Office of Academic Affairs
Indian Institute of Science Education and Research Berhampur

CDS 202 : Information for Science and Technology (2)

Learning Objectives:

Aim of this course is to sensitise students about the role of data & information in the science and technology, as well as in day-to-day life. Further, it aims at creating awareness about what technologies, tools, standards and processes are available for students as they pursue their career in different specialised domains of S&T.

Course Contents:

• Data definition, history & origin of data science, data paradigm in science & technology, data intensive understanding, data intensive analysis, data intensive discovery, data intensive forecasting


• Data science principles and theory, role of data & metadata in S&T, data life cycle in S&T processes, data & metadata standards across disciplines, data and metadata organisational tools, data as economy, information banks for S&T studies, data interoperability standards, tools, practices and processes.


• Overview of the Data discovery challenges and infrastructures, data discovery services - Bibliographic & abstracting services, data repositories - planning to implementation, specialised global and national data repositories.


• Introductions to the S&T Data publishing - data publishing framework in S&T, metadata to data papers, data, fostering data papers in specialised areas of S&T


• Introductions to the Data management, analysis & modelling technologies & tools: databasing, BIG data, analytical tools, neural networks, artificial intelligence, visualisation, virtual reality, etc.


• Introductions to the informatics landscape in different areas of S&T, especially, life, earth, environment & sustainability science (Biodiversity Informatics, Ecosystem Informatics, Bioinformatics, Environmental Informatics, GeoInformatics, Chemoinformatics, Climate Change analysis & modelling, health informatics, physicoinformatics, etc.).


• Collaborations for data & information in S&T, CODATA, TDWG, Open reasearch data policy and practices, Global efforts to rescue of data at threat, OPEN data access, FAIR Research Data Management, Research Data Alliance, Persistent Identifiers, etc.

Suggested Readings :

1. Data Science: Concepts & Practice by Vijay Kotu & Bala Deshpande (2018), Morgan & Kaufmann Publishers.
2. Build a Career in Data Science by Emily Robbinson & Jacqueline Nolis (2020), Manning Publications Co.
3. https://www.oreilly.com/library/view/getting-data-right/9781491935361/ch04.html

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