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- ZeitschriftenartikelProf. Dr. Dr. h. c. Hans-Jürgen Appelrath(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Härder, Theo
- ZeitschriftenartikelToward a Visual Analytics Approach to Support Multi-Sensor Analysis in Remote Sensing Science(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Sips, Mike; Köthur, Patrick; Eggert, DanielMulti-sensor analysis is a novel scientific approach in remote sensing science. The basic idea is to enable users to combine various satellite mission data (called scenes) into a common data set. This combination produces millions of high-resolution time series (one time series for each pixel) from which users want to extract potentially interesting spatio-temporal patterns. A challenge of multi-sensor analysis is that users often experience difficulties interpreting the extracted patterns. We use Visual Analytics (VA) to help users understand these patterns. We learned from our interdisciplinary cooperation in the GeoMultiSens project that VA has to support the assessment and selection of scenes suitable for the current application scenario and question to achieve this goal. The contribution of this paper is twofold. First, we describe how we devised a VA approach that supports users in the assessment and selection of remote sensing data based on a user and task analysis. We demonstrate how our VA approach helps users to select and assess scenes to study forest cover change in Europe between 2010 and 2016. The study of forest cover change is an important scientific scenario because the loss of forest cover has negative effects on the environment, such as undermining the capacity of ecosystems to maintain fresh water, loosing the ability to regulate the climate, and poorer air quality. Second, we discuss the Scientific Data Explorer, our research vision for VA to enable users to effectively develop VA approaches for a variety of scientific scenarios.
- ZeitschriftenartikelEditorial(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Seeger, Bernhard; König-Ries, Birgitta; Härder, Theo
- ZeitschriftenartikelA Terminology Service Supporting Semantic Annotation, Integration, Discovery and Analysis of Interdisciplinary Research Data(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Karam, Naouel; Müller-Birn, Claudia; Gleisberg, Maren; Fichtmüller, David; Tolksdorf, Robert; Güntsch, AntonResearch has become more data-intensive over the last few decades. Sharing research data is often a challenge, especially for interdisciplinary collaborative projects. One primary goal of a research infrastructure for data management should be to enable efficient data discovery and integration of heterogeneous data. In order to enable such interoperability, a lot of effort has been undertaken by scientists to develop standards and characterize their domain knowledge in the form of taxonomies and formal ontologies. However, these knowledge models are often disconnected and distributed. The work presented here provides a promising approach for integrating and harmonizing terminological resources to serve as a backbone for a platform. The component developed, called the GFBio Terminology Service, acts as a semantic platform for access, development and reasoning over internally and externally maintained terminological resources within the biological and environmental domain. We highlight the utility of the Terminology Service by practical use cases of semantically enhanced components. We show how the Terminology Service enables applications to add meaning to their data by giving access to the knowledge that can be derived from the terminologies and data annotated by them.
- ZeitschriftenartikelSkyline Queries(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Hose, KatjaMany applications face the problem that users are overwhelmed by the large amount of available data. In some cases an objective ranking function can be used to order data items by their relevance – similar to the top 10 results displayed by a Web search engine. Other applications, however, aim at considering more diverse preferences and multiple criteria to help users find good results. Such applications can benefit from skyline queries.The best known example use case for a skyline query is a hotel booking scenario where users are looking for hotels. Assume many hotels are available and the user wants to find one based on two criteria: distance to the beach and price per night. Further assume that the user is unable to say which of these criteria is more important. So, we need to look for hotels representing a good combination of both criteria. The skyline consists of all hotels that represent a “good” combinations of both criteria. For each of the other hotels, there is always at least one hotel in the skyline that is better with respect to the two criteria. So, being presented the skyline, the user gets an overview of the available hotels and can make the final decision with respect to her personal preferences for the two criteria. No matter how the user will eventually weigh her personal preferences, she will find her favorite hotel in the skyline.This article gives a short introduction to skyline queries, their main characteristics, and basic ways of processing them.
- ZeitschriftenartikelDissertationen(Datenbank-Spektrum: Vol. 16, No. 3, 2016)
- ZeitschriftenartikelDie Arbeitsgruppen für Datenbanken und Informationssysteme an der TU Kaiserslautern(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Deßloch, Stefan; Härder, Theo; Michel, SebastianIn diesem Beitrag geben wir einen Überblick über die Forschungsprojekte im Bereich Datenbanken und Informationssysteme (DBIS), die in den letzten Jahren an der TU Kaiserslautern durchgeführt wurden, bevor wir unsere aktuellen Forschungsthemen skizzieren. Desweiteren beschreiben wir unsere DBIS-bezogenen Lehraufgaben für das Bachelor- und Master-Studium, die im Lehrgebiet Informationssysteme des Fachbereichs Informatik angeboten werden.
- ZeitschriftenartikelSpeeding up Privacy Preserving Record Linkage for Metric Space Similarity Measures(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Sehili, Ziad; Rahm, ErhardThe analysis of person-related data in Big Data applications faces the tradeoff of finding useful results while preserving a high degree of privacy. This is especially challenging when person-related data from multiple sources need to be integrated and analyzed. Privacy-preserving record linkage (PPRL) addresses this problem by encoding sensitive attribute values such that the identification of persons is prevented but records can still be matched. In this paper we study how to improve the efficiency and scalability of PPRL by restricting the search space for matching encoded records. We focus on similarity measures for metric spaces and investigate the use of M‑trees as well as pivot-based solutions. Our evaluation shows that the new schemes outperform previous filter approaches by an order of magnitude.
- ZeitschriftenartikelNews(Datenbank-Spektrum: Vol. 16, No. 3, 2016)
- ZeitschriftenartikelSupporting Situation Awareness in Spatio-Temporal Databases(Datenbank-Spektrum: Vol. 16, No. 3, 2016) Behrend, Andreas; Schmiegelt, Philip; Dohr, AndreasSituation awareness refers to the capability of systems to perceive an existing or predicted context that determines the values of variables in a changing environment. Despite the enhanced support for managing temporal data, current database systems still lack mechanisms for handling highly dynamic situations in which data may change frequently. We present first results from an ongoing research project investigating these missing database features. In particular, we identify (i) the requirements for representing complex spatio-temporal data, (ii) the reasoning capabilities needed for detecting valid relationships between situations, and (iii) the operators necessary for supporting situation-based reasoning. Our investigations are based on a new perception concept, which comprises interval timestamped data derived from observed events and processed using the sequenced semantics. Perceptions provide a high level (and qualitative) description of past and current situations, complemented by projections into the future.