This course is composed of 7 sessions, based on the FAIR training handbook and 10 simple rules to make material FAIR publication. All sessions are structured in a way that complement each other aiming to introduce participants with a theoretical & hands-on approach of how to create FAIR material by design.
Registration: 11. April 2024 until 23- August 2024
Date: 18 - 19 September 2024
Join us for a two-session workshop designed specifically for busy biologists looking to enhance their productivity through effective data management practices.
Dates: March 20th and 21st
FAIR põhimõtted, mis esmakordselt avaldati 2016. aastal, sisaldavad häid andmehaldustavasid, mille eesmärk on muuta andmed leitavaks, ligipääsetavaks, ühilduvaks ja taaskasutatavaks. Iga täht FAIR-is viitab põhimõtete (15) loendile. Kuigi FAIR põhimõtted pärinevad loodusteadustest, saab neid rakendada kõigis teadusvaldkondades. Alates nende avaldamisest on Euroopa Liit, riiklikud rahastajad ja ülikoolid väljendanud nende põhimõtete toetust ja heakskiitu. Ja olgem ausad, mõnda neist asjadest te teete ilmselt juba praegu. Sellel kursusel käime läbi kõik FAIR põhimõtted ja kuidas neid reaalses elus rakendatakse. Nii tead juba, mida taotluse kirjutamisel, oma andmehalduskava täites või oma uurimistööd tehes arvesse võtta.
Lihtsas keeles väljendudes on metaandmed teie andmeid kirjeldav informatsioon. Kuid mida metaandmed tegelikult hõlmavad ja kui palju neid peaks teie andmetega kaasas olema?
On the 16th of February 2023, ELIXIR-Estonia will be holding an online data management course in English: FAIR in a Nutshell. This lecture will be a short overview of the FAIR principles and is part of a bigger data management course package aimed at DMP writers and grant applicants.
In recent years, more attention has been put on what researchers do with the data they produce. Especially in Europe (think GDPR), but also everywhere else. The main idea is that when researchers use taxpayers' money, the taxpayers themselves should also have access to the results free of charge. This means that the research should be published in open-access journals, and data should be made publicly available.
Good data management helps to make the whole process of making data reusable easier. In general, you should think about how to manage your data at the beginning and during the project and know what you plan to do with it at the end of the project. However, what is “good data management” exactly is up for debate. The FAIR Principles concentrate on making your data findable, accessible, interoperable and reusable, so this is a good start. And let’s be honest, some of these things you probably are already doing.
In this course, we will be going over all the FAIR Principles and how they are applied in real life. This way, you will already know what to consider while writing a grant, filling out your data management plan or doing your research.
Information about the lecture
Date: 16.02.2023
Language: English
Time: 10:00 - 12:00
Place: Zoom, link will be sent a couple of days before the lecture
We ask you to register responsibly. If you can't attend the lecture, please let us know as soon as possible via email (elixir@ut.ee).
Register: closed
In order to not miss out a course next time, subscribe to our newsletter at https://lists.ut.ee/wws/subscribe/elixir.news?previous_action=edit_list_request
Learning outcomes:
On the 13th of April, 2023, ELIXIR-Estonia will hold a data management lecture: Metadata and README. This lecture will be held in English and will be held online. In general, metadata is the descriptive information about your data. However, what exactly is metadata, and how much of it should be included with your data?
Good metadata can make up for human fallibilities. People forget and misplace things and leave research projects with their knowledge of the research methodology and the data. Metadata ensures that we will be able to find the data, use it, preserve and reuse it in the future.
This means that the metadata provides additional information that helps data consumers better to understand the meaning and the structure of the dataset and to clarify other issues, such as rights and license terms, the organization that generated the data, data quality, data access methods, and the update schedule of datasets. Additionally, metadata also gives information about the data in general. What an actual metadata file includes varies between disciplines and types of data you are working with. However, the documentation for your data should contain the minimum information required to be able to reuse (or understand) the data described.
In the lecture, we will be going over what exactly metadata is, the minimum information that should be included with each of the scientific results you are sharing, and how exactly you can write a README file.
Information about the lecture
Date: 13.04.2023
Language: English
Time: 10:00-12:00
Place: Zoom, the link will be sent a couple of days before the lecture
Registration is closed.
We do ask you to register for the lecture responsibly. If you can’t attend the course, please let us know as soon as possible via email at elixir@ut.ee.
In order to not miss out a course next time, subscribe to our newsletter at https://lists.ut.ee/wws/subscribe/elixir.news?previous_action=edit_list_request
Learning outcomes for the participants:
ELIXIR Estonia is continuing with the data management-related lectures and workshops this semester. To get more information about these courses, read below and visit https://elixir.ut.ee/training.
We do ask you to register for the lecture responsibly. If you can’t attend the course, please let us know as soon as possible via email at elixir@ut.ee.
ELIXIR Estonia is continuing with the data management-related lectures and workshops this semester. To get more information about these courses, read below and visit https://elixir.ut.ee/training.
Face-to-Face (F2F) lectures will take place at the Delta building in Tartu (Narva mnt 18, Tartu).
ONLINE workshops will be held through Zoom (the meeting link will be sent a couple of days before the workshop).
Register: https://forms.gle/6y2FaHMN7nrbA5bR7
More information: https://elixir.ut.ee/node/448
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More information: https://elixir.ut.ee/node/450
Register: https://forms.gle/bWiBGrpanoot3YR59
More information: https://elixir.ut.ee/node/456
Register: https://forms.gle/rjiGvJj32qweG5mj6
More information: https://elixir.ut.ee/node/452
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More information: https://elixir.ut.ee/node/454
Register: https://forms.gle/2uMN9RN8LEyT8doM7
More information: https://elixir.ut.ee/node/456
We do ask you to register for the lecture responsibly. If you can’t attend the course, please let us know as soon as possible via email at elixir@ut.ee.
On the 13th of September, 2022, ELIXIR-Estonia will hold a data management lecture: Metadata and README. This lecture will be held in English.
In general, metadata is the descriptive information about your data. However, what exactly is metadata, and how much of it should be included with your data?
Good metadata can make up for human fallibilities. People forget and misplace things and leave research projects with their knowledge of the research methodology and the data. Metadata ensures that we will be able to find the data, use it, preserve and reuse it in the future.
This means that the metadata provides additional information that helps data consumers better to understand the meaning and the structure of the dataset and to clarify other issues, such as rights and license terms, the organization that generated the data, data quality, data access methods, and the update schedule of datasets. Additionally, metadata also gives information about the data in general. What an actual metadata file includes varies between disciplines and types of data you are working with. However, the documentation for your data should contain the minimum information required to be able to reuse (or understand) the data described.
In the lecture, we will be going over what exactly metadata is, the minimum information that should be included with each of the scientific results you are sharing, and how exactly you can write a README file.
Information about the lecture
Dates: 13th of September, 2022 at 14:15 (lecture, 2h)
Place: Delta Building, r1022 (Narva mnt 18), TARTU
Register: CLOSED
Registration closes at 23:59 on 08.09.2022 or when the course gets full.
Learning outcomes for the participants:
F2F lectures will take place at the Delta building in Tartu (Narva mnt 18, Tartu).
Parking: You can park for free for 3h in the parking lot of the University of Tartu Academic Sports Club.
We do ask you to register for the lecture responsibly. If you can’t attend the course, please let us know as soon as possible via email at elixir@ut.ee.
In the month of April, ELIXIR Estonia will be holding two data management online courses: "How to make your messy data usable?" on the 4th of April and "Metadata and README" on the 11th of April. Both of the courses will be held online, in Zoom, and in English.
"How to make your messy data usable?" course will be in two parts: an 1.5 hour online lecture on how to make a spreadsheet usable for other people, held on the 4th of April at 10:00 in Zoom. The practical workshop on cleaning your messy data with OpenRefine software will be a video lecture that you can follow on your own time. Additionally, we will hold 3 Q&A sessions in Zoom, where you can talk about any problems you encountered with the OpenRefine software. In the "Metadata and README" lecture, we will be going over what exactly is metadata, what is the minimum information that should be included with each of the scientific results you are sharing and how exactly can you write a README file.
In recent years, more attention is put on what researchers do with the data (and other resources) they produce. Especially in Europe, but also everywhere else. The main idea is that when researchers use taxpayers' money, the taxpayers themselves should also have access to the results, free of charge. This means that the research should be published in open access journals and data should be made publicly available.
Good data management may help you with that, at least to make the process easier on the whole. If you think what to do with your data at the beginning and during the project and know what you plan to do with it at the end of the project, the process at the end will be easier. However, what is “good data management”, is up to debate. The FAIR Principles concentrates on making your data findable, accessible, interoperable and reusable, so this is a good start. And let’s be honest, some of these things you are probably already doing.
How to make your messy data usable? course information
In this course, we will be going over how to name your files and variables, version control, compile a data dictionary, and what to do with empty cells. In the second part, OpenRefine software is introduced. With this, you can easily clean up the messy data. For the more practical aspect of using the OpenRefine software, I will share a video that will teach the basics. You can watch it anytime and do the lessons yourself. On three days (6.04, 7.04 and 8.04) there will be a 1h slot (10:00-11:00) on Zoom, when you can come and ask any question you have regarding tables and OpenRefine software.
Information about the lecture:
Lecture: 4th of April, 2022 at 10:00 (lecture, 1.5h; in English)
Q&A session: 6.04, 7.04 and 8.04 at 10:00 (Q&A, feedback, 1h)
Place: ZOOM (link will be sent to your email)
Register: https://forms.gle/axZTA5rw3bPnKDww9 REGISTRATION IS CLOSED
Registration closes at 23:59 on 31.03.2022 or when the course gets full.
Learning outcomes:
Metadata and REAME lecture information
In general, metadata is the descriptive information about your data. However, what exactly is metadata and how much of it should be included with your data? Good metadata can make up for human fallibilities. People forget and misplace things, and leave research projects taking their knowledge of the research methodology and the data with them. Metadata ensures that we will be able to find the data, use it, preserve and reuse it in the future.
This means that the metadata provides additional information that helps data consumers to better understand the meaning of the dataset, its structure and to clarify other issues, such as rights and license terms, the organization that generated the data, data quality, data access methods and the update schedule of datasets. Additionally, metadata also gives information about the data in general. What an actual metadata file includes, varies between disciplines and types of data you are working with. However, the documentation for your data should contain the minimum information required to be able to reuse (or understand) the data described.
In this lecture, we will be going over what metadata about your dataset should be included when you are sharing it. Additionally, we will also go over some examples on how to write a good README file.
Information about the lecture:
Time: 11th of April, 2022 at 10:00 (lecture, 2h; in English)
Place: ZOOM (link will be sent to your email)
Register: https://forms.gle/YKvQyd8wrx2cvyYf9 REGISTRATION IS CLOSED
Registration closes at 23:59 on 31.03.2023 or when the course gets full.
Learning outcomes: