STRADITIZE: An open-source program for digitizing pollen diagrams and other types of stratigraphic data
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Download: straditize-presentation-EGU2018.pdf (6539.75 [Ko])
State: Public
Version: Final published version
State: Public
Version: Final published version
Secondary document(s)
Download: Abstract-EGU2018-4433.pdf (33.57 [Ko])
State: Public
Version: Final published version
State: Public
Version: Final published version
Serval ID
serval:BIB_4217A04E8AE4
Type
Inproceedings: an article in a conference proceedings.
Publication sub-type
Poster: Summary – with images – on one page of the results of a researche project. The summaries of the poster must be entered in "Abstract" and not "Poster".
Collection
Publications
Institution
Title
STRADITIZE: An open-source program for digitizing pollen diagrams and other types of stratigraphic data
Title of the conference
EGU General Assembly Conference Abstracts
Publication state
Published
Issued date
10/04/2018
Abstract
In an age of digital data analysis, gaining access to data from the pre-digital era – or any data that is only available
as a figure on a page – remains a problem and an under-utilized scientific resource. Whilst there are numerous
programs available that allow the digitization of scientific data in a simple x-y graph format, we know of no
semi-automated program that can deal with data plotted with multiple horizontal axes that share the same vertical
axis, such as pollen diagrams and other stratigraphic figures that are common in the Earth sciences. STRADITIZE
(Stratigraphic Diagram Digitizer) is a new open-source program that allows stratigraphic figures to be digitized
in a single semi-automated operation. It is designed to detect multiple plots of variables analyzed along the same
vertical axis, whether this is a sediment core or any similar depth/time series.
The program is written in python and supports mixtures of many different diagram types, such as bar
plots, line plots, as well as shaded, stacked, and filled area plots. The package provides an extensively documented
graphical user interface for a point-and-click handling of the semi-automatic process, but can also be scripted
or used from the command line. Other features of STRADITIZE include text recognition to interpret the names
of the different plotted variables, the automatic and semi-automatic recognition of picture artifacts, as well an
automatic measurement finder to exactly reproduce the data that has been used to create the diagram. Evaluation
of the program has been undertaken comparing the digitization of published figures with the original digital data.
This generally shows very good results, although this is inevitably reliant on the quality and resolution of the
original figure.
as a figure on a page – remains a problem and an under-utilized scientific resource. Whilst there are numerous
programs available that allow the digitization of scientific data in a simple x-y graph format, we know of no
semi-automated program that can deal with data plotted with multiple horizontal axes that share the same vertical
axis, such as pollen diagrams and other stratigraphic figures that are common in the Earth sciences. STRADITIZE
(Stratigraphic Diagram Digitizer) is a new open-source program that allows stratigraphic figures to be digitized
in a single semi-automated operation. It is designed to detect multiple plots of variables analyzed along the same
vertical axis, whether this is a sediment core or any similar depth/time series.
The program is written in python and supports mixtures of many different diagram types, such as bar
plots, line plots, as well as shaded, stacked, and filled area plots. The package provides an extensively documented
graphical user interface for a point-and-click handling of the semi-automatic process, but can also be scripted
or used from the command line. Other features of STRADITIZE include text recognition to interpret the names
of the different plotted variables, the automatic and semi-automatic recognition of picture artifacts, as well an
automatic measurement finder to exactly reproduce the data that has been used to create the diagram. Evaluation
of the program has been undertaken comparing the digitization of published figures with the original digital data.
This generally shows very good results, although this is inevitably reliant on the quality and resolution of the
original figure.
Publisher's website
Create date
01/05/2018 15:32
Last modification date
21/08/2019 7:09