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Living with Machines GitHub Statistics report

This report provides some high level statistics about GitHub repositories contained under the Living with Machines Organization. The report is mainly intended to provide some stats to aid in reporting to our funder.

Contents

• Report details
• Report statistics
  • Overview of repositories
  • Repository file content
  • Stars and Forks
  • Views
  • Clones

Report details

This report is updated automatically every week, last generated on: 2023-09-18

Repository Statistics

The rest of this document outlines some high level stats for GitHub repositories under the Living with Machines GitHub Organization.

Overview of repositories

Currently Living with Machines has the following public repositories:

	Repositories
1	lwm_ARTIDIGH_2020_OCR_impact_downstream_NLP_tasks
2	lwm_GIR19_resolving_places
3	D3_JS_viz_in_a_Python_Jupyter_notebook
4	alto2txt
5	DeezyMatch
6	LwM_SIGSPATIAL2020_ToponymMatching
7	histLM
8	AzureAudit
9	maps-at-scale-hack-day-notebooks
10	deduplify
11	station-to-station
12	TargetedSenseDisambiguation
13	AtypicalAnimacy
14	nnanno
15	computer-vision-DHNordic-2020-workshop
16	maps-at-scale-using-computer-vision-and-jupyte...
17	TheLivingMachine
18	gh_orgstats
19	GazFuse
20	github_stats_report
21	nnanno_example_data
22	hmd_newspaper_dl
23	PressPicker_public
24	Computer-Vision-for-the-Humanities-workshop
25	Jupyter-Notebooks-The-Weird-and-Wonderful
26	PressDirectories
27	T-Res
28	jisc-wrangler
29	MapReader
30	.github
31	genre-classification
32	subsamplr
33	lwmdb
34	image-search
35	zoonyper
36	zooniverse-analysis-workshop
37	dhoxss-text2tech
38	DiachronicEmb-BigHistData
39	hmd_url_generator
40	DeezyMatch_tutorials
41	accidents-interactive
42	machines-interactive
43	ERWT
44	alto2txt2fixture
45	dated-translator
46	ai4lam-huggingface-datasets-demo
47	wrangle-ukds-trade-directories
48	label-studio-converter
49	OS_jpg_to_geotiff
50	VisualisingPressDirectories

Additionaly Living with Machines has 38 private repositories which have not yet been published

Repository file content

This section provides an overview of what type of content is in Living with Machines repositories by looking at the file extension counts note that these counts are based only on default branches so will under count for private repositories

Number of Jupyter notebooks

Living with Machines has promised a particular focus on making methods available to other researchers, one way in which the project is aiming to this is through the production of Jupyter notebooks.

Living with Machines currently has 174 Jupyter notebooks in public repositories and 86 in private repositories.

File extensions counts by repository

File extensions by repository

This chart shows the number and type of files for each public Living with Machines repository note that this only considers files on the default branch of the repository. We also don't include .jpg files or .json files since these are often used as for storing data.

Stars and Forks

Stars are a GitHub feature which allows registered GitHub users to 'bookmark' a repository. A GitHub fork indicates that someone has made a copy of the repository into their own account. Since stars and forks are only relevant for public repos we only report these below

	stars	forks
lwm_ARTIDIGH_2020_OCR_impact_downstream_NLP_tasks	9	2
lwm_GIR19_resolving_places	7	3
D3_JS_viz_in_a_Python_Jupyter_notebook	12	3
alto2txt	8	1
DeezyMatch	109	31
...	...	...
wrangle-ukds-trade-directories	0	0
label-studio-converter	3	0
OS_jpg_to_geotiff	0	0
VisualisingPressDirectories	0	0
Total	332	91

51 rows × 2 columns

Views

GitHub provides owners of a repository with some traffic statistics, including view stats. These are broken into 'unique' and 'total' views.

Total Views

Living with Machines public repositories have generated 7731 total views to date with an average of 155 daily views

Views over time

The top chart shows us the total views over time by repository, the bottom histogram breaks this down by view type

A breakdown of total views for each public Living with Machines repository:

	total_views
.github	26
AtypicalAnimacy	281
AzureAudit	47
Computer-Vision-for-the-Humanities-workshop	120
D3_JS_viz_in_a_Python_Jupyter_notebook	195
DeezyMatch	1645
DeezyMatch_tutorials	146
DiachronicEmb-BigHistData	127
ERWT	23
GazFuse	22
Jupyter-Notebooks-The-Weird-and-Wonderful	98
LwM_SIGSPATIAL2020_ToponymMatching	275
MapReader	752
OS_jpg_to_geotiff	0
PressDirectories	174
PressPicker_public	122
T-Res	72
TargetedSenseDisambiguation	159
TheLivingMachine	14
VisualisingPressDirectories	3
accidents-interactive	1
ai4lam-huggingface-datasets-demo	13
alto2txt	197
alto2txt2fixture	35
computer-vision-DHNordic-2020-workshop	30
dated-translator	23
deduplify	277
dhoxss-text2tech	307
genre-classification	198
gh_orgstats	286
github_stats_report	270
histLM	225
hmd_newspaper_dl	177
hmd_url_generator	72
image-search	53
jisc-wrangler	12
label-studio-converter	39
lwm_ARTIDIGH_2020_OCR_impact_downstream_NLP_tasks	127
lwm_GIR19_resolving_places	115
lwmdb	34
machines-interactive	2
maps-at-scale-hack-day-notebooks	65
maps-at-scale-using-computer-vision-and-jupyter-notebooks	119
nnanno	238
nnanno_example_data	29
station-to-station	250
subsamplr	129
wrangle-ukds-trade-directories	0
zooniverse-analysis-workshop	101
zoonyper	3

Unique views

Unique views aim to not count the same person visiting a repository multiple times

Living with Machines public repositories have generated 1953 unique views to date with an average of 39 daily views per repository

A breakdown of total unique views for each public Living with Machines repository:

	unique_views
.github	7
AtypicalAnimacy	73
AzureAudit	22
Computer-Vision-for-the-Humanities-workshop	59
D3_JS_viz_in_a_Python_Jupyter_notebook	76
DeezyMatch	349
DeezyMatch_tutorials	23
DiachronicEmb-BigHistData	19
ERWT	4
GazFuse	12
Jupyter-Notebooks-The-Weird-and-Wonderful	51
LwM_SIGSPATIAL2020_ToponymMatching	57
MapReader	126
OS_jpg_to_geotiff	0
PressDirectories	30
PressPicker_public	59
T-Res	6
TargetedSenseDisambiguation	47
TheLivingMachine	5
VisualisingPressDirectories	1
accidents-interactive	1
ai4lam-huggingface-datasets-demo	4
alto2txt	41
alto2txt2fixture	4
computer-vision-DHNordic-2020-workshop	14
dated-translator	5
deduplify	79
dhoxss-text2tech	45
genre-classification	53
gh_orgstats	56
github_stats_report	73
histLM	76
hmd_newspaper_dl	43
hmd_url_generator	14
image-search	20
jisc-wrangler	2
label-studio-converter	8
lwm_ARTIDIGH_2020_OCR_impact_downstream_NLP_tasks	66
lwm_GIR19_resolving_places	56
lwmdb	6
machines-interactive	2
maps-at-scale-hack-day-notebooks	21
maps-at-scale-using-computer-vision-and-jupyter-notebooks	65
nnanno	63
nnanno_example_data	8
station-to-station	49
subsamplr	33
wrangle-ukds-trade-directories	0
zooniverse-analysis-workshop	18
zoonyper	3

Clones

Clones indicate how often a repository is 'downloaded' from GitHub:

Cloning a repository pulls down a full copy of all the repository data that GitHub has at that point in time, including all versions of every file and folder for the project.

Clones are on way in which we may also be able to assess whether people are making use of a repository. Like views, clones are also broken down into unique and total values.

Total Clones

Living with Machines public repositories have generated 13285 clones to date with an average of 266 daily clones

Clones over time across all repositories

Total clones counts by repository

		Clone counts
lwm_ARTIDIGH_2020_OCR_impact_downstream_NLP_tasks	total_clones	126
	unique_clones	106
lwm_GIR19_resolving_places	total_clones	121
	unique_clones	92
D3_JS_viz_in_a_Python_Jupyter_notebook	total_clones	769
...	...	...
label-studio-converter	unique_clones	36
OS_jpg_to_geotiff	total_clones	2
	unique_clones	2
VisualisingPressDirectories	total_clones	8
	unique_clones	4

100 rows × 1 columns