In the morning portion of class today we analyzed and critiqued projects that have occurred over the years, including the Indiana Ontology Philosophy Project [https://inpho.cogs.indiana.edu], and the 1995 Cervantes Project [http://cervantes.tamu.edu/V2/CPI/index.html]. We discussed RDF ontologies, or vocabularies, and we looked at a few databases that house these descriptors, such as dbpedia.org. Both scientific and humanistic data have been increasing exponentially over the last decade, and the need to link these resources together in an open format is very apparent. However, many academics are unaware that the methods they use to create and distribute data are closed systems and formats, such as Word documents and PDFs. Using the frameworks for linked open data can ensure that web-based projects become connected to the scholarly record, instead of being siloed and possibly forgotten in lonely corners of the Internet.
In the afternoon we covered database types, including SQL, NoSQL, Graph, and LDAP. With each of these database types come benefits and also pitfalls, but the key takeaway is to use the database type you’re most familiar with to help get projects off the ground. SQL databases are more rigid than NoSQL, but the additional flexibility of NoSQL can help projects without a clear idea of their datasets to begin building while the initial development is still in process. RDF is itself a framework, but not a standard. This is obvious in the RDF acronym, Resource Description Framework, but the ubiquity of the term can make it appear as though RDF is fully fleshed-out and set in stone. Overall, what’s really being worked toward through RDF and Linked Open Data is to interconnect web resources in such a way that they’re beneficial for knowledge creation by humans, and this can only be done if they’re inherently readable and actionable by machines.