6  Make Your Data Software Ready

Those sharing or managing data can take small steps to make them “software ready.” These include using non-proprietary formats, structuring tables with specific columns and entries, including standards for information about time, place, and organism.

6.1 Use non-proprietary formats

What is it?

Non-proprietary file formats do not require specific software and can be accessed without licenses and within different software systems.For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format compared to the proprietary .xlsx format.

Why?

  • Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms

  • Aligns better with the FAIR data principles

  • Makes data more socially equitable, supporting open science

  • Many applications (e.g. Microsoft Office) allow exporting into multiple formats, which makes it easy to share data in non-proprietary formats even if it was created using proprietary software.

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6.2 Structure tabular data in tidy/long format

What is it?

Long (or sometimes called “tidy”) format for tabular data can best be described as having one observation per row.

The following example shows two different formats – wide and long – of the same data. Notice that while sites 1, 2, and 3 are the column names filled with counts for each species in the wide format, site and count become the column names in long format.

Why?

  • The clear structure makes data more machine readable, particularly with commonly-used analytical software.

  • Data are as atomic as possible (e.g. no mixed types in one field)

  • It is easier to aggregate data across multiple files

Example of Wide Format

species

site_01

site_02

site_03

Tilia americana

3

3

5

Pinus strobus

1

0

2

Example of Long Format

species

site

count

Tilia americana

site_01

0

Tilia americana

site_02

1

Tilia americana

site_03

0

Pinus strobus

site_01

2

Pinus strobus

site_02

5

Pinus strobus

site_03

3

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6.3 Follow ISO 8601 for dates

What is it?

ISO 8601 is a convention for dates and times, where dates are listed as YYYY-MM-DD and time is given in Coordinated Universal Time (UTC, Zulu, or GMT) which is the time standard, relative to 0o longitude, that regulates global clocks.

The following table outlines how to write dates, times, and time intervals using ISO 8601:

Examples: April 3, 2023 standardized to ISO 8601

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

Examples: different styles of timezone annotation

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

https://imgs.xkcd.com/comics/iso_8601.png

Why?

  • Internationally accepted format used across multiple schemas (e.g. Darwin Core, EML, ISO 19115)
  • Removes ambiguity related to timezone, daylight savings time changes, and time of day
  • Better software integration of time date/time elements

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6.4 Match scientific names to a taxonomic authority

What is it?

A taxonomic authority is defined here as an online resource that maintains up-to-date species-level classification information and provides persistent identifiers (ID) for taxonomic classifications.

Example: For the species Balaenoptera borealis (Lesson, 1828), the WoRMS taxonomic authority ID link is https://www.marinespecies.org/aphia.php?p=taxdetails&id=137088 and the Life Science Identifier (LSID) is urn:lsid:marinespecies.org:taxname:137088.

Some important considerations:

  • Consider where you want to publish your data and use the existing taxonomic authority (e.g. World Register of Marine Species, Integrated Taxonomic Information System, NCBI taxonomy) used in that repository

  • Include the authority who manages said information in your metadata.

  • Make yourself aware of the structure, limits, and history of the authority you are using.

  • Adopt standard binomial nomenclature, when possible.

  • When possible, reference the unique identifier in addition to the nomenclature.

  • Always save and document the originally recorded name.

  • Put notes about identification uncertainty in a separate column.

  • Many authorities have APIs to facilitate matching names to identifiers.

Why?

  • To integrate or aggregate datasets, we need a common frame of reference for taxonomic name
  • Provides an anchor for the taxonomy as scientific understanding evolves.

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6.5 Record latitude and longitude in decimal degrees in WGS84

What is it?

WGS84 is a coordinate reference system that clarifies location. Recording latitude and longitude coordinates in decimal degrees (DD), rather than degrees-minutes-seconds (DMS) or decimal-minutes (DM or DDM) standardizes them to be more machine and human readable. Degrees West and South are negative in decimal degrees, and longitude can range from -180 to 180, and longitude -90 to 90. Below are example coordinates in each format. Once locations are recorded in DD, the number of decimal places included should be adjusted to match the precision of the observation.

Example Coordinates

Format

Example

Decimal Degrees (DD)

30.50833333

Degrees Minutes Seconds (DMS)

30° 15' 10 N

Degrees Decimal Minutes (DM or DDM)

30° 15.1667 N

https://imgs.xkcd.com/comics/coordinate_precision.png

Why?

  • Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.
  • Decimal-degrees avoids special symbols (° or ) which is preferable for machine readable formats
  • WGS84 is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.

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6.6 Use persistent unique identifiers

Why?

  • It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.
  • To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.
  • Although it increases workload, it safeguards against confusion and inefficiency in the future.

Key Information

  • There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.
  • One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. Station_95_Date_09JAN1997:14:35:00.000)
  • Some prefer using opaque identifiers. (e.g. 10FC9784-B30F-48ED-8DB5-FF65A2A9934E)
  • If there is an existing persistent unique identifier, it’s usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).
  • It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).
  • Important that it be persistent (consider samples possibly moving between institutions)

Examples of PIDs

Type of PID

Use Case

Example

Digital Object Identifier (DOI)

Actionable persistent link for papers, data, and other digital objects

https://doi.org/10.6084/m9.figshare.16806712.v2

International Geo Sample Number (IGSN)

Persistent identifier for physical samples

http://igsn.org/AU1243>

Life Science Identifier (LSID)

Persistent structured method for biologically significant data

urn:lsid:marinespecies.org:taxname:218214

Open Researcher and Contributor ID (ORCID)

Persistent actionable link for individuals

https://orcid.org/0000-0002-4391-107X

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