End-User Development for Linked-Data Observatories

Making Linked Data Discoverable through End-User Development (EUD) Techqniues to support Bioscience and Wildlife Research in the Context of Data Observatories

Linked-Data is a set of design principles to structuring data in an interconnected system to make them accessible and machine-readable. When the data gets linked, it becomes traversable, and nodes will be linked through relationships. Linked Data breaks down the information silos that exist between various formats and brings down the fences between various sources. It facilitates the extension of the data models and allows easy updates. As a result, data integration and browsing through complex data become easier and more efficient. In addition, Linked-Data follows a specific schema that makes it easily understood by machines and humans alike. Unfortunately, even though the data is human-readable, it is challenging for non-expert users to retrieve it because Linked-Data will need a good understanding of Semantic queries. Learning Semantic query (i.e., SPARQL Query Language) is not easy for non-expert users, and it is unlikely end-users will use it.

This project makes the Linked-Data more accessible and allows the non-technical end-user (e.g., Bioscience Researchers, wildlife conservationists) to perform their job more efficiently through developing novel interfaces. More specifically, we aim to combine GUIs with conversational AI techniques to facilitate efficient and effective linked data retrieval for non-technical users. The naive user will not need to have any experience using SPARQL or any other query language to retrieve the data. Besides, expert users will perform their job easier in less time.

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