1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
|
%global _empty_manifest_terminate_build 0
Name: python-biolink-model
Version: 3.4.3
Release: 1
Summary: 'A high level datamodel of biological entities and associations'
License: BSD
URL: https://github.com/biolink/biolink-model
Source0: https://mirrors.aliyun.com/pypi/web/packages/50/0b/742b549ee4d3ece2a72e015ac240fe75dfea55be5e401d1a04b44e04ea19/biolink-model-3.4.3.tar.gz
BuildArch: noarch
Requires: python3-linkml
Requires: python3-curies
Requires: python3-prefixmaps
%description
[](https://img.shields.io/github/license/biolink/biolink-model)
[](https://img.shields.io/github/v/release/biolink/biolink-model?style=flat-square)
[](https://www.python.org/downloads/release/python-370/)
[](https://travis-ci.com/biolink/biolink-model)
[](https://zenodo.org/badge/latestdoi/112995625)
[](https://gitter.im/biolink-model/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
<img src="images/biolink-logo.png" width="20%">
# Biolink Model
Quickstart docs:
For a good overview of the biolink-model, [watch Chris Mungall's talk](https://www.youtube.com/watch?v=RE1hFm8lvJA&t=2s) at ICBO 2020.
- Browse the model: [https://biolink.github.io/biolink-model](https://biolink.github.io/biolink-model)
- [named thing](https://biolink.github.io/biolink-model/docs/NamedThing.html)
- [association](https://biolink.github.io/biolink-model/docs/Association.html)
- [predicate](https://biolink.github.io/biolink-model/docs/predicates.html)
Refer to the following resources for a quick introduction to the Biolink Model:
- [Introduction to the Biolink Datamodel](https://www.slideshare.net/cmungall/introduction-to-the-biolink-datamodel)
- [Biolink Model - A community driven data model for life sciences](https://bit.ly/biolink-model-workshop-biocuration-2020) (Biocuration 2020)
- Slides: https://bit.ly/biolink-model-workshop-biocuration-2020
- Video: https://www.youtube.com/watch?v=RE1hFm8lvJA
See also [Biolink Model Guidelines](guidelines/README.md) for help understanding, curating, and working with the model.
## Introduction
The purpose of the Biolink Model is to provide a high-level datamodel of
biological entities (genes, diseases, phenotypes, pathways, individuals, substances, etc),
their properties, relationships, and enumerate ways in which they can be associated.
The representation is independent of storage technology or metamodel (Solr documents, neo4j/property graphs,
RDF/OWL, JSON, CSVs, etc). Different mappings to each of these are provided.
The specification of the Biolink Model is a [single YAML file](biolink-model.yaml) built using [linkml](https://github.com/linkml).
The basic elements of the YAML are:
- Class Definitions: definitions of upper level *classes* representing both 'named thing' and 'association'
- Slot Definitions: definitions of *slots* (aka properties) that can be used to relate members of these classes to other classes or data types. Slots collectively refer to predicates, node properties, and edge properties
The model itself is being used in the following projects:
- [NCATS Biomedical Data Translator](https://ncats.nih.gov/translator)
- [Monarch Initiative](https://monarchinitiative.org/)
- [KG-COVID-19](https://github.com/Knowledge-Graph-Hub/kg-covid-19/wiki)
- [KG Microbe](https://github.com/Knowledge-Graph-Hub/kg-microbe)
- [Illuminating the Druggable Genome]()
## Organization
The main source of truth is [biolink-model.yaml](biolink-model.yaml). This is a YAML file that is intended to
be relatively simple to view and edit in its native form.
The yaml definition is currently used to derive:
- [JSON Schema](json-schema)
- [Python dataclasses](biolink/model.py)
- [Java code gen](java)
- [ProtoBuf definitions](biolink-model.proto)
- [GraphQL](biolink-model.graphql)
- [RDF](biolink-model.ttl)
- [OWL](biolink-model.owl.ttl)
- [RDF Shape Expressions](biolink-model.shex)
- [JSON-LD context](context.jsonld)
- [Graphviz](graphviz)
- [GOlr YAML schemas](golr-views)
- these can be compiled down to Solr XML schemas
- these are also intermediate targets used within the BBOP/AmiGO framework
- [Markdown documentation](docs)
## Make and build instructions
Prerequisites: Python 3.7+ and pipenv
To install pipenv,
```sh
pip3 install pipenv
```
To install the project,
```sh
make install
```
To regenerate artifacts from the Biolink Model YAML,
```sh
make
```
**Note:** the Makefile requires the following dependencies to be installed:
### jsonschema
[jsonschema](https://json-schema.org/)
Generally install using
```sh
pip3 install jsonschema
```
### jsonschema2pojo
[jsonschema2pojo](https://github.com/joelittlejohn/jsonschema2pojo)
If you are on a Mac, it can be installed using `brew`:
```sh
brew install jsonschema2pojo
```
For other OS environments, download the latest release then extract it into your execution path. eg
```sh
wget https://github.com/joelittlejohn/jsonschema2pojo/releases/download/jsonschema2pojo-1.0.2/jsonschema2pojo-1.0.2.tar.gz
tar -xvzf jsonschema2pojo-1.0.2.tar.gz
export PATH=$PATH:`pwd`/jsonschema2pojo-1.0.2/bin
```
### GraphViz
See [GraphViz site](https://graphviz.org/) for installation in your operating system.
## How do I use Biolink Model YAML programmatically?
For operations such as CURIE lookup, finding class by synonyms, get parents, get ancestors, etc. please make use of [biolink-model-toolkit](https://github.com/biolink/biolink-model-toolkit/). It provides convenience methods for traversing Biolink Model.
## Citing Biolink Model
Unni DR, Moxon SAT, Bada M, Brush M, Bruskiewich R, Caufield JH, Clemons PA, Dancik V, Dumontier M, Fecho K, Glusman G, Hadlock JJ, Harris NL, Joshi A, Putman T, Qin G, Ramsey SA, Shefchek KA, Solbrig H, Soman K, Thessen AE, Haendel MA, Bizon C, Mungall CJ, The Biomedical Data Translator Consortium (2022).
Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science. Clin Transl Sci. Wiley; 2022 Jun 6; https://onlinelibrary.wiley.com/doi/10.1111/cts.13302
%package -n python3-biolink-model
Summary: 'A high level datamodel of biological entities and associations'
Provides: python-biolink-model
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-biolink-model
[](https://img.shields.io/github/license/biolink/biolink-model)
[](https://img.shields.io/github/v/release/biolink/biolink-model?style=flat-square)
[](https://www.python.org/downloads/release/python-370/)
[](https://travis-ci.com/biolink/biolink-model)
[](https://zenodo.org/badge/latestdoi/112995625)
[](https://gitter.im/biolink-model/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
<img src="images/biolink-logo.png" width="20%">
# Biolink Model
Quickstart docs:
For a good overview of the biolink-model, [watch Chris Mungall's talk](https://www.youtube.com/watch?v=RE1hFm8lvJA&t=2s) at ICBO 2020.
- Browse the model: [https://biolink.github.io/biolink-model](https://biolink.github.io/biolink-model)
- [named thing](https://biolink.github.io/biolink-model/docs/NamedThing.html)
- [association](https://biolink.github.io/biolink-model/docs/Association.html)
- [predicate](https://biolink.github.io/biolink-model/docs/predicates.html)
Refer to the following resources for a quick introduction to the Biolink Model:
- [Introduction to the Biolink Datamodel](https://www.slideshare.net/cmungall/introduction-to-the-biolink-datamodel)
- [Biolink Model - A community driven data model for life sciences](https://bit.ly/biolink-model-workshop-biocuration-2020) (Biocuration 2020)
- Slides: https://bit.ly/biolink-model-workshop-biocuration-2020
- Video: https://www.youtube.com/watch?v=RE1hFm8lvJA
See also [Biolink Model Guidelines](guidelines/README.md) for help understanding, curating, and working with the model.
## Introduction
The purpose of the Biolink Model is to provide a high-level datamodel of
biological entities (genes, diseases, phenotypes, pathways, individuals, substances, etc),
their properties, relationships, and enumerate ways in which they can be associated.
The representation is independent of storage technology or metamodel (Solr documents, neo4j/property graphs,
RDF/OWL, JSON, CSVs, etc). Different mappings to each of these are provided.
The specification of the Biolink Model is a [single YAML file](biolink-model.yaml) built using [linkml](https://github.com/linkml).
The basic elements of the YAML are:
- Class Definitions: definitions of upper level *classes* representing both 'named thing' and 'association'
- Slot Definitions: definitions of *slots* (aka properties) that can be used to relate members of these classes to other classes or data types. Slots collectively refer to predicates, node properties, and edge properties
The model itself is being used in the following projects:
- [NCATS Biomedical Data Translator](https://ncats.nih.gov/translator)
- [Monarch Initiative](https://monarchinitiative.org/)
- [KG-COVID-19](https://github.com/Knowledge-Graph-Hub/kg-covid-19/wiki)
- [KG Microbe](https://github.com/Knowledge-Graph-Hub/kg-microbe)
- [Illuminating the Druggable Genome]()
## Organization
The main source of truth is [biolink-model.yaml](biolink-model.yaml). This is a YAML file that is intended to
be relatively simple to view and edit in its native form.
The yaml definition is currently used to derive:
- [JSON Schema](json-schema)
- [Python dataclasses](biolink/model.py)
- [Java code gen](java)
- [ProtoBuf definitions](biolink-model.proto)
- [GraphQL](biolink-model.graphql)
- [RDF](biolink-model.ttl)
- [OWL](biolink-model.owl.ttl)
- [RDF Shape Expressions](biolink-model.shex)
- [JSON-LD context](context.jsonld)
- [Graphviz](graphviz)
- [GOlr YAML schemas](golr-views)
- these can be compiled down to Solr XML schemas
- these are also intermediate targets used within the BBOP/AmiGO framework
- [Markdown documentation](docs)
## Make and build instructions
Prerequisites: Python 3.7+ and pipenv
To install pipenv,
```sh
pip3 install pipenv
```
To install the project,
```sh
make install
```
To regenerate artifacts from the Biolink Model YAML,
```sh
make
```
**Note:** the Makefile requires the following dependencies to be installed:
### jsonschema
[jsonschema](https://json-schema.org/)
Generally install using
```sh
pip3 install jsonschema
```
### jsonschema2pojo
[jsonschema2pojo](https://github.com/joelittlejohn/jsonschema2pojo)
If you are on a Mac, it can be installed using `brew`:
```sh
brew install jsonschema2pojo
```
For other OS environments, download the latest release then extract it into your execution path. eg
```sh
wget https://github.com/joelittlejohn/jsonschema2pojo/releases/download/jsonschema2pojo-1.0.2/jsonschema2pojo-1.0.2.tar.gz
tar -xvzf jsonschema2pojo-1.0.2.tar.gz
export PATH=$PATH:`pwd`/jsonschema2pojo-1.0.2/bin
```
### GraphViz
See [GraphViz site](https://graphviz.org/) for installation in your operating system.
## How do I use Biolink Model YAML programmatically?
For operations such as CURIE lookup, finding class by synonyms, get parents, get ancestors, etc. please make use of [biolink-model-toolkit](https://github.com/biolink/biolink-model-toolkit/). It provides convenience methods for traversing Biolink Model.
## Citing Biolink Model
Unni DR, Moxon SAT, Bada M, Brush M, Bruskiewich R, Caufield JH, Clemons PA, Dancik V, Dumontier M, Fecho K, Glusman G, Hadlock JJ, Harris NL, Joshi A, Putman T, Qin G, Ramsey SA, Shefchek KA, Solbrig H, Soman K, Thessen AE, Haendel MA, Bizon C, Mungall CJ, The Biomedical Data Translator Consortium (2022).
Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science. Clin Transl Sci. Wiley; 2022 Jun 6; https://onlinelibrary.wiley.com/doi/10.1111/cts.13302
%package help
Summary: Development documents and examples for biolink-model
Provides: python3-biolink-model-doc
%description help
[](https://img.shields.io/github/license/biolink/biolink-model)
[](https://img.shields.io/github/v/release/biolink/biolink-model?style=flat-square)
[](https://www.python.org/downloads/release/python-370/)
[](https://travis-ci.com/biolink/biolink-model)
[](https://zenodo.org/badge/latestdoi/112995625)
[](https://gitter.im/biolink-model/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
<img src="images/biolink-logo.png" width="20%">
# Biolink Model
Quickstart docs:
For a good overview of the biolink-model, [watch Chris Mungall's talk](https://www.youtube.com/watch?v=RE1hFm8lvJA&t=2s) at ICBO 2020.
- Browse the model: [https://biolink.github.io/biolink-model](https://biolink.github.io/biolink-model)
- [named thing](https://biolink.github.io/biolink-model/docs/NamedThing.html)
- [association](https://biolink.github.io/biolink-model/docs/Association.html)
- [predicate](https://biolink.github.io/biolink-model/docs/predicates.html)
Refer to the following resources for a quick introduction to the Biolink Model:
- [Introduction to the Biolink Datamodel](https://www.slideshare.net/cmungall/introduction-to-the-biolink-datamodel)
- [Biolink Model - A community driven data model for life sciences](https://bit.ly/biolink-model-workshop-biocuration-2020) (Biocuration 2020)
- Slides: https://bit.ly/biolink-model-workshop-biocuration-2020
- Video: https://www.youtube.com/watch?v=RE1hFm8lvJA
See also [Biolink Model Guidelines](guidelines/README.md) for help understanding, curating, and working with the model.
## Introduction
The purpose of the Biolink Model is to provide a high-level datamodel of
biological entities (genes, diseases, phenotypes, pathways, individuals, substances, etc),
their properties, relationships, and enumerate ways in which they can be associated.
The representation is independent of storage technology or metamodel (Solr documents, neo4j/property graphs,
RDF/OWL, JSON, CSVs, etc). Different mappings to each of these are provided.
The specification of the Biolink Model is a [single YAML file](biolink-model.yaml) built using [linkml](https://github.com/linkml).
The basic elements of the YAML are:
- Class Definitions: definitions of upper level *classes* representing both 'named thing' and 'association'
- Slot Definitions: definitions of *slots* (aka properties) that can be used to relate members of these classes to other classes or data types. Slots collectively refer to predicates, node properties, and edge properties
The model itself is being used in the following projects:
- [NCATS Biomedical Data Translator](https://ncats.nih.gov/translator)
- [Monarch Initiative](https://monarchinitiative.org/)
- [KG-COVID-19](https://github.com/Knowledge-Graph-Hub/kg-covid-19/wiki)
- [KG Microbe](https://github.com/Knowledge-Graph-Hub/kg-microbe)
- [Illuminating the Druggable Genome]()
## Organization
The main source of truth is [biolink-model.yaml](biolink-model.yaml). This is a YAML file that is intended to
be relatively simple to view and edit in its native form.
The yaml definition is currently used to derive:
- [JSON Schema](json-schema)
- [Python dataclasses](biolink/model.py)
- [Java code gen](java)
- [ProtoBuf definitions](biolink-model.proto)
- [GraphQL](biolink-model.graphql)
- [RDF](biolink-model.ttl)
- [OWL](biolink-model.owl.ttl)
- [RDF Shape Expressions](biolink-model.shex)
- [JSON-LD context](context.jsonld)
- [Graphviz](graphviz)
- [GOlr YAML schemas](golr-views)
- these can be compiled down to Solr XML schemas
- these are also intermediate targets used within the BBOP/AmiGO framework
- [Markdown documentation](docs)
## Make and build instructions
Prerequisites: Python 3.7+ and pipenv
To install pipenv,
```sh
pip3 install pipenv
```
To install the project,
```sh
make install
```
To regenerate artifacts from the Biolink Model YAML,
```sh
make
```
**Note:** the Makefile requires the following dependencies to be installed:
### jsonschema
[jsonschema](https://json-schema.org/)
Generally install using
```sh
pip3 install jsonschema
```
### jsonschema2pojo
[jsonschema2pojo](https://github.com/joelittlejohn/jsonschema2pojo)
If you are on a Mac, it can be installed using `brew`:
```sh
brew install jsonschema2pojo
```
For other OS environments, download the latest release then extract it into your execution path. eg
```sh
wget https://github.com/joelittlejohn/jsonschema2pojo/releases/download/jsonschema2pojo-1.0.2/jsonschema2pojo-1.0.2.tar.gz
tar -xvzf jsonschema2pojo-1.0.2.tar.gz
export PATH=$PATH:`pwd`/jsonschema2pojo-1.0.2/bin
```
### GraphViz
See [GraphViz site](https://graphviz.org/) for installation in your operating system.
## How do I use Biolink Model YAML programmatically?
For operations such as CURIE lookup, finding class by synonyms, get parents, get ancestors, etc. please make use of [biolink-model-toolkit](https://github.com/biolink/biolink-model-toolkit/). It provides convenience methods for traversing Biolink Model.
## Citing Biolink Model
Unni DR, Moxon SAT, Bada M, Brush M, Bruskiewich R, Caufield JH, Clemons PA, Dancik V, Dumontier M, Fecho K, Glusman G, Hadlock JJ, Harris NL, Joshi A, Putman T, Qin G, Ramsey SA, Shefchek KA, Solbrig H, Soman K, Thessen AE, Haendel MA, Bizon C, Mungall CJ, The Biomedical Data Translator Consortium (2022).
Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science. Clin Transl Sci. Wiley; 2022 Jun 6; https://onlinelibrary.wiley.com/doi/10.1111/cts.13302
%prep
%autosetup -n biolink-model-3.4.3
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-biolink-model -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 3.4.3-1
- Package Spec generated
|
