TopBraid Composer offers three choices for importing spreadsheet data. The first two are useful when your data is laid out in a straightforward table with clearly named rows and columns, because TopBraid Composer uses these names to dynamically create a model for your data:
Semantic Tables converts an Excel .xls, .xlsx, .csv or .tsv files to an RDF model, using column and row titles to declare properties and instances for that model. Conversion is done dynamically by simply opening the source file; no persistent RDF representation is created. As a result, this conversion is round-trippable. A user can edit Excel source in RDF and save it back in the original Excel format.
Import Spreadsheets converts a tab-delimited file, which can be created by any spreadsheet program, and defines classes and properties for the data. This option uses an import dialog that can map spreadsheet columns into properties of the currently opened ontology. It will create RDF file from the source file.
Importing Excel File into Spreadsheet Ontology uses an import dialog to read an Excel .xls or .xlsx file and create an RDF file with a resource for each data cell. Converted spreadsheet data is represented using the http://www.topbraidcomposer.org/owl/2006/08/spreadsheets.owl ontology, which defines the structure of the spreadsheet with classes such as ss:Cell, ss:Sheet, and ss:Workbook. You can then develop custom SPARQL transformations to extract the data you need from this model and arrange it with a structure that is best suited for your application. This option is often best for spreadsheets with a more complex structure.
Follow the links above for more details on each importing technique.
For additional capabilities in converting spreadsheets to RDF models, TopQuadrant's Enterprise Vocabulary Net product automates the mapping of a variety of popular spreadsheet layouts.