Curricula

Objective

Purpose of the course

This course will allow you to dive deeper into the world of data utilisation in bioeconomy. We will do the necessary data analysis, explore examples of data modelling in the bioeconomy and practice processing data into information and informed decisions. There is indeed a demand for data agrologists now and in the future!

Competences

Technological competences:
-be able to select and develop technological solutions for bioeconomy production processes
-be able to measure and analyse process variables in biomass production and processing
-be able to exploit different sources of bioeconomy data, ensuring data accuracy and security
Science and environmental literacy:
-be able to apply and use scientific environmental knowledge and the potential of the circular economy in your own activities
-be able to apply biology, mathematics, chemistry and physics to applied tasks in rural industries
Proactive development:
-can apply existing knowledge in the field and use research and development methods in development

Learning outcomes

After completing this course, you will know how to generate information from raw data to support decision making and why to combine different data sources in the same decision making process. You will outline the importance of data quality requirements such as data accuracy thresholds, the time window of data needs and the cumulative nature of data. You will be able to use appropriate tools and software for data processing.

Content

-Processing and editing spatial data
-Using data for decision making
-The principle and details of spatial data
-Data needs analysis for different types of bioeconomy processes
-Options for data visualisation

Qualifications

Strong basic knowledge of the different production processes of the bioeconomy: agriculture, forestry, environmental knowledge and/or other bioeconomy application areas

Assessment criteria, satisfactory (1)

Intermediate 1;
You know how to generate information from raw data to support decision making and you know why to combine different data sources in the same decision making process. You outline the importance of data quality requirements such as data accuracy thresholds, the time window of data needs and data accumulation. You will be able to use appropriate tools and software for data processing.

Satisfactory 2:
You know how to generate different types of information from raw data to support decision making and you know why to combine different data sources in the same decision making process. You understand the importance of data quality requirements such as data accuracy thresholds, the time window of data need and data accumulation. You will also be able to use a wide range of appropriate tools and software for data processing.

Assessment criteria, good (3)

Good 3:
You know how to produce different types of information from raw data to support decision making and you know why to combine different data sources in the same decision making process. You relate the importance of data quality requirements such as data accuracy limits, the time window of data needs and data accumulation. You will be able to use a wide range of tools and software for data processing.

Excellent 4:
You know how to produce different types of information from raw data to support decision making and you know why to combine different data sources in a variety of ways in the same decision making process. Through the topic, you will justify the importance of data quality requirements such as data accuracy thresholds, the time window of data need and data accumulation. You will be able to use a wide range of tools and software for data processing.

Assessment criteria, excellent (5)

Excellent 5:
You know how to generate different types of information from raw data to support decision-making and you can combine different sources of information in a variety of ways in the same decision-making process. You will create and justify appropriate data quality requirements such as data accuracy thresholds, time window of data need and data accumulation. You will be able to make versatile and applied use of appropriate tools and software for data processing.

Further information

The course "Data Collection from Bioeconomy Processes" is recommended to be completed before this course.