The abundance of digital content requires cost-effective technologies to extract the hidden meaning from media objects. However, current approaches fail to deal with the challenges related to cross-media analysis, metadata publishing, querying and recommendation that are necessary to overcome this challenge. In this paper, we describe the EU project MICO (Media in Context) which aims to provide the necessary technologies based on open-source software (OSS) core components

The Web Annotation Data Model proposes standardised RDF structures to form "Web Annotations". These annotations are used to express metadata information about digital resources and are designed to be shared, linked, tracked back, as well as searched and discovered across different peers. Although this is an expressive and rich way to create metadata, there exists a barrier for non-RDF and SPARQL experts to create and query such information. We propose Anno4j, a Java-based library, as a solution to this problem. The library supports an Object-RDF mapping that enables users to generate Web Annotations by creating plain old Java objects -concepts they are familiar with -while a path-based querying mechanism allows comprehensive information querying. Anno4j follows natural object-oriented idioms including inheritance, polymorphism, and composition to facilitate the development. While supporting the functionality of the Web Annotation Data Model, the library is implemented in a modular way, enabling developers to add enhancements and use case specific model alterations. Features like plugin functionality, transactions, and input/output methods further decrease the boundary for non-RDF experts.

Whereas the former Web mostly consisted of information represented in textual documents, nowadays the Web includes a huge number of multimedia documents like videos, photos, and audio. This enormous increase in volume in the private, and above all in the industry sector, makes it more and more di cult to find relevant information. Besides the pure management of multimedia documents, finding hidden semantics and interconnections of heterogeneous cross-media content is a crucial task and stays mostly untouched. To overcome this tendency we see the need for a generic cross-media analysis platform, ranging from extracting relevant features from media objects over representing and publishing extraction results to integrated querying of aggregated findings. In this paper we propose the underlying foundation for a common and contextual multimedia platform in terms of an unified model for publishing multimedia analysis results. The proposed model is based on existing ontologies, adapted and extended to the cross-media environment. Besides the introduction of the already mentioned platform and model, this paper also briefly introduces specific use-case applications as well as possibilities to query the persisted data.

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