Reorganize repository structure (#1103)

This PR does the following:

1. Consolidates the external registry getters (in
`bioregistry.external`), the external registry alignment classes (in
`bioregistry.align` the data artifacts (in `bioregistry.data.external`),
and a few (3) configuration files (in `bioregistry.data`) into a single
hierarchy in `bioregistry.external`.
2. Moves the metaregistry curation sheets and the raw data from the
repositories out of the `src/` structure. They're now in the
`/exports/alignment/` and `/exports/raw/` folders, respectively. The
point of this is to reduce the size of the package that gets sent to
PyPI, related to #1100
3. minor version bump to 0.11.X series

In theory, this shouldn't affect any downstream uses, since the
`bioregistry.align` submodule isn't really for external users.

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.10.204-dev
+current_version = 0.11.0-dev
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(?:-(?P<release>[0-9A-Za-z-]+(?:\.[0-9A-Za-z-]+)*))?(?:\+(?P<build>[0-9A-Za-z-]+(?:\.[0-9A-Za-z-]+)*))?

docs/CONTRIBUTING.md

@@ -291,7 +291,7 @@ file for inspiration. Entries in this file should follow the schema defined by t
 See also the corresponding entry in the Bioregistry's [JSON schema](https://github.com/biopragmatics/bioregistry/blob/main/src/bioregistry/schema/schema.json)
 
 While not strictly required, it's also useful for each registry to add a corresponding getter script and aligner
-class in `bioregistry.external` and `bioregistry.align`, respectively. See examples there, or get in touch on the
+class in `bioregistry.external`. See examples there, or get in touch on the
 issue tracker for help.
 
 ## Code Contribution

docs/curation.md

@@ -67,7 +67,7 @@ that show relevant metadata to help curate each record as one of the following:
 {% for entry in site.data.curation["prefix_xrefs"] %}
    <tr>
       <td>{{ entry.metaprefix }}</td>
-      <td><a href="https://github.com/biopragmatics/bioregistry/blob/main/src/bioregistry/data/external/{{ entry.metaprefix }}/curation.tsv">{{ entry.name }}</a></td>
+      <td><a href="https://github.com/biopragmatics/bioregistry/blob/main/exports/alignment{{ entry.metaprefix }}.tsv">{{ entry.name }}</a></td>
    </tr>
 {% endfor %}
 </tbody>

docs/source/alignment.rst

@@ -1,6 +1,3 @@
 Alignment
 =========
-.. automodapi:: bioregistry.align
-    :no-inheritance-diagram:
-
 .. automodapi:: bioregistry.external

docs/source/conf.py

@@ -27,7 +27,7 @@
 author = "Charles Tapley Hoyt"
 
 # The full version, including alpha/beta/rc tags.
-release = "0.10.204-dev"
+release = "0.11.0-dev"
 
 # The short X.Y version.
 parsed_version = re.match(

exports/README.md

@@ -20,9 +20,11 @@ basis using GitHub Actions as a continuous integration server.
 | [`rdf`](rdf)                   | Build of an RDF triple-store representing the registry, metaregistry, and collections            |
 | [`sssom`](sssom)               | An export of prefix mappings in the Simple Standard for Sharing Ontology Mappings (SSSOM) format |
 | [`contexts`](contexts)         | Fit-for-purpose exports of JSON-LD contexts constructed from the Bioregistry                     |
+| [`alignment`](alignment)       | Curation sheets for aligning the metaregistry                                                    |
+| [`raw`](raw)                   | Raw data from select external registries                                                         |
 
 ## PURLs
 
 The Bioregistry uses https://w3id.org to create persistent uniform resource locators (PURLs) for various
-resources. These are configured on GitHub in the .htaccess file
+resources. These are configured on GitHub in the `.htaccess` file
 in https://github.com/perma-id/w3id.org/tree/master/biopragmatics.

src/bioregistry/data/external/bioportal/curation.tsv → exports/alignment/bioportal.tsv

@@ -327,7 +327,7 @@ IBO	Imaging Biomarker Ontology		The Imaging Biomarker Ontology describes radiolo
 ICD-O-3	International Classification of Diseases for Oncology, 3rd edition	https://data.jrc.ec.europa.eu/dataset/88ff4ec5-1832-403e-abe1-64928592568f	Ontology used for oncology research derived from the European Cancer Information System (ECIS)
 ICD11-BODYSYSTEM	Body System Terms from ICD11		This is a set of body-system terms used in the ICD 11 revision
 ICDO	International Classification of Diseases Ontology	https://github.com/icdo/ICDO	A biomedical ontology for logical representation of the terms and relations related to the International Classification of Diseases (ICD)
-ICECI	International Classification of  External Causes of Injuries		The International Classification of External Causes of Injury (ICECI) is a system of classifications to enable systematic description of how injuries occur. It is designed especially to assist injury prevention. The ICECI was originally designed for use in settings in which information is recorded in a way that allows statistical reporting--for example, injury surveillance based on collection of information about cases attending a sample of hospital emergency departments. It has also been found useful for other purposes. For example, it has been used as a reference classification during revision of another classification, to record risk-factor exposure of children in a cohort study, as the basis for special-purpose classifications and in a growing number of other ways.
+ICECI	International Classification of External Causes of Injuries		The International Classification of External Causes of Injury (ICECI) is a system of classifications to enable systematic description of how injuries occur. It is designed especially to assist injury prevention. The ICECI was originally designed for use in settings in which information is recorded in a way that allows statistical reporting--for example, injury surveillance based on collection of information about cases attending a sample of hospital emergency departments. It has also been found useful for other purposes. For example, it has been used as a reference classification during revision of another classification, to record risk-factor exposure of children in a cohort study, as the basis for special-purpose classifications and in a growing number of other ways.
 ICHOM-PROMS-PCB	ICHOM Set Pregnancy and Childbirth		The ICHOM Set of Patient-Centered Outcome Measures for Pregnancy And Childbirth is the result of hard work by a group of leading physicians, measurement experts and patients. It is a recommendation of the outcomes that matter most to persons experiencing Pregnancy And Childbirth.
 ICNP	International Classification for Nursing Practice	https://www.icn.ch/what-we-do/projects/ehealth-icnp	International Classification for Nursing Practice
 ICPC2P	International Classification of Primary Care - 2 PLUS	http://www.fmrc.org.au/	ICPC-2 PLUS
@@ -549,7 +549,7 @@ ONTOKBCF	Ontological Knowledge Base Model for Cystic Fibrosis		OntoKBCF is an on
 ONTOLURGENCES	Emergency care ontology		Emergency care ontology build during LERUDI project. http://www.ncbi.nlm.nih.gov/pubmed/25160343 (v4.0)
 ONTOMA	Ontology of Alternative Medicine, French	www.lavima.org	Common concepts for communication between traditional medicine and western medicine. (In French)
 ONTOPARON	Ontology of Amyotrophic Lateral Sclerosis, all modules		Ontology of ALS (amyotrophic lateral sclerosis), social module + coordination module + medical module developped by neurologists (ICM) and knowledge engineers (LIMICS). This version (11/15/2018) is upload with inferred axioms but without equivalent classe axioms. It serves in this version in a Gate pipeline for a semantic annotation task. This version (03/20/2019) is upload with object properties, inferred axioms and equivalent classes axioms. This version (11/10/2020) is uploaded with small corrections.
-ONTOPARON_SOCIAL	Ontology of amyotrophic  lateral sclerosis, social module		Ontology of ALS (amyotrophic lateral sclerosis), social module developped by neurologist (ICM) and knowledge engineers (LIMICS). Complete version available at http://bioportal.bioontology.org/ontologies/ONTOPARON
+ONTOPARON_SOCIAL	Ontology of amyotrophic lateral sclerosis, social module		Ontology of ALS (amyotrophic lateral sclerosis), social module developped by neurologist (ICM) and knowledge engineers (LIMICS). Complete version available at http://bioportal.bioontology.org/ontologies/ONTOPARON
 ONTOPBM	Ontology for Process-Based Modeling of Dynamical Systems (OntoPBM)		OntoPBM is an ontology of core entities for process-based modeling of dynamical systems.
 ONTOPNEUMO	Ontology of Pneumology		Ontology of pneumology (french version). The ONTOPNEUMO ontology was developped by Audrey Baneyx, under the direction of Jean Charlet about knowledge engineering expertise and by François-Xavier Blanc in collaboration with Bruno Housset about medical expertise. The OWL compliant ONTOPNEUMO ontology is available under Creative Commons license “Attribution-Non-Commercial-No Derivative Works 2.0 UK”. Details of this license are accessible at : http://creativecommons.org/licenses/ by-nc-nd/2.0/uk/.
 ONTOPSYCHIA	OntoPsychia, social module		Ontology of social and environmental determinants for psychiatry
@@ -661,7 +661,7 @@ ROS	Radiation Oncology Structures Ontology	http://www.twitter.com/jebibault	This
 RPO	Resource of Asian Primary Immunodeficiency Diseases (RAPID) Phenotype Ontology	http://rapid.rcai.riken.jp/ontology/v1.0/phenomer.php	RAPID phenotype ontology presents controlled vocabulary of ontology class structures and entities of observed phenotypic terms for primary immunodeficiency diseases (PIDs) that facilitate global sharing and free exchange of PID data with users’ communities
 RSA	Reference Sequence Annotation		An ontology for sequence annotations and how to preserve them with reference sequences
 RVO	Research Variable Ontology	http://w3id.org/rv-ontology/info	RVO, Research Variable Ontology, proposes a schema that can be use to record empirical data analytics research and can be use as a knowledge-base to support knowledge exploration phase of a new analytics research to learn and get recommendation. RVO is designed around the research variables, which form the basis of the hypothesis that analysts test through building a model.
-SARSMUTONTO	Ontology for SARS-CoV-2  lineages and mutations	https://github.com/jbakkas/SARSMutOnto	The SARSMutOnto ontology provides a list of all SARS-CoV-2 Pango lineages while maintaining their hierarchy (lineage/sublineage) describing in detail all lineage mutations
+SARSMUTONTO	Ontology for SARS-CoV-2 lineages and mutations	https://github.com/jbakkas/SARSMutOnto	The SARSMutOnto ontology provides a list of all SARS-CoV-2 Pango lineages while maintaining their hierarchy (lineage/sublineage) describing in detail all lineage mutations
 SATO	SATO (IDEAS expAnded wiTh BCIO): workflow for designers of patient-centered mobile health behaviour change intervention applications		Designing effective theory-driven digital behaviour change interventions (DBCI) is a challenging task. To ease the design process, and assist with knowledge sharing and evaluation of the DBCI, we propose the SATO (IDEASexpAnded wiTh BCIO) design workflow based on the IDEAS (Integrate, Design, Assess, and Share) framework and aligned with the Behaviour Change Intervention Ontology (BCIO). BCIO is a structural representation of the knowledge in behaviour change domain supporting evaluation of behaviour change interventions (BCIs) but it is not straightforward to utilise it during DBCI design. IDEAS (Integrate, Design, Assess, and Share) framework guides multi-disciplinary teams through the mobile health (mHealth) application development life-cycle but it is not aligned with BCIO entities. SATO couples BCIO entities with workflow steps and extends IDEAS Integrate stage with consideration of customisation and personalisation. The SATO ontology provides the extensions of BCIO along with examples of a BCI Scenario of Fatigue Reduction.
 SBOL	Synthetic Biology Open Language Visual Ontology	www.sbolstandard.org/visual	Synthetic Biology Open Language Visual (SBOLv) is an ontology to represent standardized graphical notation for synthetic biology.
 SCIO	Spinal Cord Injury Ontology	http://www.psink.de	Representation of pre-clinical studies in the domain of spinal cord injury therapies

exports/alignment/cheminf.tsv

@@ -0,0 +1,5 @@
+prefix	name	description
+000570	SwissLipids	
+000571	MolMeDB	
+000572	PDB ligand	
+000573	PDB structure	

src/bioregistry/data/external/ecoportal/curation.tsv → exports/alignment/ecoportal.tsv

@@ -20,6 +20,7 @@ EUROVOC	EuroVoc Core Concepts	https://op.europa.eu/s/y4TH	EuroVoc is a multiling
 FISHTRAITS	Fish Traits Thesaurus		The Fish Traits Thesaurus is the first initiative to deal with the semantics of fish functional traits. It has been developed by LifeWatch Italy, the Italian node of the e-science European infrastructure for biodiversity and ecosystem research (LifeWatch ERIC). FishTraits reflects the agreement of a scientific expert community to fix semantic properties (e.g. label, definition, relationships) of approximately 220 concepts.
 I-ADOPT	I-ADOPT Framework ontology		"The I-ADOPT Framework is an ontology designed to facilitate interoperability between existing variable description models (including ontologies, taxonomy, and structured controlled vocabularies). One of the challenges in representing semantic descriptions of variables is getting people to agree about what they mean when describing the components that define the variables. The I-ADOPT ontology addresses this by providing core components and their relations that can be applied to define machine-interpretable variable descriptions that re-use FAIR vocabulary terms. It was developed by a core group of terminology experts and users from the Research Data Alliance (RDA) InteroperAble Descriptions of Observable Property Terminology (I-ADOPT) Working Group. The first published versions of the ontology up to v0.9.1 satisfied the basic cross-domain interoperability requirements. It defines four classes or ""concepts"" (Variable, Property, Entity, Constraint), and six object properties (hasProperty, hasObjectOfInterest, hasContextObject, hasMatrix, hasConstraint, constrains). The Variable is the top concept. It represents the description of something observed or mathematically derived. It minimally consists of one entity (the ObjectOfInterest) and its Property; a Property being a type of characteristic (i.e. a quantity or a quality). More complex variables can involve additional entities, for example an entity may have the role of Matrix and/or of ContextObject(s). The framework does not capture units, instruments, methods, and geographical location information; however its usage recommendation will make explicit reference to these by connecting the I-ADOPT framework to existing and complementary ontologies. This new version of the ontology (v1.0) adds one optional new class (VariableSet) and four optional new object properties (hasApplicableProperty, hasApplicableObjectOfInterest, hasApplicableMatrix, hasApplicableContextObject). This was necessary in order to enable flexibility in assigning optional and user-defined machine-interpretable categorizations of I-ADOPT variables under one or multiple coarser grouping concepts to facilitate dataset discovery and dataset aggregation. With the introduction of these concepts and properties, the framework enables different user communities or product developers to develop their own grouping criteria. While the Variable class must be connected to at least two classes via the mandatory properties hasProperty and hasObjectOIfInterest, the VariableSet class can have either of the new properties. Additionally, the VariableSet class can also be optionally connected to the Variable class using the property [ro:hasMember](http://purl.obolibrary.org/obo/RO_0002351) from the [OBO Relations Ontology](https://obofoundry.org/ontology/ro.html)."
 LUPO	LifeWatch ERIC Upper Ontology		The LifeWatch ERIC Upper Ontology (LUPO) is the model defining the core set of LifeWatch ERIC elements (Actors, Services and Infrastructure) and describing their high-level arrangement. LUPO is extendable and will foster, connect and describe lower level models of its core elements, with the vision to provide functionalities that facilitate the uptake, re-use and enrichment of LifeWatch ERIC resources by an ever broader community.
+LWT	LifeWatch_test		
 MACROALGAETRAITS	Macroalgae Traits Thesaurus		The Macroalgae Traits Thesaurus contains several concepts on demographic and functional traits. It has been developed and published by LifeWatch Italy, the Italian node of the e-science European infrastructure for biodiversity and ecosystem research (LifeWatch ERIC). It reflects the agreement of a scientific expert community to fix semantic properties (e.g. label, definition) of approximately 100 traits.
 MR	Marine Regions ontology	https://www.marineregions.org/	The Marine Regions ontology provides definitions for the classes and properties used in the Marine Regions dataset.
 MRPTCODELIST	Marine Regions PlaceTypes code list	https://www.marineregions.org/	The Marine Regions PlaceType code list provides definitions for the PlaceTypes used in the Marine Regions dataset.