With this project, we want to make scientific contributions on the Web, e.g. articles, reviews, blog posts, multimedia objects, datasets, individual data entries, annotations, discussions, etc., better valorized and efficiently assessed in a way that allows for their automated interlinking, quality evaluation and inclusion in scientific workflows.
Our approach is based on the novel combination of three complementary techniques for integration and assessment of scientific contributions: (1) provenance-aware semantic modeling and publishing, (2) crowdsourcing, expert nichesourcing, (3) information extraction and machine learning. We believe that only a combination of these technologies can unleash the value of scientific contributions in the Web age.
Use Case 1: Semantic Publishing
We will setup an experimental platform to organize contributions around scientific journals. This platform will extend existing publishing frameworks to test in practice the approaches that we propose to enable semantic publishing and automated quality assessment of scientific papers and reviews. We will in this way experiment with new innovative approaches to scientific publishing that might shape the scientific publishing landscape in the future.
Use Case 2: Large corpus of multimedia objects
The proposed framework will be utilized for publishing, annotating and curating a large corpus of multimedia objects. This will allow scientists when publishing papers describing experiments with a dataset to be automatically linked to the dataset. This use case will also consider different channels of publishing such collections, and aims to increase their visibility and value.