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Add a datamap

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The data file I added contained multiple columns, but in the assay annotation, I just pointed to the file. Is there a way to specify which column belongs to which sample?

Yes! For this, you can make use of data fragment selectors.

There exist various different file formats and each requires its own format for annotating fragments as well. In this case, we have a tabular file format, for which our tooling provides help.

Point into results – Fragment selectors

Section titled Point into results – Fragment selectors

We will now add fragment selectors to the previously created annotation table to connect our sample to specific data points. This way, provenance is persistently tracked. Data scientists down the line will thank you for the increase in machine-actionability.

ARCitect

  1. In the “SugarMeasurement” assay, open the “Sugar Measurement” table

  2. On top of the annotation table, open the “Data Annotator” tool

  3. Click Choose a file, find and select sugar_result.csv and click Open

  4. On top switch from “autodetect” to “output”

  5. Select only the 6(!) Data columns (RT_M1, RT_M2, RT_M3, Cold_M1, Cold_M2, Cold_M3). These are the direct results of the 6 samples.

  6. Click Submit

    Input [Sample Name]Parameter […]Output [Data]Data FormatData Selector Format
    Cold1_sugar-extsugar_result.csv#col=2text/csvhttps://datatracker.ietf.org/doc/html/rfc7111
    Cold2_sugar-extsugar_result.csv#col=3text/csvhttps://datatracker.ietf.org/doc/html/rfc7111
    Cold3_sugar-extsugar_result.csv#col=4text/csvhttps://datatracker.ietf.org/doc/html/rfc7111
    RT1_sugar-extsugar_result.csv#col=5text/csvhttps://datatracker.ietf.org/doc/html/rfc7111
    RT2_sugar-extsugar_result.csv#col=6text/csvhttps://datatracker.ietf.org/doc/html/rfc7111
    RT3_sugar-extsugar_result.csv#col=7text/csvhttps://datatracker.ietf.org/doc/html/rfc7111

DataMAP: Annotation for the fragment selectors

Section titled DataMAP: Annotation for the fragment selectors
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Wow, this is very verbose, even though it only took a few clicks! And you say data scientists will now finally be content?

Yes, but with a final bit of annotation you might even raise a smile from them. Using data fragment selectors in the annotation table, you described the provenance between your samples and your data fragments.

In addition, you can further annotate these data fragments and even those which do not directly originate from any of the samples. For example, the column containing the names of the sugars. This annotation is done in the datamap.

We’ll now use the datamap to annotate all columns in the file, even the ones we didn’t cover in the annotation table.

ARCitect

  1. Go back to assay metadata (the sheet named Assay)

  2. In the Datamap section click Add Datamap to add a sheet Data Map

  3. Open the Data Map table sheet at the bottom

  4. Open the “Data Annotator” tool and select the same file (sugar_result.csv) as before.

  5. Click on Open Annotator and this time select all 7 columns and click Submit

  6. From the same file select all 7 columns

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    The first column of my result table “sugar_result.csv” contains the name of the measured sugar, that is the molecule name. The other six columns contain the measured data: molecule count in mmol / kg.

  7. Add the following annotation to describe what the columns in “sugar_result.csv”

    DataExplicationUnitObject Type
    sugar_result.csv#col=1molecule namestring
    sugar_result.csv#col=2molecule countMillimole per KilogramFloat
    sugar_result.csv#col=3molecule countMillimole per KilogramFloat
    sugar_result.csv#col=4molecule countMillimole per KilogramFloat
    sugar_result.csv#col=5molecule countMillimole per KilogramFloat
    sugar_result.csv#col=6molecule countMillimole per KilogramFloat
    sugar_result.csv#col=7molecule countMillimole per KilogramFloat