Moses - Semantic Web and Linked Data

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum SS 2017 - SS 2017.

Module / Version:
#40792 / #2

Validity:
SS 2017 - SS 2017

Default display language:
English

Module title:
Semantic Web and Linked Data

Credits:
6

Responsible person:
Hauswirth, Manfred

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Telekommunikationssysteme

Area of expertise:
34332300 FG Open Distributed Systems

Prüfungsausschuss:
No information

Kontakt

Office:
No information

Contact person:
Wylot, Marcin

E-mail address:
lehre@ods.tu-berlin.de

Website:

http://www.ods.tu-berlin.de

Learning Outcomes

Learning Objective - Demonstrate knowledge of Semantic Web and Linked Data principles. - Demonstrate skills in applying Semantic Web and Linked data technologies in practice. How Assessed - Final Exam, In-Class Labs, Assignments, Research Report - In-Class Labs, Assignments, Research Report

Content

The web has become an object of our daily life and the amount of information there is ever growing. Besides plain texts, multimedia such as graphics, audio or video have become a predominant part of the web's information traffic. But, how can we find useful information within this huge information space? How can we make use of the knowledge contained in those web documents? Traditional search engines for example will reach the limits of their power, when it comes to understanding information content. The Semantic Web and Linked Data concepts extend the traditional web in the sense that information in the form of natural language text in the web will be complemented by its explicit semantics based on a formal knowledge representation. Thus, the meaning of information expressed in natural language can be accessed in an automated way and interpreted correctly, i.e. it can be “understood“ by machines. Semantic Web technologies enable the explicit representation of knowledge and its further processing to deduce new knowledge from implicitly hidden knowledge. Morover, previously isolated data collections can be now connected with meaningfull (semantic) links trough the machine processable Web of Linked Data. Such Linked Data collections enhanced with semantics enables applications to improve their user experience - thanks to having access to a wider range of knowledge. Increasing numbers of organizations and initiatives are starting to appreciate the power of the Semantic Web and Linked Data. It provides significant power and potential to the growing Big Data domain. On this course you will learn the fundaments of the Semantic Web and Linked Data - exploring how this new Web of Data isn’t only about creating a big collection of standalone datasets, but is also about using a common format to ensure data is interchangeable.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Semantic Web and Linked Data	IV	0432 L7 65	WiSe	No information	4

Workload and Credit Points

Semantic Web and Linked Data (IV):

Workload description	Multiplier	Hours	Total
Assignments & Labs (Übungsaufgaben/ Praxisteil)	15.0	4.0h	60.0h
Präsenzzeit	15.0	4.0h	60.0h
Vor- und Nachbearbeitung	15.0	4.0h	60.0h
			180.0h(~6 LP)

The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

This course will contain in an integrated form: lectures, exercises as well as a small project assignment.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

This course will include in-class labs that involve the installation, configuration and programming of multiple tools. It is recommended, that students have some experience with programming languages (e.g. Java, C/C++), relational database systems, SQL, and Linux.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

English

Test elements

Name	Points	Categorie	Duration/Extent
(Deliverable assessment) Assignments	45	flexible	Projektabhängig
(Examination) Written Exam (Multiple-Choice)	45	written	60 min
(Learning process review) Labs	10	flexible	Projektabhängig

Grading scale

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	95.0pt	90.0pt	85.0pt	80.0pt	75.0pt	70.0pt	65.0pt	60.0pt	55.0pt	50.0pt

Test description (Module completion)

A total of 100 portfolio points can be achieved. The final grade of the module is based on the grading system 2 of Faculty IV (§ 47 (2) AllgStuPO).

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Wintersemester.

Maximum Number of Participants

The maximum capacity of students is 20.

Registration Procedures

Depending on the specific examination rules a registration via QISPOS or at the responsible examination office might be necessary. For more information, visit: http://www.ods.tu-berlin.de

Recommended literature
P. Hitzler, M. Krötzsch, S. Rudolph, Y. Sure: "Foundations of Semantic Web Technologies" (in English). Chapman & Hall/CRC, 2009; ISBN: 9781420090505
Tom Heath and Christian Bizer (2011) Linked Data: Evolving the Web into a Global Data Space (1st edition). Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136. Morgan & Claypool.

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

This module is used in the following Degree Programs (new System):

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

Miscellaneous

No information

Semantic Web and Linked Data