[et_pb_section fb_built=”1″ _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” collapsed=”off” global_colors_info=”{}”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.10.7″ _module_preset=”default” background_color=”RGBA(0,0,0,0)” border_radii=”on|8px|8px|8px|8px” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
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Open data is a movement within open science that works to ensure that data are <\/span>openly accessible, exploitable, editable and shared by anyone for any purpose.\u00a0<\/span>Open data are licensed under an <\/span>open licence<\/span><\/a>.<\/span><\/p>\n In 2014 the open data movement was strengthened by the introduction of the <\/span>FAIR<\/span><\/a> data principles. This acronym stands for data that are Findable, Accessible, Interoperable and Reusable. As an early adopter and supporter of the FAIR data principles, DANS has been highly active in promoting the evolution of data management practices that ensure that all data are FAIR and that data are \u201cas open as possible, as closed as necessary\u201d.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/dans.knaw.nl\/wp-content\/uploads\/2021\/09\/FAIR-en-Open-data-scaled.jpg” title_text=”FAIR en Open data” _builder_version=”4.10.7″ _module_preset=”default” border_radii=”on|8px|8px|8px|8px” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.10.7″ _module_preset=”default” background_color=”#FFFFFF” max_width=”678px” module_alignment=”center” overflow-x=”visible” overflow-y=”visible” custom_margin=”-125px||||false|false” custom_padding=”40px|40px|40px|40px|false|false” border_radii=”on|8px|8px|8px|8px” box_shadow_style=”preset3″ global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.10.7″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Since their inception in 2019, we have also been a supporter of the affiliated <\/span>CARE<\/span><\/a> principles for the protection of indigenous data: <\/span>Collective Benefit, Authority to Control, Responsibility, and Ethics.<\/span><\/p>\n We have been training on open and FAIR data through projects such as <\/span>FAIRsFAIR<\/span><\/a> and <\/span>FAIR-IMPACT<\/a>, as well as our longstanding training in research data management. Through our work on FAIRsFAIR, we have also been involved in the development of FAIR-enabling tools for researchers and data managers, such as <\/span>FAIR-Aware<\/span><\/a> and <\/span>F-UJI<\/span><\/a>.<\/span><\/p>\n The main training run by DANS on open and FAIR data is a course we developed in collaboration with <\/span>RDNL<\/span><\/a>:\u00a0<\/span>Essentials for Data Support<\/span><\/a>. You can follow it asynchronously online for free or sign up for one of the live training iterations.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n The sustainable management, sharing and reuse of research data are central to open science. The FAIR principles provide a widely adopted framework to support this. DANS supports researchers and data professionals in applying FAIR in practice through training, advice and reusable materials. On this page, you will find an overview of our training offering, alongside a selection of resources to help you get started with FAIR.<\/p>\n There is now a wide range of tools and training materials available to support FAIR. Below, you will find a curated selection of resources to help you build knowledge and apply FAIR in your own work.<\/p>\n [\/et_pb_text][et_pb_accordion _builder_version=”4.10.7″ _module_preset=”default” background_color=”RGBA(0,0,0,0)” global_colors_info=”{}”][et_pb_accordion_item title=”Would you like to assess your knowledge of the FAIR principles?” open=”off” _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” background_enable_color=”on” global_colors_info=”{}”]<\/p>\n The FAIR-Aware tool helps you explore your understanding of the FAIR principles and identify areas for further learning. It can be used for self-assessment as well as in group training settings.<\/p>\n Access the FAIR-Aware tool<\/a>.<\/p>\n Use this tool as a starting point to define your learning pathway.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”Looking for an introductory training in FAIR and research data management (RDM)?” _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” background_enable_color=”on” global_colors_info=”{}” open=”off”]<\/p>\n Start with openly available training materials that introduce the core concepts of FAIR and research data management, and support their application in practice.<\/span>\u00a0<\/span><\/p>\n Within the international PATTERN project, DANS and its partners developed reusable training materials, including lesson plans, slides, exercises and eLearning modules based on project-based learning.<\/span>\u00a0<\/span><\/p>\n Start with Module 1<\/a><\/strong>. For further learning, you can explore interactive eLearning modules:<\/p>\n <\/p>\n FAIR Research Data Management: A Practical Introduction<\/strong><\/a>.<\/p>\n This course is aimed at beginners and offers a structured introduction to FAIR and RDM. Through practical examples and exercises, you will learn how to apply FAIR principles in a research context.<\/p>\n <\/p>\n FAIR Research Data Management: A Deeper Dive into Putting FAIR RDM into Practice<\/strong><\/a>. <\/p>\n Full OpenPlato training catalogue<\/a>.<\/strong> [\/et_pb_accordion_item][et_pb_accordion_item title=”Are you working on data curation and reproducible research?” _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” background_enable_color=”on” global_colors_info=”{}” open=”off”]<\/p>\n Gain practical guidance on combining FAIR principles with reproducible research and improving the structure and documentation of your datasets.<\/span>\u00a0<\/span><\/p>\n The \u201810 CURE-FAIR things<\/a>\u2019 <\/span>have been developed for data curators and researchers working with computational workflows and reproducible research practices. The materials support making curation steps explicit, structured and repeatable.<\/span>\u00a0<\/span><\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”Do you work with qualitative data?” _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” background_enable_color=”on” global_colors_info=”{}” open=”off”]<\/p>\n Learn how to manage and share qualitative data responsibly, taking into account context, interpretation and ethical considerations.<\/span>\u00a0<\/span><\/p>\n Within open science, there is increasing attention for qualitative data, which do not always fit standard approaches or best practices. DANS has developed targeted materials and workshops to support researchers and data professionals in this area.<\/span>\u00a0<\/span><\/p>\n <\/span><\/p>\n Making Qualitative Data Reusable (guide)<\/span><\/b><\/a>. \u00a0<\/span><\/p>\n Workshop materials: Qualitative Data & Open Science \u2013 Are we there yet?<\/span><\/b><\/a>\u00a0<\/a> [\/et_pb_accordion_item][et_pb_accordion_item title=”Do you work with sensitive or hard-to-share data?” _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” background_enable_color=”on” global_colors_info=”{}” open=”off”]<\/p>\n Gain insight into how research data that cannot be fully shared openly can still be made available for responsible reuse.<\/span>\u00a0<\/span>In the social sciences and humanities, privacy, ethics and context often play a key role. DANS has developed training materials addressing practical challenges in sharing sensitive data.<\/span>\u00a0<\/span><\/p>\n Non-personal sensitive data (SANE).<\/span><\/b><\/a> Sharing field notes<\/a>. Ethics and CARE principles<\/a>.<\/span><\/b> [\/et_pb_accordion_item][et_pb_accordion_item title=”Do you develop training materials yourself? ” _builder_version=”4.10.7″ _module_preset=”default” background_color=”#E4F9FF” background_enable_color=”on” global_colors_info=”{}” open=”on”]<\/p>\n Develop learning materials that are more findable, accessible and reusable, and align with existing practices in the community.<\/span>\u00a0<\/span>The FAIR-by-Design methodology applies FAIR principles to the development and management of training materials, supporting structured documentation and enabling reuse and adaptation.<\/span>\u00a0<\/span><\/p>\n FAIR-by-Design methodology<\/span><\/b><\/a>. [\/et_pb_accordion_item][\/et_pb_accordion][et_pb_text _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n The DANS Training Team supports researchers and data professionals in the sustainable management, sharing and reuse of research data. The team combines expertise in research data management, FAIR and data curation, and develops training and materials for a range of audiences.\u00a0<\/p>\n <\/p>\n Would you like to use these materials in your own training or learn more about the possibilities?\u00a0 We also welcome suggestions for materials you find valuable for FAIR training.\u00a0<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.10.7″ _module_preset=”default” global_colors_info=”{}”][et_pb_button button_url=”https:\/\/dans.knaw.nl\/en\/training\/#trainingtopics” button_text=”Back to Training Topics” button_alignment=”center” module_class=”btn_red_arrow” _builder_version=”4.10.7″ _module_preset=”default” custom_button=”on” button_text_color=”#FFFFFF” button_bg_color=”#DC241F” button_border_width=”1px” button_border_radius=”8px” button_icon_color=”#FFFFFF” custom_margin=”-60px||||false|false” global_colors_info=”{}” button_icon_color__hover_enabled=”on|desktop”][\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Open and FAIR dataOpen data is a movement within open science that works to ensure that data are openly accessible, exploitable, editable and shared by anyone for any purpose.\u00a0Open data are licensed under an open licence. In 2014 the open data movement was strengthened by the introduction of the FAIR data principles. This acronym stands […]<\/p>\n","protected":false},"author":8,"featured_media":0,"parent":19846,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"class_list":["post-19599","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nTools and training materials on open & FAIR data<\/h1>\n
Getting started with FAIR<\/h2>\n
This module provides a practical introduction to FAIR and research data management. It covers key concepts such as metadata, documentation and structuring datasets, and can be used for self-study or integrated into training.<\/p>\n
This advanced module focuses on applying FAIR in practice. It addresses more complex topics such as metadata, interoperability and selecting appropriate repositories, and supports integration into existing workflows.\u00a0Access to the eLearning modules requires an account; the content is freely available after registration.<\/p>\n
The OpenPlato catalogue provides a broader range of eLearning modules on research data management, open science and FAIR, helping you identify further training aligned with your needs.\u00a0All materials are published under a CC-BY licence and are available for reuse in your own training activities.\u00a0Start with the introductory module and use the eLearning modules to deepen your understanding or apply FAIR in practice.<\/p>\n
<\/span>This guide provides practical steps and examples to make qualitative data more findable and reusable.<\/span>\u00a0<\/span><\/p>\n
<\/span>These materials, developed following a workshop at the Dutch Open Science Festival, offer insights into current challenges and approaches related to qualitative data.<\/span>\u00a0<\/span><\/p>\n
<\/span>These materials explore solutions for sharing sensitive data through secure environments such as Secure Analysis Environments (SANE).<\/span>\u00a0<\/span><\/p>\n
<\/span><\/b><\/span><\/span><\/a>This training focuses on the challenges of documenting and sharing field notes, which are often context-dependent and sensitive.<\/span>\u00a0<\/span><\/p>\n
<\/span>These materials address ethical considerations and the application of CARE principles in data sharing.<\/span>\u00a0<\/span><\/p>\n
<\/span>The methodology provides practical guidance and examples to support the development of FAIR-aligned training materials.<\/span>\u00a0<\/span>Apply this approach when developing or refining your own training materials.<\/span>\u00a0<\/span><\/p>\nAbout the DANS Training Team\u00a0<\/b><\/h3>\n
Get in touch\u00a0<\/b><\/h4>\n
Contact the DANS Training Team via email<\/a> or our contact form<\/a>.\u00a0<\/p>\n