@article{OpelNetzerDesel2023,
  author    = {Opel, Simone and Netzer, Cajus Marian and Desel, J{\"o}rg},
  title     = {Adaption von Lernwegen in adaptierten Lehrmaterialien f{\"u}r Studierende mit Berufsausbildungsabschluss},
  series = {Hochschuldidaktik Informatik HDI 2021 (Commentarii informaticae didacticae)},
  journal   = {Hochschuldidaktik Informatik HDI 2021 (Commentarii informaticae didacticae)},
  number    = {13},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-548-4},
  issn      = {1868-0844},
  doi       = {10.25932/publishup-61418},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-614188},
  pages     = {91 -- 114},
  year      = {2023},
  abstract  = {Obwohl immer mehr Menschen nicht direkt ein Studium aufnehmen, sondern zuvor eine berufliche Ausbildung absolvieren, werden die in der Ausbildung erworbenen Kompetenzen von den Hochschulen inhaltlich und didaktisch meist ignoriert. Ein Ansatz, diese Kompetenzen zu w{\"u}rdigen, ist die formale Anrechnung von mitgebrachten Kompetenzen als (f{\"u}r den Studienabschluss erforderliche) Leistungspunkte. Eine andere Variante ist der Einsatz von speziell f{\"u}r die Zielgruppe der Studierenden mit Vorkenntnissen adaptiertem Lehr-Lernmaterial. Um dar{\"u}ber hinaus individuelle Unterschiede zu ber{\"u}cksichtigen, erlaubt eine weitere Adaption individueller Lernpfade den Lernenden, genau die jeweils fehlenden Kompetenzen zu erwerben. In diesem Beitrag stellen wir die exemplarische Entwicklung derartigen Materials anhand des Kurses „Datenbanken" f{\"u}r die Zielgruppe der Studierenden mit einer abgeschlossenen Ausbildung zum Fachinformatiker bzw. zur Fachinformatikerin vor.},
  language  = {de}
}
@phdthesis{Dreseler2022,
  author    = {Dreseler, Markus},
  title     = {Automatic tiering for in-memory database systems},
  doi       = {10.25932/publishup-55825},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-558253},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 143},
  year      = {2022},
  abstract  = {A decade ago, it became feasible to store multi-terabyte databases in main memory. These in-memory databases (IMDBs) profit from DRAM's low latency and high throughput as well as from the removal of costly abstractions used in disk-based systems, such as the buffer cache. However, as the DRAM technology approaches physical limits, scaling these databases becomes difficult. Non-volatile memory (NVM) addresses this challenge. This new type of memory is persistent, has more capacity than DRAM (4x), and does not suffer from its density-inhibiting limitations. Yet, as NVM has a higher latency (5-15x) and a lower throughput (0.35x), it cannot fully replace DRAM. IMDBs thus need to navigate the trade-off between the two memory tiers. We present a solution to this optimization problem. Leveraging information about access frequencies and patterns, our solution utilizes NVM's additional capacity while minimizing the associated access costs. Unlike buffer cache-based implementations, our tiering abstraction does not add any costs when reading data from DRAM. As such, it can act as a drop-in replacement for existing IMDBs. Our contributions are as follows: (1) As the foundation for our research, we present Hyrise, an open-source, columnar IMDB that we re-engineered and re-wrote from scratch. Hyrise enables realistic end-to-end benchmarks of SQL workloads and offers query performance which is competitive with other research and commercial systems. At the same time, Hyrise is easy to understand and modify as repeatedly demonstrated by its uses in research and teaching. (2) We present a novel memory management framework for different memory and storage tiers. By encapsulating the allocation and access methods of these tiers, we enable existing data structures to be stored on different tiers with no modifications to their implementation. Besides DRAM and NVM, we also support and evaluate SSDs and have made provisions for upcoming technologies such as disaggregated memory. (3) To identify the parts of the data that can be moved to (s)lower tiers with little performance impact, we present a tracking method that identifies access skew both in the row and column dimensions and that detects patterns within consecutive accesses. Unlike existing methods that have substantial associated costs, our access counters exhibit no identifiable overhead in standard benchmarks despite their increased accuracy. (4) Finally, we introduce a tiering algorithm that optimizes the data placement for a given memory budget. In the TPC-H benchmark, this allows us to move 90\% of the data to NVM while the throughput is reduced by only 10.8\% and the query latency is increased by 11.6\%. With this, we outperform approaches that ignore the workload's access skew and access patterns and increase the query latency by 20\% or more. Individually, our contributions provide novel approaches to current challenges in systems engineering and database research. Combining them allows IMDBs to scale past the limits of DRAM while continuing to profit from the benefits of in-memory computing.},
  language  = {en}
}
@phdthesis{Lange2013,
  author    = {Lange, Dustin},
  title     = {Effective and efficient similarity search in databases},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-65712},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {Given a large set of records in a database and a query record, similarity search aims to find all records sufficiently similar to the query record. To solve this problem, two main aspects need to be considered: First, to perform effective search, the set of relevant records is defined using a similarity measure. Second, an efficient access method is to be found that performs only few database accesses and comparisons using the similarity measure. This thesis solves both aspects with an emphasis on the latter. In the first part of this thesis, a frequency-aware similarity measure is introduced. Compared record pairs are partitioned according to frequencies of attribute values. For each partition, a different similarity measure is created: machine learning techniques combine a set of base similarity measures into an overall similarity measure. After that, a similarity index for string attributes is proposed, the State Set Index (SSI), which is based on a trie (prefix tree) that is interpreted as a nondeterministic finite automaton. For processing range queries, the notion of query plans is introduced in this thesis to describe which similarity indexes to access and which thresholds to apply. The query result should be as complete as possible under some cost threshold. Two query planning variants are introduced: (1) Static planning selects a plan at compile time that is used for all queries. (2) Query-specific planning selects a different plan for each query. For answering top-k queries, the Bulk Sorted Access Algorithm (BSA) is introduced, which retrieves large chunks of records from the similarity indexes using fixed thresholds, and which focuses its efforts on records that are ranked high in more than one attribute and thus promising candidates. The described components form a complete similarity search system. Based on prototypical implementations, this thesis shows comparative evaluation results for all proposed approaches on different real-world data sets, one of which is a large person data set from a German credit rating agency.},
  language  = {en}
}
@misc{DegkwitzAndermann2003,
  author    = {Degkwitz, Andreas and Andermann, Heike},
  title     = {Angebots-, Nutzungs- und Bezugsstrukturen elektronischer Fachinformation in Deutschland},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-672},
  year      = {2003},
  abstract  = {Mit dem {\"U}bergang zum digitalen Medium haben sich die Bezugsstrukturen und das Angebot an elektronischer Fachinformation in den Bibliotheken nachhaltig ver{\"a}ndert. In den vorliegenden Untersuchungen wird das Angebot elektronischer Zeitschriften und Datenbanken und die Nutzung elektronischer Zeitschriften in f{\"u}nf ausgew{\"a}hlten Fachgebieten und in unterschiedlichen Bibliothekstypen dargelegt. Dar{\"u}ber hinaus werden die derzeitigen Bezugsstrukturen beschrieben sowie die Ergebnisse einer Befragung der Konsortien zu Zielsetzungen, Vertragsformen und Gesch{\"a}ftsmodellen dargestellt. Chancen und Risiken der konsortialen Bezugsform werden er{\"o}rtert.},
  language  = {de}
}