132 research outputs found
The social in the platform trap: Why a microscopic system focus limits the prospect of social machines
“Filter bubble”, “echo chambers”, “information diet” – the metaphors to describe today’s information dynamics on social media platforms are fairly diverse. People use them to describe the impact of the viral spread of fake, biased or purposeless content online, as witnessed during the recent race for the US presidency or the latest outbreak of the Ebola virus (in the latter case a tasteless racist meme was drowning out any meaningful content). This unravels the potential envisioned to arise from emergent activities of human collectives on the World Wide Web, as exemplified by the Arab Spring mass movements or digital disaster response supported by the Ushahidi tool suite
Understanding personal data as a space - learning from dataspaces to create linked personal data
In this paper we argue that the space of personal data is a dataspace as defined by Franklin et al. We define a personal dataspace, as the space of all personal data belonging to a user, and we describe the logical components of the dataspace. We describe a Personal Dataspace Support Platform (PDSP) as a set of services to provide a unified view over the user’s data, and to enable new and more complex workflows over it. We show the differences from a DSSP to a PDSP, and how the latter can be realized using Web protocols and Linked APIs.<br/
On the topology of the web of data
The Web of Data consists of the open accessible structured data on the Web. This includes the evolving number of Linked Open Data data sets but also the structured data which is embedded in Web pages. In this paper we address questions related to a unified definition of distinct data sets and factors that influence different network representations of structured Web data. The contributions are (1) an algorithm to generate a data set linking structure of the em- bedded structured data sourcing from (a) the Billion Triples Challenge corpus (b) the Web Data Commons corpus, and (c) the sindice crawl, (2) a discussion on the issue of identifying distinct data sets in a generic fashion, and (3) a high level visual abstraction of the current Web of Data topology
On the topology of the web of data
The Web of Data consists of the open accessible structured data on the Web. This includes the evolving number of Linked Open Data data sets but also the structured data which is embedded in Web pages. In this paper we address questions related to a unified definition of distinct data sets and factors that influence different network representations of structured Web data. The contributions are (1) an algorithm to generate a data set linking structure of the em- bedded structured data sourcing from (a) the Billion Triples Challenge corpus (b) the Web Data Commons corpus, and (c) the sindice crawl, (2) a discussion on the issue of identifying distinct data sets in a generic fashion, and (3) a high level visual abstraction of the current Web of Data topology
a survey
Building ontologies in a collaborative and increasingly community-driven
fashion has become a central paradigm of modern ontology engineering. This
understanding of ontologies and ontology engineering processes is the result
of intensive theoretical and empirical research within the Semantic Web
community, supported by technology developments such as Web 2.0. Over 6 years
after the publication of the first methodology for collaborative ontology
engineering, it is generally acknowledged that, in order to be useful, but
also economically feasible, ontologies should be developed and maintained in a
community-driven manner, with the help of fully-fledged environments providing
dedicated support for collaboration and user participation. Wikis, and similar
communication and collaboration platforms enabling ontology stakeholders to
exchange ideas and discuss modeling decisions are probably the most important
technological components of such environments. In addition, process-driven
methodologies assist the ontology engineering team throughout the ontology
life cycle, and provide empirically grounded best practices and guidelines for
optimizing ontology development results in real-world projects. The goal of
this article is to analyze the state of the art in the field of collaborative
ontology engineering. We will survey several of the most outstanding
methodologies, methods and techniques that have emerged in the last years, and
present the most popular development environments, which can be utilized to
carry out, or facilitate specific activities within the methodologies. A
discussion of the open issues identified concludes the survey and provides a
roadmap for future research and development in this lively and promising
field
From coincidence to purposeful flow? properties of transcendental information cascades
In this paper, we investigate a method for constructing cascades of information co-occurrence, which is suitable to trace emergent structures in information in scenarios where rich contextual features are unavailable. Our method relies only on the temporal order of content-sharing activities, and intrinsic properties of the shared content itself. We apply this method to analyse information dissemination patterns across the active online citizen science project Planet Hunters, a part of the Zooniverse platform. Our results lend insight into both structural and informational properties of different types of identifiers that can be used and combined to construct cascades. In particular, significant differences are found in the structural properties of information cascades when hashtags as used as cascade identifiers, compared with other content features. We also explain apparent local information losses in cascades in terms of information obsolescence and cascade divergence; e.g., when a cascade branches into multiple, divergent cascades with combined capacity equal to the original
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