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primarily to enable orchestration. Due to security measures, a browser application
should only communicate directly with one server (the domain currently displayed
in the browser). To enable the browser application to show contents originating
from different servers, the browser server needs to work as a mediator to establish
connections to the different servers.
The purpose of feed robots is to automatically provide content to the database,
which might be helpful for the users. Most importantly, when a user enters a search
query, a new page is created and in a simultaneous process, a feed robot is initiated;
this in turn calls the Google search API to feed the search results to the newly
created page.
Each object, which is added by the users, is attached to semantic metadata.
Currently, these are very simple semantic statements. The underlying technology
follows the semantic web stack. Uniform resource identifiers (URI) [
44
] provide a
technology to uniquely identify resources. They can be used to identify external
content and content that is used within the platform. The resource description
framework (RDF) [
90
] allows the modelling of basic statements about the identified
resources. This can be used to link different content, to give content meaning and to
store content in a structured way [
87
]. The integration of different content can be
facilitated using the web ontology language (OWL) [
89
] as defining integrating
ontologies has proven to be a good way to integrate heterogeneous data from
heterogeneous data sources [
80
,
95
]. We have used the Jena semantic web frame-
work to attach metadata to the data network.
The semantic metadata is provided as hierarchically organised RDF documents
on a web server. The metadata are linked to each other using the linked data
principles. The data can be easily retrieved and processed using SPARQL queries.
These can possibly enable different forms of social networking analysis but, so far,
this has not been investigated further in our prototype implementation.
Overall, as illustrated in Fig.
12.7
, our proposed conceptual architecture could
provide guidance for this implementation project directed towards youth-well-
being. The most distinguishing characteristic of our framework and architecture
is the social collaboration layer. In order to understand data that is distributed
among extremely loosely coupled databases by erratic conversations, it is essential
to provide databases which accommodate the special requirements of youth. We
have identified further requirements for youth-oriented community-driven data-
bases based on our explorative implementation: for instance, the need to support
composition and orchestration by allowing users to work with data networks.
12.11 Conclusion
Community-built databases have been established for diverse groups and commu-
nities. Well-known examples of this include the open-source community and the
Wikipedia community. With the emergence of Web 2.0 technologies and the
adaptation of community-driven web spaces by wider audiences, new issues
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