A metadata model for hybrid data products on a multilateral data marketplace

Abstract

Multilateral data marketplaces provide a platform where organizations and individuals can buy, trade, sell, and combine data into hybrid data products. On such marketplaces, multiple different vendors can offer equivalent products in terms of functionality, but different in attributes such as pricing, quality and licensing; attributes that could be contained in metadata. Furthermore, hybrid data products introduce an additional challenge: How can metadata regarding the origin and attributes of data be contained? In this thesis, we propose a metadata model based on W3C PROV that is able to contain both provenance and relevant metadata related to data products. In addition, the functionality of the metadata model is demonstrated and evaluated through a prototype implementation.