  Although several grammar-based self-indexes have been proposed thus far,
their applicability is limited to offline settings where whole input texts are
prepared, thus requiring to rebuild index structures for given additional
inputs, which is often the case in the big data era. In this paper, we present
the first online self-indexed grammar compression named OESP-index that can
gradually build the index structure by reading input characters one-by-one.
Such a property is another advantage which enables saving a working space for
construction, because we do not need to store input texts in memory. We
experimentally test OESP-index on the ability to build index structures and
search query texts, and we show OESP-index's efficiency, especially
space-efficiency for building index structures.
