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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.
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A Demonstration of Interactive Exploration of Big Geospatial Data on UCR-Star
The ever rising volume of geospatial data is undeniable. So is the need to explore and analyze these datasets. However, these datasets vary widely in their size, coverage, and accuracy. Therefore, users need to assess these aspects of the data to choose the right dataset to use in their analysis. Unfortunately, all the publicly available repositories for geospatial datasets provide a list of datasets with some information about them with no way to explore the datasets beforehand. Through this demonstration, we propose the repository, UCR-Star, that is capable of hosting hundreds of thousands of geospatial datasets that a user can explore visually to judge their quality before even downloading them. This demo provides a deeper dive into the core engine behind UCR-Star. It provides a web interface geared towards database researchers to understand how the index internally works. It provides a comparison interface where the attendees can see side-by-side how two versions of the system work with the ability to customize each of them separately. Finally, the interface reports the response time of the indexes for a quantitative comparison.
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- PAR ID:
- 10293607
- Date Published:
- Journal Name:
- SIGSPATIAL '20: Proceedings of the 28th International Conference on Advances in Geographic Information Systems
- Page Range / eLocation ID:
- 151 to 154
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3397536.3422334
