  Link Traversal-based Query Processing (ltqp), in which a sparql query is
evaluated over a web of documents rather than a single dataset, is often seen
as a theoretically interesting yet impractical technique. However, in a time
where the hypercentralization of data has increasingly come under scrutiny, a
decentralized Web of Data with a simple document-based interface is appealing,
as it enables data publishers to control their data and access rights. While
ltqp allows evaluating complex queries over such webs, it suffers from
performance issues (due to the high number of documents containing data) as
well as information quality concerns (due to the many sources providing such
documents). In existing ltqp approaches, the burden of finding sources to query
is entirely in the hands of the data consumer. In this paper, we argue that to
solve these issues, data publishers should also be able to suggest sources of
interest and guide the data consumer towards relevant and trustworthy data. We
introduce a theoretical framework that enables such guided link traversal and
study its properties. We illustrate with a theoretic example that this can
improve query results and reduce the number of network requests. We evaluate
our proposal experimentally on a virtual linked web with specifications and
indeed observe that not just the data quality but also the efficiency of
querying improves.
  Under consideration in Theory and Practice of Logic Programming (TPLP).
