Relation Liftings on Preorders and Posets

The category Rel(Set) of sets and relations can be described as a category of spans and as the Kleisli category for the powerset monad. A set-functor can be lifted to a functor on Rel(Set) iff it preserves weak pullbacks. We show that these results extend to the enriched setting, if we replace sets by posets or preorders. Preservation of weak pullbacks becomes preservation of exact lax squares. As an application we present Moss's coalgebraic over posets

Semantic Web Reasoning by Swarm Intelligence

Abstract. Semantic Web reasoning systems are confronted with the task to process growing amounts of distributed, dynamic resources. This paper presents a novel way of approaching the challenge by RDF graph traversal, exploiting the advantages of swarm intelligence. The natureinspired and index-free methodology is realised by self-organising swarms of autonomous, light-weight entities that traverse RDF graphs by following paths, aiming to instantiate pattern-based inference rules. The method is evaluated on the basis of a series of simulation experiments with regard to desirable properties of Semantic Web reasoning, focussing on anytime behaviour, adaptiveness and scalability.

Rough Set Semantics for Identity on the Web

Identity relations are at the foundation of many logic-based knowledge representations. We argue that the traditional notion of equality, is unsuited for many realistic knowledge representation settings. The classical interpretation of equality is too strong when the equality statements are re-used outside their original context. On the Semantic Web, equality statements are used to interlink multiple descriptions of the same object, using owl:sameAs assertions. And indeed, many practical uses of owl:sameAs are known to violate the formal Leibniz-style semantics. We provide a more flexible semantics to identity by assigning meaning to the subrelations of an identity relation in terms of the predicates that are used in a knowledge-base. Using those indiscernability-predicates, we define upper and lower approximations of equality in the style of rought-set theory, resulting in a quality-measure for identity relations

CEDAR: The Dutch Historical Censuses as Linked Open Data

In this document we describe the CEDAR dataset, a five-star Linked Open Data representation of the Dutch historical censuses, conducted in the Netherlands once every 10 years from 1795 to 1971. We produce a linked dataset from a digitized sample of 2,288 tables. The dataset contains more than 6.8 million statistical observations about the demography, labour and housing of the Dutch society in the 18th, 19th and 20th centuries. The dataset is modeled using the RDF Data Cube vocabulary for multidimensional data, uses Open Annotation to express rules of data harmonization, and keeps track of the provenance of every single data point and its transformations using PROV. We link these observations to well known standard classification systems in social history, such as the Historical International Standard Classification of Occupations (HISCO) and the Amsterdamse Code (AC), which in turn link to DBpedia and GeoNames. The two main contributions of the dataset are the improvement of data integration and access for historical research, and the emergence of new historical data hubs, like classifications of historical religions and historical house types, in the Linked Open Data cloud

A web observatory for the machine processability of structured data on the web

General human intelligence is needed in order to process Linked Open Data (LOD). On the Semantic Web (SW), content is intended to be machine-processable as well. But the extent to which a machine is able to navigate, access, and process the SW has not been extensively researched. We present LOD Observer, a web observatory that studies the Web from a machine processor's point of view. We do this by reformulating the five star model of LOD publishing in quantifiable terms. Secondly, we built an infrastructure that allows the model's criteria to be quantified over existing datasets. Thirdly, we analyze a significant snapshot of the LOD cloud using this infrastructure and discuss the main problems a machine processor encounters