SWOT analysis is a popular planning method used to evaluate the Strength, Weakness, Opportunities, and Threats of an organization’s internal and external environments.
1.1 It has succeeded in a niche of serving the academic community not only to preserve but to discover and access to contents that come from a variety of sources, including public domain, Google, Internet Archive, Microsoft, and in-house partner institutions. It is the largest network of research libraries and institutions, 72 partners as of March 2013.
1.2 Due to fair use exception, it has better position than commercial companies to open up in-copyright materials to great extent such as assigning viewability status to library copies, moving orphan works into the public domain, etc.
1.3 Its collaborative works among partners have resulted in a wide range of tools, including discovery, validation, full text research, highly scalable redundant clustered storage system, copyright review, and so on.
1.4 It has embraced a true service-oriented architecture (SOA) for supporting the service scalability over time and allowing third-party applications to enhance accesses to its gigantic contents.
1.5 It has achieved high standard of preservation, and was certified as a “Trustworthy Digital Repository” by TRAC who only awarded such a distinction to two institutions as of 2011.
2.1 Its citation exportation capabilities were disappointing. The information exported is often incomplete. (https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=20&cad=rja&ved=0CIEBEBYwCTgK&url=http%3A%2F%2Fjournals.tdl.org%2Fpal%2Findex.php%2Fpal%2Farticle%2Fdownload%2F5880%2F5922&ei=j8E7UcrsBOWHywGeh4HYBQ&usg=AFQjCNGMT2QhplQCqahTwu2CYiIgqHVsLw&bvm=bv.43287494,d.aWc)
2.2 Provision of new content types, including multimedia, is still in primitive stage.
2.3 With multiple ingestions and/or sources, duplication and inconsistency are still prevailing.
3.1 Its funding is constrained by partner members’ contributions. It might need to create other revenue streams such as licensing its developed technologies, to overcome short-term fluctuations in financial pressures or uncertainties.
3.2 It is a challenge, considering disparate agendas of its members, to resolve the tension in developing services for new content types while continuing to improve the legacy core services.
3.3 Collaborative learning environment support is an area less addressed by HathiTrust but is becoming a hot wish-list item in university environments.
4.1 By licensing its developed technologies to DPLA, it can create revenue streams to fulfill its mission through more R&D. DPLA’s goals have significant overlapping with HathiTrust’s, although it is hard to predict what its end product will be eventually. However, many of technologies or know-hows developed in HathiTrust should be applicable to DPLA.
4.2 Expressing relationships among objects in RDF triples would enable richer searches and lay the foundation for creating standards or tools for the future semantic network.
4.3 Further applying machine learning technologies can facilitate the understanding of usage patterns and consequently offer higher-quality recommendation or discovery services.
4.4 Expanding its mission to support on-line course teaching is a promising area to grow.