Large-Scale Storage and Reasoning for Semantic Data Using Swarms

Scalable, adaptive and robust approaches to store and analyze the massive amounts of data expected from Semantic Web applications are needed to bring the Web of Data to its full potential. The solution at hand is to distribute both data and requests onto multiple computers. Apart from storage, the annotation of data with machine-processable semantics is essential for realizing the vision of the Semantic Web. Reasoning on webscale data faces the same requirements as storage. Swarm-based approaches have been shown to produce near-optimal solutions for hard problems in a completely decentralized way. We propose a novel concept for reasoning within a fully distributed and self-organized storage system that is based on the collective behavior of swarm individuals and does not require any schema replication. We show the general feasibility and efficiency of our approach with a proof-of-concept experiment of storage and reasoning performance. Thereby, we positively answer the research question of whether swarm-based approaches are useful in creating a large-scale distributed storage and reasoning system. © 2012 IEEE

On Liability Insurance for Automobiles

Car owners are liable for property damage inflicted on other motorists. In most countries such liability must be insured by law. That law may favor expensive or heavy vehicles, prone to suffer or inflict large losses. This paper explores links between liability rules and vehicle choice. It presumes cooperative insurance, but non-cooperative acquisition of vehicles. Thus, the Nash equilibrium and its degree of efficiency depend on the liability regime

Light Extraction from Plasmonic Particles with Dielectric Shells and Overcoatings

We rigorously simulate light scattering via the FEM from core-shell plasmonic particles and plasmonic particles with an isolating overcoat, in order to recommend design principles for maximising plasmonic scattering gains

The impact of international outsourcing on individual employment security: A micro-level analysis

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Web

The Web of Linked Data grows rapidly and already contains data originating from hundreds of data sources. The quality of data from those sources is very diverse, as values may be out of date, incomplete or incorrect. Moreover, data sources may provide conflicting values for a single real-world object. In order for Linked Data applications to consume data from this global data space in an integrated fashion, a number of challenges have to be overcome. One of these challenges is to rate and to integrate data based on their quality. However, quality is a very subjective matter, and finding a canonic judgement that is suitable for each and every task is not feasible. To simplify the task of consuming high-quality data, we present Sieve, a framework for flexibly expressing quality assessment methods as well as fusion methods. Sieve is integrated into the Linked Data Integration Framework (LDIF), which handles Data Access, Schema Mapping and Identity Resolution, all crucial preliminaries for quality assessment and fusion. We demonstrate Sieve in a data integration scenario importing data from the English and Portuguese versions of DBpedia, and discuss how we increase completeness, conciseness and consistency through the use of our framework

A Tale of Two Paces

After decades of economic expansion, largely at the expense of environmental quality, new trends in environmental governance are taking shape in Asia. This paper analyses these developments in China, India, Vietnam and Indonesia. It finds that environmental governance within a “traditional” agenda of environmental protection remains severely hampered by capacity constraints. Simultaneously, all four countries have embarked on ambitious policy initiatives to address climate change and promote clean technologies, signaling an important shift in national priorities. The paper discusses possible implications of these trends, sketching possible scenarios for the further development of environmental governance

Tverberg plus constraints

Many of the strengthenings and extensions of the topological Tverberg theorem can be derived with surprising ease directly from the original theorem: For this we introduce a proof technique that combines a concept of "Tverberg unavoidable subcomplexes" with the observation that Tverberg points that equalize the distance from such a subcomplex can be obtained from maps to an extended target space. Thus we obtain simple proofs for many variants of the topological Tverberg theorem, such as the colored Tverberg theorem of Zivaljevic and Vrecica (1992). We also get a new strengthened version of the generalized van Kampen-Flores theorem by Sarkaria (1991) and Volovikov (1996), an affine version of their "j-wise disjoint" Tverberg theorem, and a topological version of Soberon's (2013) result on Tverberg points with equal barycentric coordinates.Comment: 15 pages; revised version, accepted for publication in Bulletin London Math. Societ

Validation and Evaluation

In this technical report, we present prototypical implementations of innovative tools and methods for personalized and contextualized (multimedia) search, collaborative ontology evolution, ontology evaluation and cost models, and dynamic access and trends in distributed (semantic) knowledge, developed according to the working plan outlined in Technical Report TR-B-12-04. The prototypes complete the next milestone on the path to an integral Corporate Semantic Web architecture based on the three pillars Corporate Ontology Engineering, Corporate Semantic Collaboration, and Corporate Semantic Search, as envisioned in TR-B-08-09