First off, you can use CSV as a Linked Open Data (LOD) serialization format. This has been the case since 2009 (early days of LOD cloud, demonstrated via DBpedia; just look in the footer of any of DBpedia's entity description pages). There's even a Linked CSV draft spect in regards to this matter (there are even CSV Browsers). The only downside is that existing LOD consumer apps/services expect N-Triples, Turtle, JSON-LD (of late), or RDF/XML etc..

If you seek a productivity tool based approach for quickly converting CSV to Linked Open Data, consumable by a majority of existing consumer apps and services, you should consider using a tool like Google Refine or the LOD Refine derivative to achieve this goal. In either case, you will have the ability to leverage existing vocabularies and ontologies when mapping CSV records to actual entities (class instances), entity types (classes), and relationship types (properties associated with a Property Domain (class) and expected values or objects ranges [class instances or typed literals].

If you want to achieve this goal by hand, you should consider the following, in order of ascending complexity:

1. N-Triples
2. Turtle (N-Triples plus a few shorthand tricks for statement brevity)
3. JSON-LD (if you are a Web Programmer conversant with Javascript and conversant with Entity-Attribute-Value based data representation)
4. RDF/XML (if you are a Web Programmer conversant with XML and RDF Language Semantics).

Hope this helps.

First off, you can use CSV as a Linked Open Data (LOD) serialization format. This has been the case since 2009 (early days of LOD cloud, demonstrated via DBpedia; just look in the footer of DBpedia's entity description pages). There's even a Linked CSV draft spec in regard to this matter (there are even CSV Browsers). The only downside is that existing LOD consumer apps/services expect N-Triples, Turtle, JSON-LD (of late), or RDF/XML etc.

If you seek a productivity tool based approach for quickly converting CSV to Linked Open Data, consumable by a majority of existing consumer apps and services, you should consider using a tool like OpenRefine or the LOD Refine derivative to achieve this goal. In either case, you will have the ability to leverage existing vocabularies and ontologies when mapping CSV records to actual entities (class instances), entity types (classes), and relationship types (properties associated with a Property Domain (class) and expected values or objects ranges [class instances or typed literals].

If you want to achieve this goal by hand, you should consider the following, in order of ascending complexity:

1. N-Triples
2. Turtle (N-Triples plus a few shorthand tricks for statement brevity)
3. JSON-LD (if you are a Web Programmer conversant with Javascript and conversant with Entity-Attribute-Value based data representation)
4. RDF/XML (if you are a Web Programmer conversant with XML and RDF Language Semantics).

Hope this helps.

First off, you can use CSV as a Linked Open Data (LOD) serialization format. This has been the case since 2009 (early days of LOD cloud, demonstrated via DBpedia; just look in the footer of any of DBpedia's entity description pages). There's even a Linked CSV draft spect in regards to this matter. The only downside is that existing LOD consumer apps/services expect N-Triples, Turtle, JSON-LD (of late), or RDF/XML etc..

If you seek a productivity tool based approach for quickly converting CSV to Linked Open Data, consumable by a majority of existing consumer apps and services, you should consider using a tool like Google Refine or the LOD Refine derivative to achieve this goal. In either case, you will have the ability to leverage existing vocabularies and ontologies when mapping CSV records to actual entities (class instances), entity types (classes), and relationship types (properties associated with a Property Domain (class) and expected values or objects ranges [class instances or typed literals].

If you want to achieve this goal by hand, you should consider the following, in order of ascending complexity:

1. N-Triples
2. Turtle (N-Triples plus a few shorthand tricks for statement brevity)
3. JSON-LD (if you are a Web Programmer conversant with Javascript and conversant with Entity-Attribute-Value based data representation)
4. RDF/XML (if you are a Web Programmer conversant with XML and RDF Language Semantics).

Hope this helps.

First off, you can use CSV as a Linked Open Data (LOD) serialization format. This has been the case since 2009 (early days of LOD cloud, demonstrated via DBpedia; just look in the footer of any of DBpedia's entity description pages). There's even a Linked CSV draft spect in regards to this matter (there are even CSV Browsers). The only downside is that existing LOD consumer apps/services expect N-Triples, Turtle, JSON-LD (of late), or RDF/XML etc..

If you seek a productivity tool based approach for quickly converting CSV to Linked Open Data, consumable by a majority of existing consumer apps and services, you should consider using a tool like Google Refine or the LOD Refine derivative to achieve this goal. In either case, you will have the ability to leverage existing vocabularies and ontologies when mapping CSV records to actual entities (class instances), entity types (classes), and relationship types (properties associated with a Property Domain (class) and expected values or objects ranges [class instances or typed literals].

If you want to achieve this goal by hand, you should consider the following, in order of ascending complexity:

1. N-Triples
2. Turtle (N-Triples plus a few shorthand tricks for statement brevity)
3. JSON-LD (if you are a Web Programmer conversant with Javascript and conversant with Entity-Attribute-Value based data representation)
4. RDF/XML (if you are a Web Programmer conversant with XML and RDF Language Semantics).

Hope this helps.