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IMSEM Seminar on Hot Topics in Information Management

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SoSe 2023 - WiSe 2023/24

English

IMSEM Seminar on Hot Topics in Information Management

3

Markl, Volker

Benotet

Portfolioprüfung

English

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34351500 FG Datenbanksysteme und Informationsmanagement (DIMA)

Keine Angabe

Kontakt


EN 7

Soto, Juan

sekr@dima.tu-berlin.de

https://www.tu.berlin/dima

Lernergebnisse

In this seminar, students will learn how to: (a) critically read and interpret scientific papers drawn from the data management, database systems, as well as technologies and systems for big data management and data science literature, (b) give a good scientific presentation that is technically precise, concentrated on the relevant topics, and also enjoyable, and (c) write a scientific survey based on papers drawn from varying sources, such as contemporary computer science journals and conference proceedings. In addition, students will learn about state-of-the art and current research topics in data management, database systems, as well as technologies and systems for big data management and data science.

Lehrinhalte

Students will initially be assigned a research paper (to be used as a primary source and a starting point). Students will then conduct their own literature search to identify related/supplementary materials (drawn from varying sources, such as books, conference proceedings, and journals). Representative sources, include conferences, such as VLDB, SIGMOD, ICDE, and CIDR as well as journals, such as the ACM Transactions on Database Systems, or the VLDB Journal. The set of “hot” research topics will be announced each term.

Modulbestandteile

Compulsory area

Die folgenden Veranstaltungen sind für das Modul obligatorisch:

LehrveranstaltungenArtNummerTurnusSpracheSWS ISIS VVZ
IMSEM - Seminar Hot Topics in Information ManagementSEM0434 L 476WiSe/SoSeKeine Angabe2
ISIS-Kurssuche nach Veranstaltungen des Moduls

Arbeitsaufwand und Leistungspunkte

IMSEM - Seminar Hot Topics in Information Management (SEM):

AufwandbeschreibungMultiplikatorStundenGesamt
Preparation/Individual Work15.04.0h60.0h
Plenary sessions15.02.0h30.0h
90.0h(~3 LP)
Der Aufwand des Moduls summiert sich zu 90.0 Stunden. Damit umfasst das Modul 3 Leistungspunkte.

Beschreibung der Lehr- und Lernformen

During the initial phase of this class, students will hear presentations on how to read scientific papers, how to give a good presentation, and how to write high-quality scientific/technical reports. You will also receive an initial paper as primary literature. Then you should find and use secondary sources to research your topic assigned to you in the seminar, which should go beyond the supplied primary literature. Next to conventional sources like the internet you are required to use research journals and articles published at important conferences in the areas of databases and information systems, big data and data science. You will deliver a presentation on your topic, followed by a discussion with all of the seminar participants. Details may vary and will be announced in the respective semester.

Voraussetzungen für die Teilnahme / Prüfung

Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen:

This course is aimed at third semester Master's students with a focus on database systems and information management. Desirable prerequisites include the following: (a) successfully completed the TU Berlin Database Technology (DBT) course or its equivalent, (b) at least one of the advanced information management courses, such as the Management of Data Streams or Data Management on Modern Hardware, (c) sound understanding of written and spoken English. Ideally, this seminar should be taken the semester before commencing your master's thesis.

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

100 Punkte insgesamt

Sprache(n)

English

Prüfungselemente

NamePunkteKategorieDauer/Umfang
(Deliverable Assessment) Seminar Presentation30mündlich20 min.
(Deliverable Assessment) Discussion of Seminar Content20mündlich5 min. per presentation
(Deliverable Assessment) Written Seminar Report50schriftlich15 pages

Notenschlüssel

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl1.01.31.72.02.32.73.03.33.74.0
100.0pt95.0pt90.0pt85.0pt80.0pt75.0pt70.0pt65.0pt60.0pt55.0pt50.0pt

Prüfungsbeschreibung (Abschluss des Moduls)

The exam will be done as a 'portfolio examination', see the information above for details. The final grade according to § 68 (2) AllgStuPO will be calculated with the faculty grading Table 2. (Die Gesamtnote gemäß § 68 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.)

Dauer des Moduls

Für Belegung und Abschluss des Moduls ist folgende Semesteranzahl veranschlagt:
1 Semester.

Dieses Modul kann in folgenden Semestern begonnen werden:
Winter- und Sommersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 8.

Anmeldeformalitäten

Students are required to register for the course in the official TUB examination system within six weeks after commencement of the first lecture or when the first graded assignment is due, whichever happens to be first.

Literaturhinweise, Skripte

Skript in Papierform

Verfügbarkeit:  nicht verfügbar

 

Skript in elektronischer Form

Verfügbarkeit:  nicht verfügbar

 

Literatur

Empfohlene Literatur
Seminar specific literature (hot topics ...) will be published in the first lecture.

Zugeordnete Studiengänge


Diese Modulversion wird in folgenden Studiengängen verwendet:

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Dieses Modul findet in keinem Studiengang Verwendung.
This course targets Master's students interested in data management, database systems, as well as technologies and systems for big data management and data science. This seminar is one of the eligible courses for those following the Fak. IV Data Science and Engineering Track: https://www.tu.berlin/en/dima/analytics/data-science-and-engineering-track.

Sonstiges

Keine Angabe