Course description - Revision history

Vimala at 09:24, 18 August 2020

2020-08-18T09:24:47Z

← Older revision		Revision as of 09:24, 18 August 2020
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	* '''Mandatory activities:''' Participation at 80% of course seminars is mandatory. When teaching is distributed across institutions, students in other institutions may participate online from their institution.		* '''Mandatory activities:''' Participation at 80% of course seminars is mandatory. When teaching is distributed across institutions, students in other institutions may participate online from their institution.
	* '''Evaluation forms:'''		* '''Evaluation forms:'''
	** ''Written exam (30%):'' An individual, theoretical essay with thoughtful research and discussion of an assigned topic (30%). In addition there is a practical assignment in groups (40%). Both assignments must be done in the teaching semester.		** ''Written exam (30%):'' An individual, theoretical essay with thoughtful research and discussion of an assigned topic (27,5%). In addition there is a practical assignment in groups (27,5%). Both assignments must be done in the teaching semester and oral presentations of both essay and project assignment (15%) .
	** ''Grading scale:'' The grading system has a descending scale from A to E for passes and F for fail.		** ''Grading scale:'' The grading system has a descending scale from A to E for passes and F for fail.
	* '''Evaluation semester:''' Irregular		* '''Evaluation semester:''' Irregular
	* '''Subject evaluation:''' INFO319 is evaluated by students every three years and by the department every year.		* '''Subject evaluation:''' INFO319 is evaluated by students every three years and by the department every year.
	* '''Department:''' Department of Information Science and Media Studies		* '''Department:''' Department of Information Science and Media Studies

Vimala at 13:44, 1 November 2018

2018-11-01T13:44:31Z

← Older revision		Revision as of 13:44, 1 November 2018
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	*** prepare and evaluate uses of big data in emergency situations		*** prepare and evaluate uses of big data in emergency situations

	* '''Required prior knowledge:''' European (three-year) Bachelor's degree in information science or similar degree in ICT, covering ~~basic~~ programming skills.		* '''Required prior knowledge:''' European (three-year) Bachelor's degree in information science or similar degree in ICT, covering good programming skills.
	* '''Requirements for students:''' Master in Information Science or similar ICT background. Students in their last year of a 4-year Bachelor’s programme can be admitted.		* '''Requirements for students:''' Master in Information Science or similar ICT background. Students in their last year of a 4-year Bachelor’s programme can be admitted.
	* '''Teaching forms and extent of organised teaching:''' Lectures, and work with assignments, presentations and discussions. Parts of the course may be taught at a distance.		* '''Teaching forms and extent of organised teaching:''' Lectures, and work with assignments, presentations and discussions. Parts of the course may be taught at a distance.

Sinoa: /* INFO319 Research Topics in Big Data for Emergency Management (15 ECTS) */

2017-11-16T11:31:36Z

INFO319 Research Topics in Big Data for Emergency Management (15 ECTS)

← Older revision		Revision as of 11:31, 16 November 2017
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	This is the formal course description for the proposed new course on Big Data, with Emergency Management as the central application area. The details are not set in stone, but changes take some time due to bureaucracy, and the course title is permanent (which is why it is so general).		This is the formal course description for the proposed new course on Big Data, with Emergency Management as the central application area. The details are not set in stone, but changes take some time due to bureaucracy, and the course title is permanent (which is why it is so general).

	== INFO319 Research Topics in Big Data ~~for Emergency Management~~ (15 ECTS) ==		== INFO319 Research Topics in Big Data (15 ECTS) ==

	* '''Study points:''' 15 ECTS (50% of a bi-mester)		* '''Study points:''' 15 ECTS (50% of a bi-mester)

Sinoa: Sinoa moved page Course description: to Course description

2017-11-15T15:21:11Z

Sinoa moved page Course description: to Course description

← Older revision	Revision as of 15:21, 15 November 2017
(No difference)

Sinoa at 15:20, 15 November 2017

2017-11-15T15:20:17Z

← Older revision		Revision as of 15:20, 15 November 2017
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	* '''Study level:''' Master level (4th year of studies)		* '''Study level:''' Master level (4th year of studies)

	* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.		* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation. The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management. The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.
	The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management. The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.

	* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:		* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Sinoa at 15:19, 15 November 2017

2017-11-15T15:19:59Z

← Older revision		Revision as of 15:19, 15 November 2017
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	* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.		* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.
	The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management.~~<br>~~The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.		The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management. The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.

	* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:		* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Sinoa at 15:19, 15 November 2017

2017-11-15T15:19:40Z

← Older revision		Revision as of 15:19, 15 November 2017
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	== INFO319 Research Topics in Big Data for Emergency Management (15 ECTS) ==		== INFO319 Research Topics in Big Data for Emergency Management (15 ECTS) ==
	~~(See end of document)~~

	* '''Study points:''' 15 ECTS (50% of a bi-mester)		* '''Study points:''' 15 ECTS (50% of a bi-mester)
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	* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.		* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.
	The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management.		The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management.<br>The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.
	The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.

	* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:		* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Sinoa at 15:19, 15 November 2017

2017-11-15T15:19:10Z

← Older revision		Revision as of 15:19, 15 November 2017
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	* '''Study level:''' Master level (4th year of studies)		* '''Study level:''' Master level (4th year of studies)

	* '''Goal and content:'''		* '''Goal and content:''' The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.
	The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.
	The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management.		The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management.
	The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.		The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.

	* '''Learning outcomes:'''		* '''Learning outcomes:''' A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
	A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
	** ''Knowledge:'' Upon completion of the course the candidate shall		** ''Knowledge:'' Upon completion of the course the candidate shall
	*** understand central concepts, standards, and technologies for big data		*** understand central concepts, standards, and technologies for big data
Line 31:		Line 29:
	*** prepare and evaluate uses of big data in emergency situations		*** prepare and evaluate uses of big data in emergency situations

	* '''Required prior knowledge:'''		* '''Required prior knowledge:''' European (three-year) Bachelor's degree in information science or similar degree in ICT, covering basic programming skills.
	European (three-year) Bachelor's degree in information science or similar degree in ICT, covering basic programming skills.		* '''Requirements for students:''' Master in Information Science or similar ICT background. Students in their last year of a 4-year Bachelor’s programme can be admitted.
			* '''Teaching forms and extent of organised teaching:''' Lectures, and work with assignments, presentations and discussions. Parts of the course may be taught at a distance.
	* '''Requirements for students:'''		* '''Mandatory activities:''' Participation at 80% of course seminars is mandatory. When teaching is distributed across institutions, students in other institutions may participate online from their institution.
	Master in Information Science or similar ICT background. Students in their last year of a 4-year Bachelor’s programme can be admitted.		* '''Evaluation forms:'''
			** ''Written exam (30%):'' An individual, theoretical essay with thoughtful research and discussion of an assigned topic (30%). In addition there is a practical assignment in groups (40%). Both assignments must be done in the teaching semester.
	* '''Teaching forms and extent of organised teaching:'''		** ''Grading scale:'' The grading system has a descending scale from A to E for passes and F for fail.
	Lectures, and work with assignments, presentations and discussions. Parts of the course may be taught at a distance.		* '''Evaluation semester:''' Irregular
			* '''Subject evaluation:''' INFO319 is evaluated by students every three years and by the department every year.
	* '''Mandatory activities:'''		* '''Department:''' Department of Information Science and Media Studies
	Participation at 80% of course seminars is mandatory. When teaching is distributed across institutions, students in other institutions may participate online from their institution.

	* '''Evaluation forms:'''
	** ''Written exam (30%):''
	An individual, theoretical essay with thoughtful research and discussion of an assigned topic (30%).
	In addition there is a practical assignment in groups (40%).
	Both assignments must be done in the teaching semester.

	** ''Grading scale:''
	The grading system has a descending scale from A to E for passes and F for fail.

	* '''Evaluation semester:'''
	Irregular

	* '''Subject evaluation:'''
	INFO319 is evaluated by students every three years and by the department every year.

	* '''Department:'''
	Department of Information Science and Media Studies

Sinoa: Created page with "This is the formal course description for the proposed new course on Big Data, with Emergency Management as the central application area. The details are not set in stone, but..."

2017-11-15T15:18:08Z

Created page with "This is the formal course description for the proposed new course on Big Data, with Emergency Management as the central application area. The details are not set in stone, but..."

New page

This is the formal course description for the proposed new course on Big Data, with Emergency Management as the central application area. The details are not set in stone, but changes take some time due to bureaucracy, and the course title is permanent (which is why it is so general).

== INFO319 Research Topics in Big Data for Emergency Management (15 ECTS) ==
(See end of document)

* '''Study points:''' 15 ECTS (50% of a bi-mester)
* '''Teaching semester:''' Autumn. Irregular (not necessarily taught every year)
* '''Subject code:''' INFO319
* '''Number of semesters:''' 1
* '''Language:''' English
* '''Study level:''' Master level (4th year of studies)

* '''Goal and content:'''
The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation.
The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management.
The course involves development work using selected technologies and standards for big data and for emergency management. Examples of research and research methods in the area will also be presented and discussed.

* '''Learning outcomes:'''
A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
** ''Knowledge:'' Upon completion of the course the candidate shall
*** understand central concepts, standards, and technologies for big data
*** know about current research and industry trends in big data
*** understand central concepts and standards in emergency management
*** understand how big data can be leveraged in emergency situations
*** know about current research and industry trends in big data for emergency management
*** know the relevant reseach methods for the area
** ''Skills:'' Upon completion of the course the candidate shall be able to
*** use central technologies and tools for managing and using big data
*** use central technologies and tools for emergency management
*** leverage big data in emergency situations
*** prepare and evaluate uses of big data in emergency situations

* '''Required prior knowledge:'''
European (three-year) Bachelor's degree in information science or similar degree in ICT, covering basic programming skills.

* '''Requirements for students:'''
Master in Information Science or similar ICT background. Students in their last year of a 4-year Bachelor’s programme can be admitted.

* '''Teaching forms and extent of organised teaching:'''
Lectures, and work with assignments, presentations and discussions. Parts of the course may be taught at a distance.

* '''Mandatory activities:'''
Participation at 80% of course seminars is mandatory. When teaching is distributed across institutions, students in other institutions may participate online from their institution.

* '''Evaluation forms:'''
** ''Written exam (30%):''
An individual, theoretical essay with thoughtful research and discussion of an assigned topic (30%).
In addition there is a practical assignment in groups (40%).
Both assignments must be done in the teaching semester.

** ''Grading scale:''
The grading system has a descending scale from A to E for passes and F for fail.

* '''Evaluation semester:'''
Irregular

* '''Subject evaluation:'''
INFO319 is evaluated by students every three years and by the department every year.

* '''Department:'''
Department of Information Science and Media Studies