In the digital era we live in, users can access an abundance of digital resources in their daily life. These digital resources can be located on the user's devices, in traditional repositories such as intranets or digital libraries, but also in open environments such as the World Wide Web.
To be able to efficiently work with this abundance of information, users need support to get access to the resources that are relevant to them. Access to digital resources can be supported in various ways. Whether we talk about technologies for browsing, searching, filtering, ranking, or recommending resources: what they all have in common is that they depend on the available information (i.e., resources and metadata). The accessibility of digital resources that meet a user's information need, and the existence and quality of metadata is crucial for the success of any information system.
This work focuses on how social media technologies can support the access to digital resources. In contrast to closed and controlled environments where only selected users have the rights to contribute digital resources and metadata, and where this contribution involves a social process of formal agreement of the relevant stakeholders, potentially any user can easily create and provide information in social media environments. This usually leads to a larger variety of resources and metadata, and allows for dynamics that would otherwise hardly be possible.
Most information systems still mainly rely on traditional top-down approaches where only selected stakeholders can contribute information. The main idea of this thesis is an approach that allows for introducing the characteristics of social media environments in such traditional contexts. The requirements for such an approach are being examined, as well as the benefits and potentials it can provide.
The ALOE infrastructure was developed according to the identified requirements and realises a Social Resource and Metadata Hub. Case studies and evaluation results are provided to show the impact of the approach on the user's behaviours and the creation of digital resources and metadata, and to justify the presented approach.
If an automated system is tasked to provide services such as search or clustering of information on an information repository, the quality of the output depends a lot on the information that is available to the system in machine-readable form. Simple text, for example, is machine-readable only in a very limited sense. Advanced services typically need to derive other representations of the text (e.g., sets of keywords) as input for their core algorithms. Some services might need information that cannot be derived from the resource in question alone, but is available as separate metadata only, such as usage information. Annotations can be used to carry this information.
This thesis focuses on so-called ontology-based annotations. In contrast to other forms of annotations such as Tags (arbitrary strings that users can assign to resources), ontology-based annotations conform to a predefined data structure and class hierarchy. An advantage of this approach is that rich information can be stored in a well-structured way in the annotations; a drawback is that users need to be familiar with the hierarchy and other design decisions of the underlying ontology used for annotations.
Two scenarios are considered in this thesis:
First, a document-based scenario in which text annotations are used to represent both information about the text content and usage and user context information in a multi-user setting with mostly objective annotation criteria; second, a resource-based scenario whose annotation model focuses on multi-user settings with subjective annotation criteria, using (dis-)similarities in user annotations to derive user similarity metrics, and building personalized views from this information.
Finally, the prototypical systems that have been developed throughout this thesis get evaluated, proving the concepts presented in this thesis.