Are you building or maintaining a Sesame-based application? Aduna has extensive
experience in setup and auditing that can greatly improve your projects ROI. Or
perhaps you are looking for someone who can implement or improve Sesame
functionality? Aduna has all the skills! Please feel free to
contact us to discuss
how we can be of help to you!
Three examples of Sesame projects:
- How to find dinosaurs across Europe?
An infrastructure was created to connect online collections of cultural heritage
organizations across Europe. The software works on top of different collection
management systems and it generates new virtual collections of objects.
- Fighting the paper-based "Thesaurus Rex"
A Sesame-based infrastructure was used to make a large thesaurus - tens of thousands
of pages on paper - accessible. Users are given the ability to query and navigate
a collection of medical research papers using the thesaurus, while hiding much of
the complexity, such as the existence of multiple data sources.
- "Needle in the haystack"
Working on top of a file system and a database, Sesame integrates data from both
sources. It allows the user to search both sources at once.
Some examples of organizations that have implemented Sesame solutions:
- Pharmaceutical organizations: Disclosure of large medical data sources.
- Publishers: Finding publications with a thesaurus.
- Museums: Connect collections of different museums.
- Governments: Create an open government data infrastructure.
- Software vendors: Create platforms and tools to explore, mine, present large information collections
Sesame could be the right choice for you:
- When your project requires integration of data from different sources
- When you use standards like RDF and SPARQL
- When you want to wrap existing data sources in a semantic web architecture
- When you want a flexible, adaptable, transparant information architecture
- When you're looking for cloud solution for complex integration projects.
Contact us if you want help:
- Creating a semantic web architecture for your project.
- Installing Sesame in your project environment.
- Writing and optimizing SPARQL queries to find data.
- Implementing requested features on top of Sesame.
- Writing wrappers for your existing data sources.
- Auditing and implementation reviews.