  The current de-facto way to query the Web of Data is through the SPARQL
protocol, where a client sends queries to a server through a SPARQL endpoint.
Contrary to an HTTP server, providing and maintaining a robust and reliable
endpoint requires a significant effort that not all publishers are willing or
able to make. An alternative query evaluation method is through link traversal,
where a query is answered by dereferencing online web resources (URIs) at real
time. While several approaches for such a lookup-based query evaluation method
have been proposed, there exists no analysis of the types (patterns) of queries
that can be directly answered on the live Web, without accessing local or
remote endpoints and without a-priori knowledge of available data sources. In
this paper, we first provide a method for checking if a SPARQL query (to be
evaluated on a SPARQL endpoint) can be answered through zero-knowledge link
traversal (without accessing the endpoint), and analyse a large corpus of real
SPARQL query logs for finding the frequency and distribution of answerable and
non-answerable query patterns. Subsequently, we provide an algorithm for
transforming answerable queries to SPARQL-LD queries that bypass the endpoints.
We report experimental results about the efficiency of the transformed queries
and discuss the benefits and the limitations of this query evaluation method.
