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

Archetypes in OWL, fake archetyped patient data and indicators formalised as SPARQL queries

<p>This dataset contains some ontologized openEHR archetypes in OWL. The translation has been done with a slightly adapted version of the archetype ontologizer, which bases the output ontologies on the OpenEHR Specific Data Structures and Data Types Ontology.</p> <p>These ontologies have been merged and used for fake patient data (100,000 patients; ca. 700 MB). Finally, the dataset contains formalized numerators and denominators of indicators (as SPARQL queries). The data underlies our paper "Semantic Integration of Patient Data and Quality Indicators Based on openEHR Archetypes". </p

Formalised quality indicator and fake patient data

<p>Indicator formalised by 8 students and fake patient data (schema might have changed a little) accompanying our paper "The Reproducibility of CLIF, a Method for Clinical Quality Indicator Formalisation". The application to formalise indicators is on github. </p

Dutch colorectal cancer quality indicators formalised in SPARQL, together with fake patient data to compute them on

<p>These are the formalised indicator and the data underlying the paper "Towards the Automated Calculation of Clinical Quality Indicators". </p

Computing for the Semantic Web

Abstract The success of the Semantic Web, with the ever increasing publication of machine readable semantically rich data on the Web, has started to create serious problems as the scale and complexity of information outgrows the current methods in use, which are mostly based on database technology, expressive knowledge representation formalism and high-performance computing. We argue that methods from computational intelligence (CI) can play an important role in solving these problems. In this paper we introduce and systemically discuss the typical application problems on the Semantic Web and discuss CI alternative to address the limitations of their underlying reasoning tasks consistently with respect to the increasing size, dynamicity and complexity of the data. Finally, we discuss two case studies in which we successfully applied soft computing methods to two of the main reasoning tasks; an evolutionary approach to querying, and a swarm algorithm for entailment. This short paper is a summary of Guéret, C.; Schlobach, S.; Dentler, K.; Schut, M.; Eiben, G. &quot;Evolutionary and Swar

Barriers to the reuse of routinely recorded clinical data: a field report

Today, clinical data is routinely recorded in vast amounts, but its reuse can be challenging. A secondary use that should ideally be based on previously collected clinical data is the computation of clinical quality indicators. In the present study, we attempted to retrieve all data from our hospital that is required to compute a set of quality indicators in the domain of colorectal cancer surgery. We categorised the barriers that we encountered in the scope of this project according to an existing framework, and provide recommendations on how to prevent or surmount these barriers. Assuming that our case is not unique, these recommendations might be applicable for the design, evaluation and optimisation of Electronic Health Records

REGIONAL DIFFERENCES BETWEEN JOB SEEKERS: CASE OF LATVIA

Differences in labour market have always been on great importance in Latvia, however special concern is about regions of Latvia where finding a new job sometimes could be very challenging process, because these regions are developing unevenly, job vacancies are limited, wages are lower and there is a lack of high qualified specialists in labour market. Purpose of the study is to analyse regional differences between job seekers in regions in Latvia. The tasks of the study: 1) To analyse theoretical background of regional differences of job seekers and employment in context of urban and rural areas; 2) To analyse main challenges and problems of regional differences between job seekers in regions in Latvia. Research methods used in preparation of the paper were the analysis of scientific publications and previous conducted research results, the analysis of Labour Force Survey results and the analysis of data of Central Statistical Bureau of Latvia. The Survey results are analysed using indicators of descriptive statistics (indicators of central tendency or location - arithmetic mean, mode, median), indicators of variability (indicators of dispersion - range, standard deviation and standard error of mean), cross-tabulation for regions of Latvia, for territories: urban-rural living and analysis of variance - ANOVA are used. The results of analysis have indicated several differences between regions of Latvia, but there are no differences between job seekers in urban and rural areas of Latvia.The research was supported by the NATIONAL RESEARCH PROGRAMME “LATVIAN HERITAGE AND FUTURE CHALLENGES FOR THE SUSTAINABILITY OF THE STATE” project “CHALLENGES FOR THE LATVIAN STATE AND SOCIETY AND THE SOLUTIONS IN INTERNATIONAL CONTEXT" (INTERFRAME-LV, Project No.VPP-IZM-2018/1-0005)