TWed Discussion: Using Semantic Data Dictionaries for Semantic Data Conversion in SETLr

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Website: TWed Discussion: Using Semantic Data Dictionaries for Semantic Data Conversion in SETLr
When: March 29 2017
Where: Winslow 1140, RPI Campus, Troy, NY
TWed Talk: Weds, 29 Mar (6p Winslow 1140)
TITLE: "Using Semantic Data Dictionaries for Semantic Data Conversion in SETLr"
LEADER: Katie Chastain
VIDEO: TWed video streams
EVENT: YouTube
KEYWORDS: Linked Data, Semantic Web, SETLr

Please join us this Weds (29 Mar, 6p Winslow 1140) as TWC PhD student Katie Chastain leads us in a tour-de-force discussion of the challenges presented when including data dictionaries and codebooks in knowledge graphs, and the use of SETLr to slay such dragons. Katie's talk will include a very brief review of SETLr for noobies...

DESCRIPTION: Conversion of tabular data into linked data is a daunting task for many projects, where hand-crafting conversion parameters is not a scaleable solution. After a brief (re)introduction to SETLr and its functionality and capabilities, I will present a Semantic Data Dictionary as an extension to a traditional data dictionary. I will highlight its usefulness for limiting the workload for human users in annotating implicit data structure, and then describe a "parsing" script for processing a completed SDD into a SETLr script. I can talk about potential future work for the parse script, and I invite discussion and ideas for what functionalities may be helpful to other research projects.

BIO: Katie Chastain is a Ph.D student working with Prof. McGuinness, focusing on data curation for semantic web applications. Their current research is with the Gates Foundation's Healthy Birth, Growth, and Development program, working on a relatively painless way to get the many datasets involved into linked data format for use in the cool visualizations the TWC is developing with CASE. Outside of research, their interests include '90s science fiction television, Magic the Gathering, and cooperative problem solving in a fantasy environment (aka Dungeons and Dragons).

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