Deprecated. This material represents early efforts and may be of interest to historians. It doe not describe current VIVO efforts.

Page tree

Versions Compared


  • This line was added.
  • This line was removed.
  • Formatting was changed.


Approach to building the index
  1. For each institution
    1. Get a list of all URIs of interest for that institution
  2. For each URI
    1. Get the linked data RDF for the URI
    2. Build a Solr index "document" using the RDF statements for which that URI is the subject; subsequent request obtain additional data for related objects based on VIVO's linked data harvesting patterns, that will add to the index a person's title(s) from their position(s) and other data from their VIVO page (real or virtual, if from another system) that would normally be indexed with that person in VIVO's internal search
      • TODO: what governs the follow-on linked data requests, and do the results from what is harvested into a local VIVO search?
    3. Add the document to the Solr index


  1. There are some parts of the technology stack that are suggested by the goal of indexing data from VIVO. 
    • Using HTTP requests for RDF to gather data from the sites is the most direct approach.
    • Most other options for gathering data from the VIVO sites would need additional coding.
  2. In general we would go with Solr for the search index because of we have experience with it, because of its documentation, because of it distributed features and because it is mature.
  3. As of 2012 uses Drupal and solrsearch javascript libraries. The js libraries allow the development of the search UI with only client side interaction ( ).
    • This choice could be revisited for the multi-site VIVO search project. 
  4. In order to scale the process out we were planing to use Hadoop to manage parallel tasks and to run the indexing jobs on a set VMs setup as Hadoop nodes.
    • Many approaches to the problem of indexing linked data from VIVO sites would be embarrassingly paralleled.
    • Brian Caruso Cornell has worked with RDF indexing to Solr on Hadoop clusters on Eucalyptus clouds.
    • Consider using a IaaS abstraction layer such as jcloudsapache libcloud or overmind. These allow developing against an interface which can then target many different cloud service providers. The primary goal of this would be to avoid lock in to one cloud provider.


  • HTTP for retrieving RDF, yes
  • What is the adoption of SPARQL in the community
  • It may be nice to demonstrate that a SPARQL endpoint is not needed to enable interesting results
  • Solr, seems reasonable for now
    • Considering having Solr in one place versus distributed Solr (master/slaves)
  • Web interface: drupal with solrsearch.js
    • Most work is on clientside with js
    • This continues to be appealing
    • We have limited insight into this component
    • Suggestion to create list of default technologies, criteria, and alternatives
  • Hadoop is currently reasonable choice
  • Ruby (blacklight/hydra) or Drupal?
    • The js pattern allows from minimal reliance on Drupal
  • Need a mock-up of the UI to inform design of solr index
  • BootStrap is an interesting js framework to consider
  • Drupal upgrade cycle can be onerous