GODAN e-learning course on Open Data Management in Agriculture and Nutrition
Open Data Management in Agriculture and Nutrition online course (on GODAN portal) |
- 19th November - 7th December 2018
- 1st - 19th October 2018
- 2nd July – 27th July 2018
- 9th April - 4th May 2018
- 13th November - 8th December 2017
in English - have been delivered through the FAO of the UN MOODLE e-learning platform.
This e-learning course is the result of a collaboration between GODAN Action partners, including Wageningen Environmental Research (WUR), AgroKnow, AidData, the Food and Agriculture Organization of the United Nations (FAO), the Global Forum on Agricultural Research (GFAR), and the Institute of Development Studies (IDS), the Land Portal, the Open Data Institute (ODI) and the Technical Centre for Agriculture and Rural Cooperation (CTA).
# THE COURSE FOCUSES ON
how to deal with different types of data formats and uses, and on the importance of reliability, accessibility, interoperability and transparency of data. The course covers key knowledge and concepts needed by the target audience groups, as well as provides task-based and vocational training to support information and data professionals in their daily activities.
# THE COURSE ADDRESSES
- Infomediaries (including ICT workers, technologist-journalists, communication officers, librarians and extensionists) - interested in open data and research data management (in agriculture and nutrition);
- Researchers engaged in producing and curating datasets that underlie research publications, identifying datasets suitable for reuse in research as well as in communicating societal benefits of research results;
- Policy and decision makers involved in formulating policies and reports using open data, and in developing strategies for sustainable open data plans.
# THE COURSE IS MODULAR
and split into five units (comprising a series of e-learning lessons):
UNIT 1 : OPEN DATA PRINCIPLES | Lesson 1: What is open data Lesson 2: Ethics in open data LifeCycle |
UNIT 2 : USING OPEN DATA
| Lesson 1: Discovering open data Lesson 2: Quality and provenance Lesson 3: Data analysis and visualisation Lesson 4: Open data in policy cycles Lesson 5: Referencing data |
UNIT 3 : MAKING DATA OPEN
| Lesson 1: Managing data sets Lesson 2: Managing dynamic datasets Lesson 3: Creating and managing data repositories Lesson 4: Advocate for capacity development Lesson 5: Developing strategies for implementing open data plans |
UNIT 4 : INTEROPERABILITY
| Lesson 1: Guiding frameworks for data sharing Lesson 2: Introduction to open data interoperability Lesson 3: Structural and architectural interoperability Lesson 4: Semantic interoperability Lesson 4.1: Using published semantics for agronomic data |
UNIT 5 : INTELLECTUAL PROPERTY & COPYRIGHT | Lesson 1: Intellectual property rights Lesson 2: Licensing |
# THE COURSE AIMS TO
strengthen the capacity of data producers and data consumers to manage and use open data in agriculture and nutrition. In particular, by the end of the course, learners will be able to:
# Understand the principles and benefits of open data | # Recognize the potential of using and publishing open data in agriculture and nutrition |
# Identify the steps to advocate for open data policies, in both public and private sectors | # Be aware of the economical and social value of open data |
# Understand how and where to find open data | # Identify benefits of using data creation, management and exchange widely-used good practices in agriculture and nutrition |
# Recognise the necessary steps to set up an open data repository | # Understand how to advocate for the adoption of open data principles |
# Identify the principles to make data FAIR : findable, accessible, interoperable, and reusable | # Recognise the benefits and costs associated with exchanging meaningful open data |
# Understand the basics of copyright and database rights | # Know how to assign licenses to data and how to respect licenses while using data |
Welcome to Open Data Management in Agriculture and Nutrition Online Course UNITS
Skills and knowledge obtained in this course are to be used in the context of different institutions in agricultural and nutrition knowledge networks.
# THE COURSE ASSESSMENT & CERTIFICATION
The course lasts four weeks, with an end of course exam and course evaluation at the end. Learners will take short quizzes, assignments and hands-on practices within the units.
Attendance of certificate is provided for those who passed the end of course exam with 60% success rate. Certificate are only provided in electronic form in PDF.
Important announcements and upcoming event related to the course will be made on the course page (GODAN). GODAN Action is a programme launched by the UK’s Department of International Development (DFID). It brings together agriculture and nutrition specialists and open data experts, and will support Global Open Data for Agriculture and Nutrition (GODAN) by building and developing people’s capacity to engage with open data. |
You can get in touch with any other questions or thoughts about this online course at the following e-mails: <[email protected]>, <[email protected]>
Followie @AIMS_Community... and thanks again for your interest!
Related: |
- Providing researchers with the skills and competencies they need to practise Open Science (Open Science Skills Working Group Report, EC 2017)
- What is 'Open Data'? (ANDS)
- WHY FOCUS ON DATA? WHY GODAN? (CTA, 2017)
- Open Data Essentials (The World Bank)
- Recorded GODAN Action Webinar: Sharing Open Data and Capacity Development experiences from RCMRD
- Recorded ANDS FAIR Webinar series : #1 Findable #2 Accessible #3 Interoperable #4 Reusable
- Recorded GODAN Webinar : Strategies for Supporting Collaborations and Building Relationships for Opening Data in Agriculture
- Recorded Webinar : What is GODAN? Network, Action & Secretariat (GODAN)
- Recorded GODAN Webinar : Using Open Data (The Open Data Institute)
- Open Data in a Day : ODI introductory course (ODI)
- Creating impact with data (CTA)
- Implement effective Open Data & Keep it alive with Open Data TOOLKIT
Webinar recording on GODAN Action Project (all GODAN Webinar Series)
The Open Data for Development (OD4D) program that brings together a network of leading implementing partners who have a wealth of experience in developing countries
European Data Portal (Training on the basics of Open Data)
FOSTER portal (including resources from the LEARN Project). Help FOSTER promote Open Science and contribute
Free FAO e-learning course on communication for rural development
Why choose Moodle? Outlining the benefits (CoSector, University of London)
Data management practices have been described in detail in a variety of documentation and tutorials, which may focus on specific needs and resources applicable to the organization that produced them:
- Data Tree e-course [funded by the Natural Environment Research Council (NERC) through the National Productivity Investment Fund (NPIF), delivered by the Institute for Environmental Analytics and Stats4SD and supported by the Institute of Physics]
- New e-learning module online: Finding research data (Wageningen University & Research)
- Free e-lectures on Integrated Marine Observing System (IMOS) Marine DATA and SCIENCE
A list of training opportunities/resources on Research Data Management compiled by the US/RDA Education Effort
- Essentials 4 Data Support is an introductory course for those people who (want to) support researchers in storing, managing, archiving and sharing their research data
- Coursera Data Science e-learning
- Coursera Research Data Management and Sharing e-learning
- FOSTER Open Science Course
- MANTRA - how to manage digital data as part of your research project
- MANTRA for Librarians
- Author Carpentry
- Data Carpentry
- Library Carpentry
- WDS Data & Services Training Resources
- UCT eResearch
- The Class Central website has curated a list of several data science and analysis methods MOOCs, developed by reputable source. The MOOCs listed here have been developed through Johns Hopkins University, and offered through the Coursera platform. They are part of a Data Science Specialization series of of courses, and have applicability to data management practices outside of specific analytical techniques. Each of these courses lasts 4 weeks, and are frequently offered. Some of the are:
* The Data Scientist’s Toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. It focuses on a practical introduction to tools, using version control, markdown, git, GitHub, R, and RStudio;
* Getting and Cleaning Data. This course will cover the basic ways that data can be obtained. It will also cover the basics of data cleaning and how to make data “tidy”. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data. Tools used in this course: Github, R, RStudio;
* Reproducible Research.
- Short guide“10 Simple Rules for the Care and Feeding of Scientific Data” offers practical advice for researchers on practices they can follow to manage their data for sharing and reuse
- The University of Washington offers a well organized, comprehensive data management guide. Most of the resources listed are publicly available
- Make FAIR your Datasets using Springer Nature RESEARCH DATA SUPPORT
- Guidelines for Data Management Plan from SNSF : learning from each other
- Implement effective Open Data & Keep it alive with Open Data TOOLKIT
- Articulating the value of DATA with the Australian National Data Service (ANDS)