Infopaket

Big data in geosciences

ОК 7

Обов’язкова дисципліна для ОП

Second

2021/2022

2 Semester

3

Use oral and written technical Ukrainian language and communicate in a foreign language (English) among specialists in geodesy and land management. Know the theoretical foundations of geodesy, higher and engineering geodesy, topographic and thematic mapping, mapping and updating maps, remote sensing of the Earth and photogrammetry, land management, real estate appraisal and land cadastre.

Full-time form

1. Basic knowledge of general disciplines of Earth sciences (geology, geophysics, geodesy, etc.), basic of databases and programming. 2. Basic technical skills in informational technologies, programming, data processing and databases.

Academic discipline "Big data in Geosciences" that integrates the knowledge of geodata in Earth sciences is part of education and professional training program for the education level "master" branch of knowledge 19 - Архітектура та будівництво 193 - Геодезія та землеустрій, educational program: Geoinformation systems and Technologies. The discipline is taught in the 2nd semester of 1st year Master’s degree program in volume - 90 hours (3 credits ECTS) including lectures - 14 hours, practical works - 14 hours, consultations - 2 hours, self-study work - 60 hours. The course content provides two modules and two module tests. The discipline is finished by test. The tasks of the discipline – to highlight the following issues: o big data concept; o geodata sources and techniques of the data acquiring; o geodatabases and data warehouses; o geodata processing methods; o applications of big data in the geosciences.

1. Cebr: Data equity, Unlocking the value of big data. in: SAS Reports, (2012) 2. EMC: Data Science and Big Data Analytics. In: EMC Education Services, (2012) 3. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H.: Big Data: The Next Frontier for Innovation, Competition, and Productivity. In: McKinsey Global Institute Reports, (2011) 4. Plattner, H., Zeier, A.: In-Memory Data Management: An Inflection Point for Enterprise Applications. Springer, Heidelberg (2011) 5. Russom, P.: Big Data Analytics. In: TDWI Best Practices Report, (2011) 6. Big Data: Survey, Technologies, Opportunities, and Challenges http://www.hindawi.com/journals/tswj/2014/712826/ 7. “Challenges and Opportunities with Big Data”, A community white paper developed by leading researchers across the United States. 8. C. Wunsch, Discrete Inverse and State Estimation Problems With Geophysical Fluid Applications. 371 pp: Cambridge University Press, 2006.

lectures, practical classes, self-studying work

For admission to the final grading it is obligatory: 1) to pass two control tests; 2) to prepare six oral reports, which can be presented in the form of presentations and abstracts. The final grading is carried out in the form of written modular test.

english