Popular education and the digital citizen: a genealogical analysis

This paper historicises and problematises the concept of the digital citizen and how it is constructed in Sweden today. Specifically, it examines the role of popular education in such an entanglement. It makes use of a genealogical analysis to produce a critical ‘history of the present’ by mapping out the debates and controversies around the emergence of the digital citizen in the 1970s and 1980s, and following to its manifestations in contemporary debates. This article argues that free and voluntary adult education (popular education) is and has been fundamental in efforts to construe the digital citizen. A central argument of the paper is that popular education aiming for digital inclusion is not a 21st century phenomenon; it actually commenced in the 1970s. However, this digitisation of citizens has also changed focus dramatically since the 1970s. During the 1970s, computers and computerisation were described as disconcerting, and as requiring popular education in order to counter the risk of the technology “running wild”. In current discourses, digitalisation is constructed in a non-ideological and post-political way. These post-political tendencies of today can be referred to as a post-digital present where computers have become so ordinary, domesticized and ubiquitous in everyday life that they are thereby also beyond criticism. (DIPF/Orig.

How do Ontology Mappings Change in the Life Sciences?

Mappings between related ontologies are increasingly used to support data integration and analysis tasks. Changes in the ontologies also require the adaptation of ontology mappings. So far the evolution of ontology mappings has received little attention albeit ontologies change continuously especially in the life sciences. We therefore analyze how mappings between popular life science ontologies evolve for different match algorithms. We also evaluate which semantic ontology changes primarily affect the mappings. We further investigate alternatives to predict or estimate the degree of future mapping changes based on previous ontology and mapping transitions.Comment: Keywords: mapping evolution, ontology matching, ontology evolutio

Latent Heat Fluxes over Complex Terrain from Airborne Water Vapour and Wind Lidars

Tropospheric profiles of water vapour and wind were measured with a differential absorption lidar (DIAL) and a heterodyne detection Doppler wind lidar collo-cated onboard the DLR Falcon research aircraft in the past two years. The DIAL is a newly developed four-wavelength system operating on three water vapour absorption lines of different strengths, one offline wavelength at 935 nm (each 50 Hz, 40 mJ), and 532 and 1064 nm for aerosol profiling. It is designed as an airborne demonstrator for a possible future space-borne water vapour lidar mission. It operated success-fully during the Convective and Orographically-induced Precipitation Study (COPS) in July 2007 over the Black Forest Mountains in southern Germany, and during the Norwegian THORPEX-IPY field experiment in March 2008 over the European North Sea. For the study of summertime convection initiation over complex terrain and the development of Polar Lows in the North Sea both campaigns included latent heat flux missions where both airborne lidars were pointed nadir-viewing. Using eddy-correlation of the remotely-sensed wind and water vapour fluctuations, a repre-sentative flux profile can be obtained from a single over-flight of the area under investigation. The lidars’ spatial resolution is ~200 m which resolves the domi-nant circulation and flux patterns in a convective boundary layer. This novel instrumentation allows ob-taining profiles of the latent heat flux beneath the air-craft from one single over-flight of any area of interest

Citation analysis of database publications

We analyze citation frequencies for two main database conferences (SIGMOD, VLDB) and three database journals (TODS, VLDB Journal, Sigmod Record) over 10 years. The citation data is obtained by integrating and cleaning data from DBLP and Google Scholar. Our analysis considers different comparative metrics per publication venue, in particular the total and average number of citations as well as the impact factor which has so far only been considered for journals. We also determine the most cited papers, authors, author institutions and their countries

AWESOME: A Data Warehouse-based System for Adaptive Website Recommentations

Recommendations are crucial for the success of large websites. While there are many ways to de-termine recommendations, the relative quality of these recommenders depends on many factors and is largely unknown. We propose a new clas-sification of recommenders and comparatively evaluate their relative quality for a sample web-site. The evaluation is performed with AWESOME (Adaptive website recommenda-tions), a new data warehouse-based recommen-dation system capturing and evaluating user feedback on presented recommendations. More-over, we show how AWESOME performs an automatic and adaptive closed-loop website op-timization by dynamically selecting the most promising recommenders based on continuously measured recommendation feedback. We pro-pose and evaluate several alternatives for dy-namic recommender selection including a power-ful machine learning approach

Instance-Based Matching of Large Life Science Ontologies

Ontologies are heavily used in life sciences so that there is increasing value to match different ontologies in order to determine related conceptual categories. We propose a simple yet powerful methodology for instance-based ontology matching which utilizes the associations between molecular-biological objects and ontologies. The approach can build on many existing ontology associations for instance objects like sequences and proteins and thus makes heavy use of available domain knowledge. Furthermore, the approach is flexible and extensible since each instance source with associations to the ontologies of interest can contribute to the ontology mapping. We study several approaches to determine the instance-based similarity of ontology categories. We perform an extensive experimental evaluation to use protein associations for different species to match between subontologies of the Gene Ontology and OMIM. We also provide a comparison with metadata-based ontology matching

Dynamic Fusion of Web Data

Mashups exemplify a workflow-like approach to dynamically integrate data and services from multiple web sources. Such integration workflows can build on existing services for web search, entity search, database querying, and information extraction and thus complement other data integration approaches. A key challenge is the efficient execution of integration workflows and their query and matching steps at runtime. We relate mashup data integration with other approaches, list major challenges, and outline features of a first prototype design

Airborne Coherent Doppler Wind Lidar measurements of vertical and horizontal wind speeds for the investigation of gravity waves

Gravity waves are well known phenomena in the atmosphere, but there is still a lack of knowledge of their life cycle including excitation, propagation and dissipation mechanisms. In order to investigate these topics, DLR’s coherent Doppler wind lidar system was recently deployed during 3 airborne campaigns on the Falcon F20 research aircraft, namely the GW-LCYCLE I campaign (Kiruna, Sweden, December 2013), the DEEPWAVE campaign (Christchurch, New Zealand, June/July 2014) and the GW-LCYCLE II campaign (Kiruna, Sweden, January/February 2016). In this paper, a case study based on a research flight performed during GW-LCYCLE I is discussed and a method for correcting horizontal wind contribution in the vertical wind retrieval based on ECMWF data is introduced. The remaining systematic error of the retrieved vertical wind is estimated to be less than 10 cm/s. A measurement of a flight leg across the Scandinavian mountain ridge is used to characterize gravity waves during strong forcing conditions. The measured vertical wind reaches amplitudes of larger than ± 3 m/s and horizontal wavelengths of 10 km to 20 km. A comparison with WRF-model calculations shows a quite good representation of the horizontal structure of the vertical wind. The amplitude however is obviously underestimated by a factor of 2 and shows maximum wind speeds of ± 1.5 m/s

MOMA - A Mapping-based Object Matching System

Object matching or object consolidation is a crucial task for data integration and data cleaning. It addresses the problem of identifying object instances in data sources referring to the same real world entity. We propose a flexible framework called MOMA for mapping-based object matching. It allows the construction of matchworkflows combining the results of several matcher algorithms on both attribute values and contextual information. The output of a match task is an instance-level mapping that supports information fusion in P2P data integration systems and can be re-used for other match tasks. MOMA utilizes further semantic mappings of different cardinalities and provides merge and compose operators for mapping combination. We propose and evaluate several strategies for both object matching between different sources as well as for duplicate identification within a single data source