, and fairness and transparency in AI.

Michael Barden

from Arizona State University

Sophomore majoring in Applied Computing, minoring in Communication full-time at ASU with a focus on topics such as big data, optimization and graphic design.

Humberto Luiz Razente

from Universidade Federal de Uberlandia (Brazil) / Arizona State University (ASU)

Humberto Razente is a Associate Professor at the Computer Science Department at Universidade Federal de Uberlandia (Brazil). He is currently (2020) a visiting scholar at Arizona State University (ASU). His research focuses on data structures and algorithms for data mining.

My name is Heather Flynn and I'm an Applied Computing student at Arizona State University. I'm a current research assistant working under Dr. Yasin Silva on the DBSnap project which is a web based application to build database queries.

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Bryant Bettencourt

from UC Berkeley

The ability to retrieve data from a data store and perform core operations such as filtering, merging, and aggregating tasks, is becoming a critical skill in a data driven world where Data Science is becoming a fundamental interdisciplinary field. In this presentation we will describe and show the key features of DBSnap, a web application to build database queries (based on relational algebra operators) by snapping blocks. An important characteristic of DBSnap, which was built adapting existing Snap! modules, is that it uses a tree-based structure to represent a database query. This query structure has been extensively used by educators and in many textbooks as an intuitive way to describe the operators and datasets that are used in a given query and the way the operators interact with each other. DBSnap is also a highly dynamic tool that shows intermediate results of a query as the user adds more data and operator blocks. It also enables the inspection of the intermediate results associated with any node in the query tree. In this presentation we will (1) present the core components of DBSnap to create a query, (2) demonstrate the construction of queries using common operators such as selection, projection, join and grouping, and (3) highlight some recently implemented features such as the support of views and the ability to save and load queries. DBSnap, developed at Arizona State University, is a publicly available tool and aims to have the same transformational effect on database learning as other block-based systems had on traditional programming learning. Additional information about DBSnap can be found at:

Presenters: Yasin Silva, Humberto Razente, Michael Barden, Heather Flynn

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30 min
Zoom 3
Snap!Con 2020
Short Talk
Short Talk