- Understand the concept of metadata
- Understand the different kinds of metadata
- Get an introduction to the Ecological Metadata Language
6 February 2023
“data that provides information about other data”
“shorthand representation of the data to which they refer”
Metadata benefits science by
increased data longevity
Metadata benefits science by
increased data longevity
increased data reuse & sharing
Metadata benefits science by
increased data longevity
increased data reuse & sharing
expanded scales/scopes of analyses
Descriptive metadata is information about a resource that is used for searching & identification
Structural metadata indicates how 2+ objects are connected
Structural metadata are often conceptualized in an entity–relationship model
An entity can be physical or logical
Entities are connected via a relationship
ER models are usually drawn as boxes (entities) connected by lines (relationships)
Administrative metadata refers to technical info about a data file
.csv
)Information about the contents and quality of statistical data
Describes the collection and any processing of the data
Information about improved access to data
Two factors to consider
effort involved in creating the metadata
value derived from it
In general, assume that “more is better”
EML describes a range of essential aspects of ecological data
EML reduces ambiguity & uncertainty by formalizing metadata concepts
General dataset
Geographic
Temporal
Taxonomic
Methods
Data table
Contains concepts that
Contains information about where
Contains information about when
Contains information about
Contains information about what happened
Contains information about what happened
Unlike the Methods section of a publication, fully detailed descriptions can be included
Contains information about a rectangular table
date
)numeric
, character
)BVA = Bear Valley Creek
Length
is a positive, real valueThe KNB is an international repository intended to facilitate ecological & environmental research
Provides read & write access to data and metadata from DataONE network
## username me <- list(individualName = list(givenName = "Mark", surName = "Scheuerell")) ## list of attributes my_eml <- list( dataset = list( title = "A Minimal Valid EML Dataset", creator = me, contact = me ) ) ## inspect the EML my_eml
$dataset $dataset$title [1] "A Minimal Valid EML Dataset" $dataset$creator $dataset$creator$individualName $dataset$creator$individualName$givenName [1] "Mark" $dataset$creator$individualName$surName [1] "Scheuerell" $dataset$contact $dataset$contact$individualName $dataset$contact$individualName$givenName [1] "Mark" $dataset$contact$individualName$surName [1] "Scheuerell"
We’ll discuss data analysis and visualization