contexere 0.5

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Scientists and engineer create a multitude of digital artefacts during their daily work:

• experimental results,

• simulation results,

• literate programming notebooks analysing experiments and simulations

• statistical models,

• machine learning models,

• figures,

• tables, etc

In order to trace and track these multiple interconnected research artefacts, hierarchical naming schemes are a powerful tool to document the connection between research artefacts, find previous research outputs, and enable reproducible research [1].

The following naming scheme has evolved over several years to track research artefacts of all kinds.

The general scheme is: DSyymd[hMM]e[_x]__title

• DS: Project specific initials. Here, DS stands for Data Science.

• yy: [0-9][0-9] are the last two digits of the years in the 21st century. I won’t live beyond that. So, I do not care for following centuries.

• m: [o-z] these letters map to the respective months.

• d: [1-9,A-V] represent the 31 days of a month. Digits and upper-case characters have approximately the same height, such that this element gives a visual structure to the name, which divides the date from the daily counter.

• h: [a-x] these optional letters refer to the hours of the day

• MM: [0-5][0-9] are the minutes with 00 encoding the full hour

• e: [a-z]+ daily counter as lower-case letter enumerating the respective database or dataset. The 28th dataset would start with be enumerated as aa.

• x: Optional attribute being the last significant characters of the dataset, from which DSyymde is derived.

• title: Readable name of the respective data set with whitespaces being replaced by underscores.

month m	day d	day d	day d	hour h	hour h
o	January	1	1	B	11	L	21	0	a	12	m
p	February	2	2	C	12	M	22	1	b	13	n
q	March	3	3	D	13	N	23	2	c	14	o
r	April	4	4	E	14	O	24	3	d	15	p
s	May	5	5	F	15	P	25	4	e	16	q
t	June	6	6	G	16	Q	26	5	f	17	r
u	July	7	7	H	17	R	27	6	g	18	s
v	August	8	8	I	18	S	28	7	h	19	t
w	September	9	9	J	19	T	29	8	i	20	u
x	October	A	10	K	20	U	30	9	j	21	v
y	November					V	31	10	k	22	w
z	December							11	l	23	x

• The first dataset created on Friday 01.01.2021 would be named DS21o1a.

• The second dataset created on the same day would be named DS21o1b.

• An analysis (e.g. Jupyter notebook) of the first data set started after the second data set had been created would be named DS21o1c_a. Exported figures of this analysis should be named DS21o1c_a__[plottype].[filetype].

• An analysis of data set DS21o1b started on 2nd January should be named DS21o2a_1b.

• An meta analysis of DS21o1c_a and DS21o2a_1b started on 11th February should be named DS21pBa_o1c_2a.

Installation

The module contexere can be installed from PyPi:

pip install contexere

Usage

The project provides the command line tool name:

usage: name [-h] [--version] [-n] [-p PROJECT] [-s] [-t] [-v] [-vv] [path]

Suggest name for research artefact

positional arguments:
  path                  Path to folder with research artefacts (default:
                        current working dir)

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  -n, --next            Suggest next artefact name
  -p PROJECT, --project PROJECT
                        Specify project abbreviation
  -s, --summary         Sumarize files following the naming convention
  -t, --time            add time abbreviation
  -u, --utc             Generate timestamp with respect to UTC (default is local timezone)
  -v, --verbose         set loglevel to INFO
  -vv, --very-verbose   set loglevel to DEBUG

Calling the tool without any arguments returns the date abbreviation of today:

name
24xV

Adding the option --time also abbreviates the actual time:

name --time
24xVj36

In an empty folder, a file name is suggested by specifying a project abbreviation and the --next option:

mkdir test_folder
cd test_folder
name --project DS --next
DS24xVa

After the creation of the first file, only the --next option needs to be provided to get another file name suggestion:

touch DS24xVa__test.dat
name --next
DS24xVb

Let’s assume that DS24xVb is the name of a Jupyter notebook, which analyses results created by DS24xVa.py. You can reflect this relation by actually naming the notebook DS24xVb_xVa__anlysis.ipynb to reflect its relation to DS24xVa.py. However, simplifying the name by removing redundant elements of the reference DS24xVb_a__anlysis.ipynb is even more efficient.

References

[1] Martin Kühne and Andreas W. Liehr. Improving the traditional information management in natural sciences. Data Science Journal, 8(1):18–26, 2009. doi: 10.2481/dsj.8.18.