Search for: All records

With the rise of data science, there has been a sharp increase in data-driven techniques that rely on both real and synthetic data. At the same time, there is a growing interest from the scientific com- munity in the reproducibility of results. Some conferences include this explicitly in their review forms or give special badges to repro- ducible papers. This tutorial describes two systems that facilitate the design of reproducible experiments on both real and synthetic data. UCR-Star is an interactive repository that hosts terabytes of open geospatial data. In addition to the ability to explore and visu- alize this data, UCR-Star makes it easy to share all or parts of these datasets in many standard formats ensuring that other researchers can get the same exact data mentioned in the paper. Spider is a spa- tial data generator that generates standardized spatial datasets with full control over the data characteristics which further promotes the reproducibility of results. This tutorial will be organized into two parts. The first part will exhibit the key features of UCR-star and Spider where participants can get hands-on experience in in- teracting with real spatial datasets, generating synthetic data with varying distributions, and downloading them to a local machine or a remote server. The second part will explore the integration of both UCR-Star and Spider into existing systems such as QGIS and Apache AsterixDB.