  Data on the web is naturally unindexed and decentralized. Centralizing web
data, especially personal data, raises ethical and legal concerns. Yet,
compared to centralized query approaches, decentralization-friendly
alternatives such as Link Traversal Query Processing (LTQP) are significantly
less performant and understood. The two main difficulties of LTQP are the lack
of apriori information about data sources and the high number of HTTP requests.
Exploring decentralized-friendly ways to document unindexed networks of data
sources could lead to solutions to alleviate those difficulties. RDF data
shapes are widely used to validate linked data documents, therefore, it is
worthwhile to investigate their potential for LTQP optimization. In our work,
we built an early version of a source selection algorithm for LTQP using RDF
data shape mappings with linked data documents and measured its performance in
a realistic setup. In this article, we present our algorithm and early results,
thus, opening opportunities for further research for shape-based optimization
of link traversal queries. Our initial experiments show that with little
maintenance and work from the server, our method can reduce up to 80% the
execution time and 97% the number of links traversed during realistic queries.
Given our early results and the descriptive power of RDF data shapes it would
be worthwhile to investigate non-heuristic-based query planning using RDF
shapes.
