This is NOT a list of currently available Masterprojects, as a current list is in the works. If you want to know what we offer please come and contact us directly. You can also contact a supervisor of a project / Prof. Bernstein directly to to talk about you own ideas.
Linked Raster Data
Project for 3-5 Students
In the Geo-Sptial community, Linked Data is gaining increasing importance. Recent examples are Linked Geo-Data and, most popular, Geonames aka the Linked Data version of Open Street Map. Such initiatives are not only supported by academia but indeed backed by prominent partners from industry (e.g. ESRI, Oracle) and the public services (UK Ordnance Survey, Swiss Federal Office for the Environment, US National Geographic Survey). Most approaches, however, aim towards the processing of vector data where entities (points, lines, polygons) are defined ex-ante. In collaboration with the Department of Geography (UZH) we recently approached towards linking raster data such as fields containing information about slope, height, population density, etc. to the Linked Open Data cloud. In particular, it is features deduced from raster data that can potentially be enriched with semantics.
Your task will be to integrate operators from a Geographic Information System such as ArcGIS or GRASS into a SPARQL engine such as Jena or Sesame. Based on a faceted browser you will integrate raster-data into the results of faceted search and/or faceted browsing. In the context of a Bachelor's thesis you will also show how operators in SPARQL translate into operators in the GIS. If performed as a Master Project, the work will more focus on the integration and optiomization aspect of SPARQL to GIS and vice versa.
Contact: Thomas Scharrenbach
Most of todays (web) applications rely on some kind of ORM (Object-relational-mappers or Object-RDF-mappers) libraries to talk to databases. The ORM layers do a minimal effort when constructing queries for the underlying database, pushing thus the "hard-work" to the database optimizer. This projects aim is to enrich the ORM library with a database aware optimizer intended to create an optimal "mix" of queries intended to maximize the applications performance (interaction-throughput). The project is implemented in python. We are looking for students that have good knowledge of functional programming languages (not necessarylly python)
Contact: Cosmin Basca