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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)

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What is the emeScheme?

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What is it?

  • metadata Scheme
  • for Ecological Microcosm Experiments
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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
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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
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Why do we need it?

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Data Life Cylce

Adapted from https://www.dataone.org/data-life-cycle
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  • 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)

Data Life Cylce

Adapted from https://www.dataone.org/data-life-cycle

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  • 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

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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

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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
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What is FAIR?

  • Findable
  • Accessible
  • Interoperable
  • Re-usable

See https://www.force11.org/group/fairgroup/fairprinciples for a detailed description.

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  • 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!

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Data Levels

  • Raw Data

    • videos
    • images
    • count data from manual count
  • Extracted data

    • bemovi
    • extracted size distributions
    • extracted count / density data
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Metadata levels

  • Experiment
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Metadata levels

  • Experiment

  • Treatment

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Metadata levels

  • Experiment

  • Treatment

  • Sampling

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Metadata levels

  • Experiment

  • Treatment

  • Sampling

  • Measurement Raw Data

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Metadata levels

  • Experiment

  • Treatment

  • Sampling

  • Measurement Raw Data

  • Data DataExtraction Extracted Data

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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

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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

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What is the emeScheme?

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