Martin Schäler

QuEval: beyond high-dimensional indexing à la carte

In the recent past, the amount of high-dimensional data, such as feature vectors extracted from multimedia data, increased dramatically. A large variety of indexes have been proposed to store and access such data efficiently. However, due to specific requirements of a certain use case, choosing an adequate index structure is a complex and time-consuming task. This may be due to engineering challenges or open research questions. To overcome this limitation, we present QuEval, an open-source framework that can be flexibly extended w.r.t. index structures, distance metrics, and data sets. QuEval provides a unified environment for a sound evaluation of different indexes, for instance, to support tuning of indexes. In an empirical evaluation, we show how to apply our framework, motivate benefits, and demonstrate analysis possibilities.

Reliable provenance information for multimedia data using invertible fragile watermarks

Today, more and more data is available in digital form, ranging from normal text to multimedia data such as image or video data. Since some data is of high sensitivity or undergoes legal restrictions, it is important to obtain more reliable information about the data origin and its transformations, known as data provenance. Unfortunately, current approaches for data provenance neither support multimedia data nor provide mechanisms to ensure reliability of the provenance information. In this paper, we present an approach based on existing watermarking schemes evaluated by a database system. Hence, this approach ensures the reliability of multi media data (e.g., fingerprint data) and its corresponding provenance information. Furthermore, we show how this approach can be applied within a specific database, used for fingerprint verification.

Building information system variants with tailored database schemas using features

Database schemas are an integral part of many information systems (IS). New software-engineering methods, such as software product lines, allow engineers to create a high number of different programs tailored to the customer needs from a common code base. Unfortunately, these engineering methods usually do not take the database schema into account. Particularly, a tailored client program requires a tailored database schema as well to form a consistent IS. In this paper, we show the challenges of tailoring relational database schemas in software product lines. Furthermore, we present an approach to treat the client and database part of an IS in the same way using a variable database schema. Additionally, we show the benefits and discuss disadvantages of the approach during the evolution of an industrial case study, covering a time span of more than a year.

Toward variability management to tailor high dimensional index implementations

The increasing amount of complex data requires a solution to store and query these data efficiently. One possibility to speed-up various query types is the application of high dimensional index structures. In prior work, we introduced QuEval as platform to evaluate these indexes for user-defined use cases. Our design allows to easily extend QuEval with new index structure implementations. However, based on our experiences, we encountered severe challenges by tailoring index structure implementations to specific use cases. In particular, we face challenges to manage several similar implementation variants of the same index. In this paper, we consequently show benefits and drawbacks that emphasize the necessity to tailor index structure implementations with the help of a short evaluation study. Finally, we outline approaches for adequate variability management to address the aforementioned drawbacks.

Database-centric chain-of-custody in biometric forensic systems

Biometric systems gain more and more attention in everyday life regarding authentication and surveillance of persons. This includes, amongst others, the login on a notebook based on fingerprint verification, controlling of airports or train stations, and the biometric identity card. Although these systems have several advantages in comparison to traditional approaches, they exhibit high risks regarding confidentiality and data protection issues. For instance, tampering biometric data or general misuse could have devastating consequences for the owner of the respective data. Furthermore, the digital nature of biometric data raises specific requirements for the usage of the data for crime detection or at court to convict a criminal. Here, the chain-of-custody has to be proven without any doubt. In this paper, we present a database-centric approach for ensuring the chain-ofcustody in a forensic digital fingerprint system.

Accelerating Multi-Column Selection Predicates in Main-Memory - The Elf Approach

Evaluating selection predicates is a data-intensive task that reduces intermediate results, which are the input for further operations. With analytical queries getting more and more complex, the number of evaluated selection predicates per query and table rises, too. This leads to numerous multicolumn selection predicates. Recent approaches to increase the performance of main-memory databases for selection-predicate evaluation aim at optimally exploiting the speed of the CPU by using accelerated scans. However, scanning each column one by one leaves tuning opportunities open that arise if all predicates are considered together. To this end, we introduce Elf, an index structure that is able to exploit the relation between several selection predicates. Elf features cache sensitivity, an optimized storage layout, fixed search paths, and slight data compression. In our evaluation, we compare its query performance to state-of the-art approaches and a sequential scan using SIMD capabilities. Our results indicate a clear superiority of our approach for multicolumn selection predicate queries with a low combined selectivity. For TPC-H queries with multi-column selection predicates, we achieve a speed-up between a factor of five and two orders of magnitude, mainly depending on the selectivity of the predicates.

Relational on demand data management for IT-services

Database systems are widely used in technical applications. However, it is difficult to decide which database management system fits best for a certain application. For many applications, different workload types often blend to mixed workloads that cause mixed requirements. The selection of an appropriate database management system is more critical for mixed workloads because classical domains with complementary requirements are combined, e.g., OLTP and OLAP. A definite decision for a database management system is not possible. Hybrid database system are developed to accept this challenge, i.e., these systems combine different storage approaches. However, a mutual optimization in hybrid systems is not available for mixed workloads. We develop a decision-support framework to provide application-performance estimation on a certain database management system on the one hand and to provide query optimization for hybrid database systems on the other hand. In this paper, we combine heuristics to a rule-based query optimization framework for hybrid relational database systems. That is, we aim on support for IT-services with volatile requirements. We evaluate the Aqua2 framework on standard database benchmarks. and show an acceleration of query execution on hybrid database systems.

Database and Data Management Requirements for Equalization of Contactless Acquired Traces for Forensic Purposes—Provenance and Performance

The importance of fingerprints and microtraces within the field of criminalistics and forensics is well-known. An upcoming field is the contactless acquisition of traces, because the integrity of traces is preserved Hildebrandt et al. (MM’Sec, pp. 1–8, 2011). A further issue from such an acquisition method is the potential presence of perspective distortions, which we already started to deal with in Kist et al. (SPIE 8546 Conf., pp. 0A/1–0A/12, 2012). Within the scope of a productive use of contactless acquisition methods, preprocessing steps like the equalization come along. In this paper, we give a perspective on requirements for an underlying database and database management system to support the methods of Kist et al. (SPIE 8546 Conf., pp. 0A/1–0A/12, 2012) as a potential real-case scenario. Thereby, we point out possible starting points for parallelization potential and evaluate the benefit. Finally, we integrate an approach to ensure the chain of custody by means of provenance, which is essential for any forensic investigation and evaluate the effect on the overall system performance.

BTW 2013 – Zwischen wissenschaftlicher Geschichte und moderner Herausforderung

Nach einer sehr gelungenen BTW 2011 in Kaiserslautern war die Messlatte sehr hoch gesteckt, um die 15. GIFachtagung Datenbanksysteme für Business, Technologie und Web (BTW) in der Otto-Stadt Magdeburg in SachsenAnhalt auf vergleichbar hohem Niveau durchzuführen. Dieser Herausforderung stellten sich Gunter Saake für die lokale Organisation und Volker Markl, der das Programmkomitee leitete. Die BTW 2013 fand vom 11. bis 15. März auf dem Campusgelände der Otto-von-Guericke-Universität in Magdeburg statt. Neben der BTW-Haupttagung wurden sechs Workshops und drei Tutorien sowie das etablierte BTW-Studierendenprogramm in den ersten beiden Tagen der Konferenzwoche durchgeführt. Zur Hauptkonferenz wurden dieses Mal 54 Beiträge eingereicht, von denen durch das Programmkomitee acht als Langbeiträge und zehn als Kurzbeiträge akzeptiert wurden. Außerdem wurden im Demoprogramm 22 Beiträge eingereicht, von denen 12 ausgewählt und live vor Ort präsentiert wurden. Im Industrieprogramm der BTW 2013 wurden die Ergebnisse von sieben Beiträgen vorgestellt.

A first proposal for a general description model of forensic traces

In recent years, the amount of digitally captured traces at crime scenes increased rapidly. There are various kinds of such traces, like pick marks on locks, latent fingerprints on various surfaces as well as different micro traces. Those traces are different from each other not only in kind but also in which information they provide. Every kind of trace has its own properties (e.g., minutiae for fingerprints, or raking traces for locks) but there are also large amounts of metadata which all traces have in common like location, time and other additional information in relation to crime scenes. For selected types of crime scene traces, type-specific databases already exist, such as the ViCLAS for sexual offences, the IBIS for ballistic forensics or the AFIS for fingerprints. These existing forensic databases strongly differ in the trace description models. For forensic experts it would be beneficial to work with only one database capable of handling all possible forensic traces acquired at a crime scene. This is especially the case when different kinds of traces are interrelated (e.g., fingerprints and ballistic marks on a bullet casing). Unfortunately, current research on interrelated traces as well as general forensic data models and structures is not mature enough to build such an encompassing forensic database. Nevertheless, recent advances in the field of contact-less scanning make it possible to acquire different kinds of traces with the same device. Therefore the data of these traces is structured similarly what simplifies the design of a general forensic data model for different kinds of traces. In this paper we introduce a first common description model for different forensic trace types. Furthermore, we apply for selected trace types from the well established database schema development process the phases of transferring expert knowledge in the corresponding forensic fields into an extendible, database-driven, generalised forensic description model. The trace types considered here are fingerprint traces, traces at locks, micro traces and ballistic traces. Based on these basic trace types, also combined traces (multiple or overlapped fingerprints, fingerprints on bullet casings, etc) and partial traces are considered.