FAIR Research¶
About the DDH Community Data Wiki¶
The aim of the DDH Community Data Wiki is to articulate the Data Wheel framework into a practical and actionable FAIR data and software workflow. Through ongoing community contributions and support, this resource will grow to help researchers defining and recommending processes and tools for geographic and historic data collection, data verification, data publishing, as well as analysis, source management, and more.
The pages contain links to learning resources and popular programming libraries and packages (collections of ready-made functions) in geospatial analysis, as well as hands-on demonstrations of how to transition to a more reproducible workflow by collecting, preparing, analysing, visualising and sharing data. See the FAIR data and software section for information on including metadata and documentation to help make your research outputs Findable, Accessible, Interoperable and Reusable.
Use the menu bar to navigate to each section of the Wiki. Have fun! :)
Figure 1. The Data Wheel methodology (by Carola Hein and the Delft Digital Humanities group at Delft University of Technology).
What is FAIR data and software?¶
From openaire.eu: “The FAIR principles describe how research outputs should be organised so they can be more easily accessed, understood, exchanged and reused. Major funding bodies, including the European Commission, promote FAIR data to maximise the integrity and impact of their research investment.” FAIR stands for Findable, Accessible, Interoperable, and Reusable/Reproducible.
Resources to learn more about the FAIR principles and how to apply them:
The GO FAIR community, which has been working towards implementations of the FAIR Guiding Principles since 2018
How to Make your Data FAIR - guide for researchers by OpenAIRE.eu
Guidelines on FAIR Data Management in Horizon 2020 from the European Commission (PDF)
The FAIR guiding principles¶
Source: https://doi.org/10.1038/sdata.2016.18
To be Findable:
F1. (meta)data are assigned a globally unique and persistent identifier (DOI)
F2. data are described with rich metadata (defined by R1 below)
F3. metadata clearly and explicitly include the identifier of the data it describes
F4. (meta)data are registered or indexed in a searchable resource
To be Accessible:
A1. (meta)data are retrievable by their identifier using a standardized communications protocol
A1.1. the protocol is free, open and universally implementable
A1.2. the protocol allows for an authentication and authorization procedure, where necessary
A2. metadata are accessible, even when the data are no longer available
To be Interoperable:
I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation
I2. (meta)data uses vocabularies that follow FAIR principles
I3. (meta)data include qualified references to other (meta)data
To be Reusable:
R1. (meta)data are richly described with a plurality of accurate and relevant attributes
R1.1. (meta)data are released with a clear and accessible data usage license
R1.2. (meta)data are associated with data provenance
R1.3. (meta)data meet domain relevant community standards
Disciplinary metadata¶
Data Documentation Initiative (DDI)¶
“While data curators, and increasingly researchers, know that good metadata is key for research data access and re-use, figuring out precisely what metadata to capture and how to capture it is a complex task. Fortunately, many academic disciplines have supported initiatives to formalise the metadata specifications the community deems to be required for data re-use. This page [by the Data Documentation Initiative] provides links to information about these disciplinary metadata standards, including profiles, tools to implement the standards, and use cases of data repositories currently implementing them.” Also see this full list of metadata standards per discipline maintained by the DDI.
ISO metadata standards¶
The International Organisation for Standardization (ISO) is the largest developer and publisher of international standards. International standards are used like OGC standards to make sure industry works efficiently, and information and data are interoperable making it easier, quicker and more reliable to share and to control. ISO formed in 1947 and has a library of 19 500 standards covering a wide range of sectors. ISO also develops and publishes metadata standards, the ones relevant to the geospatial sector include:
FGDC metadata standards¶
FGDC stands for Federal Geographic Data Committee (FGDC) and is a committee that promote coordinated development, use, sharing and dissemination of geospatial data on a national basis in the US. One of FGDC’s principal tasks is to develop and assist in the adaptation, development and delivery of metadata standards.
FGDC were responsible for the metadata standards program called the Content Standard for Digital Geospatial Metadata (CSDGM) that has been a long standing metadata standard that is used by many organisations. However, the FGDC now endorses the transition of metadata standards to ISO metadata standards.
Dublin Core Metadata Initiative (DCMI) standards¶
The Dublin Core Metadata Initiative is an open, public and not-for-profit organisation which aims to develop, support and share metadata in an appropriate standard system that enhances the provision of resources like geographical information. DCMI manages creation and development of Metadata standard specifications and terms as well as training resources based around metadata best practice. These are among several other tasks the DCMI takes part in. DCMI developed standards that follow an Element set that is made up of 15 properties that are to always be used within resource description (i.e. metadata). The 15 properties are described in Table 1.
Table 1. DCMI Element Set used within resource description. Source: DCMI Element Set Version 1.1 Website (http://dublincore.org/documents/dces/).
INSPIRE metadata standards¶
The INSPIRE directive, which began in 2007, aims to provide a European Union (EU) spatial data infrastructure (SDI) that will be able to improve access to spatial data within several environmental sectors. The information about INSPIRE was covered in unit 1, so if you want to know more you can refer back to that unit.
Metadata is a big part of the INSPIRE directive, which means that metadata standards are also an important part as well. INSPIRE metadata standards have been chosen from existing standard types and are the ones seen as being the most important and efficient. The metadata standards that are INSPIRE compliant includes:
Learn more¶
Much of the above information on Metadata Standards for Geospatial Data comes from this Course on Open Geospatial Consortium standards by Dominic Taylor and Joseph McGenn is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License