  The fashion industry is looking forward to use artificial intelligence
technologies to enhance their processes, services, and applications. Although
the amount of fashion data currently in use is increasing, there is a large gap
in data exchange between the fashion industry and the related AI companies, not
to mention the different structure used for each fashion dataset. As a result,
AI companies are relying on manually annotated fashion data to build different
applications. Furthermore, as of this writing, the terminology, vocabulary and
methods of data representation used to denote fashion items are still ambiguous
and confusing. Hence, it is clear that the fashion industry and AI companies
will benefit from a protocol that allows them to exchange and organise fashion
information in a unified way. To achieve this goal we aim (1) to define a
protocol called DDOIF that will allow interoperability of fashion data; (2) for
DDOIF to contain diverse entities including extensive information on clothing
and accessories attributes in the form of text and various media formats; and
(3)To design and implement an API that includes, among other things, functions
for importing and exporting a file built according to the DDOIF protocol that
stores all information about a single item of clothing. To this end, we
identified over 1000 class and subclass names used to name fashion items and
use them to build the DDOIF dictionary. We make DDOIF publicly available to all
interested users and developers and look forward to engaging more collaborators
to improve and enrich it.
