The emeScheme - an Introduction
What is it?
What is it for?
Why do we need it?
Rainer M Krug
Group Seminar 18/12/2018
(updated: 2018-12-17)
What is the emeScheme?
What is it?
- metadata Scheme
- for Ecological Microcosm Experiments
What is it?
- metadata Scheme
- for Ecological Microcosm Experiments
What does this metada scheme do?
- standardised structure
- standardised terminology / property names
- to describe the an Ecological Microcosm Experiment
What is it?
- metadata Scheme
- for Ecological Microcosm Experiments
What does this metada scheme do?
- standardised structure
- standardised terminology / property names
- to describe the an Ecological Microcosm Experiment
What is the metadata?
- Materials
- Conditions / Manipulations
- Measuring
- Data conversions
Why do we need it?
Plan: description of the data that will becompiled, and how the data will be managed and made accessible throughout its lifetime
Collect: observations are made either by hand or with sensors or other instruments and the data are placed a into digital form
Assure: the quality of the data are assured through checks and inspections
Analyze: data are analyzed
Preserve: data are submitted to an appropriate long-term archive (i.e. data center)
Discover: potentially useful data are located and obtained, along with the relevant information about the data
Integrate: data from disparate sources are combined to form one homogeneous set of data that can be readily analyzed
Describe: data are accurately and thoroughly described using the appropriate metadata standards
(metadata)
Plan: description of the data that will becompiled, and how the data will be managed and made accessible throughout its lifetime
Collect: observations are made either by hand or with sensors or other instruments and the data are placed a into digital form
Assure: the quality of the data are assured through checks and inspections
Describe: data are accurately and thoroughly described using the appropriate metadata standards
Preserve: data are submitted to an appropriate long-term archive (i.e. data center)
Discover: potentially useful data are located and obtained, along with the relevant information about the data (metadata)
Integrate: data from disparate sources are combined to form one homogeneous set of data that can be readily analyzed
Analyze: data are analyzed
Why do we want this?
Data should be archived
Data should be findable
Data is Re-usable
We can re-use other data
Why do we want this?
Data should be archived
Data should be findable
Data is Re-usable
We can re-use other data
Data should not disappear
Why do we want this?
Data should be archived
Data should be findable
Data is Re-usable
We can re-use other data
Data should not disappear
- Data should be FAIR
What is FAIR?
- Findable
- Accessible
- Interoperable
- Re-usable
See https://www.force11.org/group/fairgroup/fairprinciples for a detailed description.
To be Findable:
- F1. (meta)data are assigned a globally unique and eternally persistent identifier.
- F2. data are described with rich metadata.
- F3. (meta)data are registered or indexed in a searchable resource.
- F4. metadata specify the data identifier.
TO BE ACCESSIBLE:
- A1 (meta)data are retrievable by their identifier using a standardized communications protocol.
- A1.1 the protocol is open, free, 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 use vocabularies that follow FAIR principles.
- I3. (meta)data include qualified references to other (meta)data.
TO BE RE-USABLE:
- R1. meta(data) have 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 their provenance.
- R1.3. (meta)data meet domain-relevant community standards.
We need the emeScheme!
Data Levels
Raw Data
- videos
- images
- count data from manual count
Extracted data
- bemovi
- extracted size distributions
- extracted count / density data
Metadata levels
- Experiment
Metadata levels
Experiment
Treatment
Metadata levels
Experiment
Treatment
Sampling
Metadata levels
Experiment
Treatment
Sampling
Measurement ⇒ Raw Data
Metadata levels
Experiment
Treatment
Sampling
Measurement ⇒ Raw Data
Data DataExtraction ⇒ Extracted Data
Data Levels
Raw Data
- videos
- images
- count data from manual count
Extracted data
- bemovi
- extracted size distributions
- extracted count / density data
Metadata levels
Experiment
Treatment
Sampling
Measurement ⇒ Raw Data
Data DataExtraction ⇒ Extracted Data
Data Levels
Raw Data
- videos
- images
- count data from manual count
Extracted data
- bemovi
- extracted size distributions
- extracted count / density data
Metadata levels
Experiment
Treatment
Sampling
Measurement ⇒ Raw Data
Data DataExtraction ⇒ Extracted Data
Website of the emeScheme:
https://exp-micro-ecol-hub.github.io/emeScheme/
Presentation at:
https://rkrug.github.io/emeScheme_Introduction/The_emeScheme.html
