  In Brazil, the governmental body responsible for overseeing and coordinating
post-graduate programs, CAPES, keeps records of all theses and dissertations
presented in the country. Information regarding such documents can be accessed
online in the Theses and Dissertations Catalog (TDC), which contains abstracts
in Portuguese and English, and additional metadata. Thus, this database can be
a potential source of parallel corpora for the Portuguese and English
languages. In this article, we present the development of a parallel corpus
from TDC, which is made available by CAPES under the open data initiative.
Approximately 240,000 documents were collected and aligned using the Hunalign
tool. We demonstrate the capability of our developed corpus by training
Statistical Machine Translation (SMT) and Neural Machine Translation (NMT)
models for both language directions, followed by a comparison with Google
Translate (GT). Both translation models presented better BLEU scores than GT,
with NMT system being the most accurate one. Sentence alignment was also
manually evaluated, presenting an average of 82.30% correctly aligned
sentences. Our parallel corpus is freely available in TMX format, with
complementary information regarding document metadata
