The VIVO DuraSpace Project is pleased to announce the release of VIVO 1.7. The VIVO 1.7 release combines new features with improvements to existing features and services and continues to leverage the VIVO-Integrated Semantic Framework (VIVO-ISF) ontology introduced in VIVO 1.6. No data migration or changes to local data ingest procedures, visualization, or analysis tools drawing directly on VIVO data will be required to upgrade to VIVO 1.7.
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 of the entire research community.
VIVO 1.7 also incorporates several updates to key software libraries in VIVO, including the Apache Jena libraries that provide the default VIVO triple store from Jena 2.6.4 to Jena 2.10.1. This Jena upgrade does require existing VIVO sites to run an automated migration procedure for user accounts prior to upgrading VIVO itself.
The Apache Solr search 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 to benefit from 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 knowledge base for analysis by external tools has also been improved to scale better with triple store size, as has the ability to request lists of RDF by type to facilitate linked data applications.
The VIVO 1.7 release also reflects feedback from VIVO Project sponsors requesting a predictable pattern of one minor release and one major release each year. We anticipate releases in late spring/early summer and late fall to help adopters anticipate the schedule for new features and anticipate any necessary changes to local data ingest processes, visualizations, reporting, and/or data analysis.