Big data management

Objective Goals - Desired Learning Outcomes:

Knowledge

• Basic theories and concepts for the management of large amounts of information (Big Data Management -BDM)
• Research areas related to BDM
• '21st century' skills for BDM and research, in order to respond to contemporary challenges
• Software technologies and integration strategies related to BDM

Comprehension

• Understanding how theories are applied in practice
• Understanding the relationship between various research areas related to BDM and society
• Understanding the impact of software technologies

Application

• Applying basic principles of the theories of BDM
• Designing the basic principles of BDM through artificial intelligence and computational intelligence software
• Identifying the applications of the above software through the BDM organization "Kaggle"
• Developing a basic research structure
• Carrying out basic activities to bridge the gap between technological potential and real-world application

Analysis

• Identifying core parameters of the BDM basic principles
• Analyzing research data
• Identifying limitations in the application of technologies

Synthesis

• Combining theoretical approaches and research findings to interpret questions related to BDM
• Presenting results
• Presenting results of Kaggle competitions on major problem-solving and prediction challenges

Evaluation

• Learning how the evaluation of BDM results takes place through self-organizing deep learning machines
• Reflective practice on the impact of big data on the professional field
• Examining social dimensions of the big data phenomenon

Week schedule:

Week 1:  Introduction - Course presentation

Week 2:  From the real world to the world of information

Week 3:  About Ontology

Week 4:  Machine Learning

Week 5:  System security - Personal data

Week 6:  Big Data & management technologies

Week 7:  Machine Learning Technologies

Week 8:  Neural Networks

Week 9:  Kaggle Big Data

Week 10:  Assignment

Week 11: (a) Semantic web: Processing and managing large data collections on the internet – the case study of Patrologia Migne (b) In-class presentation assignments (online)

Week 12:  (a) Accessibility of cultural sites (b) In-class presentation assignments (online)

Week 13:  In-class presentation assignments

Recommended bibliography:

Suggested reading list:

In the "Documents" tab of the course on the Ionio Open eclass platform (https://opencourses.ionio.gr), in the "Bibliography" subfolder.

Selected/Further reading:

American Psychological Association (n.d). Interconnection of psychology and technology. Washington, DC: Author. Available at https://pages.apa.org/interconnections-booklet/

Delft University of Technology (n.d.).Open science: Sharing your research with the world. Free online course. Available at https://www.classcentral.com/course/research-delft-university-of-technology-open-scie-11719?utm_source=qz&utm_medium=web&utm_campaign=new_courses_october_2018

Hasso Plattner Institut (n.d.). Clean-IT- Towards sustainable digital technologies. Free online course. Available at https://open.hpi.de/sessions/new

Related journals

Big Data & Society, https://journals.sagepub.com/home/bds, Sage

Discover Data, https://link.springer.com/journal/44248, Springer

gradPSYCH, https://www.apa.org/gradpsych, American Psychological Association

Journal of Big Data, https://journalofbigdata.springeropen.com/, Springer

Journal of Computer Information Systems, https://www.tandfonline.com/journals/ucis20, Taylor and Francis

Heliyion, https://www.sciencedirect.com/journal/heliyon, Science Direct

International Journal of Heritage in the Digital Era, https://journals.sagepub.com/home/hde, Sage

Security and human rights, https://brill.com/view/journals/shrs/shrs-overview.xml, Brill

Teaching and learning methods:

Combination of synchronous distance learning with face-to-face teaching.

Face-to-face: two (2) lectures per semester.

Distance learning (using the synchronous ZOOM platform): eleven (11) lectures

Use of the Ionian University's asynchronous Opencourses platform

Use of Information and Communication Technologies:

Support for teaching/learning through the Ionian University's asynchronous distance learning platform Opencourses (document area, announcements, posting of notes and files, user groups, online coursework, file sharing, etc.)

Use of the Zoom platform for synchronous teaching and communication with students.

Use of the Turnitin language processing program to check for text similarity when preparing and evaluating course assignments and exercises.

Use of office applications (word processor, spreadsheets, presentation program)

Use of free software (e.g., PSPP, Protégé, HTML editor)

Assessment/grading methods:

Written assignments

Presentations

The assessment criteria are:

• understanding, organized structure, proper presentation, and performance
• originality/innovation of proposals
• the personal point of view
• honesty/integrity/transparency of sources
• proper structure and formatting of the presentation
• timely submission.