What do you need in a graph library?
A recently launched open source library in Python provides an abstraction layer for developing knowledge graphs. This survey attempts to find needs/features/use cases for us to prioritize in our development roadmap. Your info will be kept private, not shared with any third-party, and will not be used for any form of targeted marketing.
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What kinds of graph support do you need most? *
Which serialization methods do you need most?
Clear selection
Which forms of network inference do you need most?
Clear selection
Which forms of validation support do you need most?
Clear selection
Which graph database integrations do you need most?
Clear selection
What kinds of graph algorithms do you need to use the most?
Any other suggestions about what you'd like to see in a KG library?
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