The VIVO DuraSpace Project is pleased to announce the release of VIVO 1.7. VIVO 1.7 introduces new features as well as improvements to existing features and services. In contrast to VIVO 1.6, however, VIVO 1.7 does not include changes to the VIVO-Integrated Semantic Framework (VIVO-ISF) ontology that required data migration or changes to local data ingest procedures or to visualization or analysis tools drawing directly on VIVO data.
VIVO 1.7 notably includes the results of an ORCID Adoption and Integration Grant (http://goo.gl/fLIuVb) to support the creation and verification of ORCID iDs. VIVO now offers the opportunity for a researcher to add and/or confirm his or her global, unique researcher identifier directly with ORCID (http://orcid.org) without the necessity of applying through other channels and re-typing the 16-digit identifier. We anticipate that this facility will help promote ORCID iDs more widely and expand adoption for the benefit the entire research community.
VIVO 1.7 also incorporates several updates to key software libraries in VIVO, including updating the Apache Jena libraries that provision the default VIVO triple store from Jena 2.6.4 to Jena 2.10.1. The Apache Solr library used by VIVO has been updated to Solr 4.7.2 and the programming interface to Solr has been modularized to allow substitution of alternative search indexing libraries based on specific desired features.
The SPARQL web services introduced in VIVO 1.6 have been extended to support full read-write capability and content negotiation through a single interface. The ability to export or "dump" the entire VIVO knowledgebase for analysis by external tools has also been improved to scale better with triple store size, and there have been improvements to the ability for an external application to request lists of RDF by type in VIVO to facilitate linked data applications.
The VIVO 1.7 release also reflects feedback from VIVO Project sponsors suggesting a pattern of one minor release and one more major release each year. We anticipate that predictable releases in late spring/early summer and late fall will help adopters plan for changes and coordinate with local data ingest processes, tools, visualizations, and/or analysis.
