2022 NASA Space Apps Challenge - Tacoma Location
"Can AI Preserve Our Science Legacy?" 🔗
The challenge is to develop a technique using Artificial Intelligence (AI) to improve the accessibility and discoverability of records in the public NASA Technical Report Server (NTRS).
Proposed solution 🔗
Improve the accessibility and discoverability of records in the NTRS
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The Search Algorithm (Librarian Analogy)
- Enter query through the api
- Receive a list of documents
- Drill down into the full text of the document
- Run NLP to get some statistics for ranking
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automatically read NTRS documents
- summarize them (Pre-Trained),
- generate text analytic data (Word Cloud, Frequency Distribution Visualisation, Question Generation and Answering),
- produce a list of topic keywords to help researchers find the documents they need.
- Delivering PDFs in a binder available for reading (with similar parts highlighted)
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Challenge specification pdf 🔗
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An example query 🔗 that returns json and defaults to the first 25 of 345 items.
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json viewers
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online 🔗
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cd /data/infiles jq '.' query-result.json | less jq 'keys' query-result.json jq '.results | .[2]' query-result.json | less jq '.results | .[2] | .downloads' query-result.json | less jq '.results | .[2] | .downloads | .[0]' query-result.json jq '.results | .[2] | .downloads | .[0] | .links' query-result.json jq '.results | .[2] | .downloads | .[0] | .links | .fulltext' query-result.json
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python
- json-module 🔗 (note there is a difference between load and loads !)