Socially Enhanced Access to Digital Resources

  • 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.

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Author:Martin Memmel
Advisor:Andreas Dengel, Erik Duval
Document Type:Doctoral Thesis
Language of publication:English
Publication Date:2015/10/07
Year of Publication:2015
Publishing Institute:Technische Universität Kaiserslautern
Granting Institute:Technische Universität Kaiserslautern
Acceptance Date of the Thesis:2015/06/26
Date of the Publication (Server):2015/07/13
Tag:collective intelligence; crowdsourcing; information systems; long tail; metadata; social media
Number of page:XVI, 379
Faculties / Organisational entities:Kaiserslautern - Fachbereich Informatik
CCS-Classification (computer science):H. Information Systems / H.0 GENERAL
H. Information Systems / H.1 MODELS AND PRINCIPLES
DDC-Cassification:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):Standard gemäß KLUEDO-Leitlinien vom 13.02.2015