schatz
/
openaire-graph-docs
forked from D-Net/openaire-graph-docs
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases 5 Wiki Activity

addressing comments from the code review

This commit is contained in:
Claudio Atzori 2022-11-08 16:54:39 +01:00
parent e9296f1a40
commit 12263fca62
5 changed files with 84 additions and 411 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
docs/data-model/pids-and-identifiers.md
View File

@ -13,8 +13,8 @@ Such a policy defines a list of data sources that are considered authoritative f
* OpenAIRE IDs depend on persistent IDs when they are provided by the authority responsible to create them; * OpenAIRE IDs depend on persistent IDs when they are provided by the authority responsible to create them;
* PIDs are included in the graph according to a tight criterion: the PID Types declared in the table below are considered to be mapped as PIDs only when they are collected from the relative PID authority data source. * PIDs are included in the graph according to a tight criterion: the PID Types declared in the table below are considered to be mapped as PIDs only when they are collected from the relative PID authority data source.
| *PID Type* | *Authority* | | PID Type | Authority |
|------------|-----------------------------------------------------------------------------------------------------| |-----------|-----------------------------------------------------------------------------------------------------|
| doi | [Crossref](https://www.crossref.org), [Datacite](https://datacite.org) | | doi | [Crossref](https://www.crossref.org), [Datacite](https://datacite.org) |
| pmc, pmid | [Europe PubMed Central](https://europepmc.org/), [PubMed Central](https://www.ncbi.nlm.nih.gov/pmc) | | pmc, pmid | [Europe PubMed Central](https://europepmc.org/), [PubMed Central](https://www.ncbi.nlm.nih.gov/pmc) |
| arXiv | [arXiv.org e-Print Archive](https://arxiv.org/) | | arXiv | [arXiv.org e-Print Archive](https://arxiv.org/) |
@ -31,8 +31,8 @@ assigns PIDs to their scientific products from a given PID minter.
This "selection" can be performed when the entities in the graph sharing the same identifier are grouped together. The list of the delegated authorities currently includes This "selection" can be performed when the entities in the graph sharing the same identifier are grouped together. The list of the delegated authorities currently includes
| *Datasource delegated* | *Datasource delegating* | *Pid Type* | | Datasource delegated | Datasource delegating | Pid Type |
|--------------------------------------|----------------------------------|------------| |--------------------------------------|----------------------------------|-----------|
| [Zenodo](https://zenodo.org) | [Datacite](https://datacite.org) | doi | | [Zenodo](https://zenodo.org) | [Datacite](https://datacite.org) | doi |
| [RoHub](https://reliance.rohub.org/) | [W3ID](https://w3id.org/) | w3id | | [RoHub](https://reliance.rohub.org/) | [W3ID](https://w3id.org/) | w3id |

4
docs/data-provision/aggregation/aggregation.md
View File

@ -10,14 +10,14 @@ OpenAIRE materializes an open, participatory research graph (the OpenAIRE Resear
OpenAIRE aggregates metadata records describing objects of the research life-cycle from content providers compliant to the [OpenAIRE guidelines](https://guidelines.openaire.eu/) and from entity registries (i.e. data sources offering authoritative lists of entities, like [OpenDOAR](https://v2.sherpa.ac.uk/opendoar/), [re3data](https://www.re3data.org/), [DOAJ](https://doaj.org/), and various funder databases). After collection, metadata are transformed according to the OpenAIRE internal metadata model, which is used to generate the final OpenAIRE Research Graph, accessible from the [OpenAIRE EXPLORE portal](https://explore.openaire.eu) and the [APIs](https://graph.openaire.eu/develop/). OpenAIRE aggregates metadata records describing objects of the research life-cycle from content providers compliant to the [OpenAIRE guidelines](https://guidelines.openaire.eu/) and from entity registries (i.e. data sources offering authoritative lists of entities, like [OpenDOAR](https://v2.sherpa.ac.uk/opendoar/), [re3data](https://www.re3data.org/), [DOAJ](https://doaj.org/), and various funder databases). After collection, metadata are transformed according to the OpenAIRE internal metadata model, which is used to generate the final OpenAIRE Research Graph, accessible from the [OpenAIRE EXPLORE portal](https://explore.openaire.eu) and the [APIs](https://graph.openaire.eu/develop/).
The transformation process includes the application of cleaning functions whose goal is to ensure that values are harmonised according to a common format (e.g. dates as YYYY-MM-dd) and, whenever applicable, to a common controlled vocabulary. The controlled vocabularies used for cleansing are accessible at http://api.openaire.eu/vocabularies. Each vocabulary features a set of controlled terms, each with one code, one label, and a set of synonyms. If a synonym is found as field value, the value is updated with the corresponding term. The transformation process includes the application of cleaning functions whose goal is to ensure that values are harmonised according to a common format (e.g. dates as YYYY-MM-dd) and, whenever applicable, to a common controlled vocabulary. The controlled vocabularies used for cleansing are accessible at [api.openaire.eu/vocabularies](https://api.openaire.eu/vocabularies/). Each vocabulary features a set of controlled terms, each with one code, one label, and a set of synonyms. If a synonym is found as field value, the value is updated with the corresponding term.
Also, the OpenAIRE Research Graph is extended with other relevant scholarly communication sources that do not follow the OpenAIRE Guidelines and/or are too large to be integrated via the “normal” aggregation mechanism: DOIBoost (which merges Crossref, ORCID, Microsoft Academic Graph, and Unpaywall). Also, the OpenAIRE Research Graph is extended with other relevant scholarly communication sources that do not follow the OpenAIRE Guidelines and/or are too large to be integrated via the “normal” aggregation mechanism: DOIBoost (which merges Crossref, ORCID, Microsoft Academic Graph, and Unpaywall).
<p align="center"> <p align="center">
<img loading="lazy" alt="Aggregation" src="/img/docs/aggregation.png" width="65%" className="img_node_modules-@docusaurus-theme-classic-lib-theme-MDXComponents-Img-styles-module"/> <img loading="lazy" alt="Aggregation" src="/img/docs/aggregation.png" width="65%" className="img_node_modules-@docusaurus-theme-classic-lib-theme-MDXComponents-Img-styles-module"/>
</p> </p>
The OpenAIRE aggregation system collects information about objects of the research life-cycle compliant to the [OpenAIRE acquisition policy](https://www.openaire.eu/content-aquisition-policy1) from [different types of data sources](https://explore.openaire.eu/search/find/dataproviders): The OpenAIRE aggregation system collects information about objects of the research life-cycle compliant to the [OpenAIRE acquisition policy](https://www.openaire.eu/content-acquisition-policy) from [different types of data sources](https://explore.openaire.eu/search/find/dataproviders):
1. Scientific literature metadata and full-texts from institutional and thematic repositories, CRIS (Common Research Information Systems), Open Access journals and publishers; 1. Scientific literature metadata and full-texts from institutional and thematic repositories, CRIS (Common Research Information Systems), Open Access journals and publishers;
2. Dataset metadata from data repositories and data journals; 2. Dataset metadata from data repositories and data journals;

36
docs/data-provision/aggregation/doiboost.md
View File

@ -4,10 +4,6 @@ DOIBoost is a dataset that combines research outputs and links among them from a
It enriches the records available on Crossref with what's available on Unpaywall, Microsoft Academic Graph, ORCID intersecting all those datasets by DOI. It enriches the records available on Crossref with what's available on Unpaywall, Microsoft Academic Graph, ORCID intersecting all those datasets by DOI.
As consequence, DOIBoost does not contain any record from MAG, Unpaywall, or ORCID that doesn't provide a DOI available in Crossref. As consequence, DOIBoost does not contain any record from MAG, Unpaywall, or ORCID that doesn't provide a DOI available in Crossref.
The idea behind DOIBoost and its origin can be found in the paper (and related resources) at:
* La Bruzzo S., Manghi P., Mannocci A. (2019) OpenAIRE's DOIBoost - Boosting CrossRef for Research. In: Manghi P., Candela L., Silvello G. (eds) Digital Libraries: Supporting Open Science. IRCDL 2019. Communications in Computer and Information Science, vol 988. Springer, doi:10.1007/978-3-030-11226-4_11 . Open Access version available at: [10.5281/zenodo.1441071](https://doi.org/10.5281/zenodo.1441071)
Each Crossref record is enriched with: Each Crossref record is enriched with:
* ORCID identifiers of authors from ORCID * ORCID identifiers of authors from ORCID
* Open Access instance (with OA color/route and license) from Unpaywall * Open Access instance (with OA color/route and license) from Unpaywall
@ -29,7 +25,11 @@ The Open Access status is also set by intersecting the journal information of a
The construction of the DOIBoost dataset consists of the following phases: The construction of the DOIBoost dataset consists of the following phases:
## 1. Crossref filtering ## Process
The following section describes the processing steps needed to build DOIBoost starting from the input data.
### Crossref filtering
Records in Crossref are ruled out according to the following criteria Records in Crossref are ruled out according to the following criteria
@ -68,7 +68,7 @@ Records in Crossref are ruled out according to the following criteria
Records with `type=dataset` are mapped into OpenAIRE results of type dataset. All others are mapped as OpenAIRE results of type publication. Records with `type=dataset` are mapped into OpenAIRE results of type dataset. All others are mapped as OpenAIRE results of type publication.
## 2. Mapping Crossref properties into the OpenAIRE Research Graph ### Mapping Crossref properties into the OpenAIRE Research Graph
Properties in OpenAIRE results are set based on the logic described in the following table: Properties in OpenAIRE results are set based on the logic described in the following table:
@ -133,9 +133,9 @@ Possible improvements:
h3. 2 Map Crossref links to projects/funders h3. 2 Map Crossref links to projects/funders
Links to funding available in Crossref are mapped as funding relationships (`result -- isProducedBy --> project`) applying the following mapping: Links to funding available in Crossref are mapped as funding relationships (`result -- isProducedBy -- project`) applying the following mapping:
| *funder* | *grant code* | *Link to* | | Funder | Grant code | Link to |
|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------| |----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|
| DOI: `{10.13039/100010663, 10.13039/100010661, 10.13039/501100007601, 10.13039/501100000780, 10.13039/100010665}` or name: `'European Union’s Horizon 2020 research and innovation program'` | series of `4-9` digits in `award` | Link to H2020 project | | DOI: `{10.13039/100010663, 10.13039/100010661, 10.13039/501100007601, 10.13039/501100000780, 10.13039/100010665}` or name: `'European Union’s Horizon 2020 research and innovation program'` | series of `4-9` digits in `award` | Link to H2020 project |
| DOI: `{10.13039/100011199, 10.13039/100004431, 10.13039/501100004963, 10.13039/501100000780}` | series of `4-9` digits in `award` | Link to FP7 project | | DOI: `{10.13039/100011199, 10.13039/100004431, 10.13039/501100004963, 10.13039/501100000780}` | series of `4-9` digits in `award` | Link to FP7 project |
@ -159,7 +159,7 @@ Links to funding available in Crossref are mapped as funding relationships (`res
| DOI: `10.13039/501100004410` | `award` | Link to TUBITAK project | | DOI: `10.13039/501100004410` | `award` | Link to TUBITAK project |
| DOI: `10.10.13039/100004440` or name: `Wellcome Trust Masters Fellowship` | `award` | Link to Wellcome Trust specific project and to the `unidentified` project. | | DOI: `10.10.13039/100004440` or name: `Wellcome Trust Masters Fellowship` | `award` | Link to Wellcome Trust specific project and to the `unidentified` project. |
## 3. Intersect Crossref with UnpayWall by DOI ### Intersect Crossref with UnpayWall by DOI
The fields we consider from UnpayWall are: The fields we consider from UnpayWall are:
* `is_oa` * `is_oa`
@ -168,7 +168,7 @@ The fields we consider from UnpayWall are:
The results of Crossref that intersect by DOI with UnpayWall records are enriched with one additional `instance` with the following properties: The results of Crossref that intersect by DOI with UnpayWall records are enriched with one additional `instance` with the following properties:
| *OpenAIRE Result field path* | *Unpaywall field path* | *Notes* | | OpenAIRE Result field path | Unpaywall field path | Notes |
|----------------------------------------|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |----------------------------------------|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `instance` | | created only if `is_oa` and a `best_oa_location` is available | | `instance` | | created only if `is_oa` and a `best_oa_location` is available |
| `instance.accessright` | | default value `Open Access`: we do not add instances if UnpayWall says there is no open version | | `instance.accessright` | | default value `Open Access`: we do not add instances if UnpayWall says there is no open version |
@ -186,14 +186,14 @@ For the definition of UnpayWall's `oa_status` refer to the [Unpaywall FAQ](https
The record will also feature a relation to the UnpayWall data source: `name="UnpayWall"`, `id=openaire____::8ac8380272269217cb09a928c8caa993`. The record will also feature a relation to the UnpayWall data source: `name="UnpayWall"`, `id=openaire____::8ac8380272269217cb09a928c8caa993`.
## 4. Intersect with ORCID ### Intersect with ORCID
The fields we consider from ORCID are: The fields we consider from ORCID are:
* `doi` * `doi`
* `authors`, a list of authors, each with optional `name`, `surname`, `creditName`, `oid` * `authors`, a list of authors, each with optional `name`, `surname`, `creditName`, `oid`
| *OpenAIRE field path* | *ORCID path* | *Notes* | | OpenAIRE field path | ORCID path | Notes |
|-------------------------------------|-----------------------|--------------------------------------------------------------------------------------------------------------------------------------| |------------------------------------|-----------------------|--------------------------------------------------------------------------------------------------------------------------------------|
| `pid` | `doi` | | | `pid` | `doi` | |
| `author.name` | `capitalize(name)` | only mapped if not blank | | `author.name` | `capitalize(name)` | only mapped if not blank |
| `author.surname` | `capitalize(surname)` | only mapped if not blank | | `author.surname` | `capitalize(surname)` | only mapped if not blank |
@ -216,7 +216,7 @@ Miriam will modify the process to ensure that:
* the list of authors from Crossred always "win" * the list of authors from Crossred always "win"
* the identifiers from ORCID "win" * the identifiers from ORCID "win"
## 5. Intersect with Microsoft Academic Graph ### Intersect with Microsoft Academic Graph
*Important Notes* *Important Notes*
* Only papers with DOI are considered * Only papers with DOI are considered
@ -238,10 +238,16 @@ The records are enriched with:
* conference or journal information (in the `journal` field) TODO: or `container`, in case of the dump? * conference or journal information (in the `journal` field) TODO: or `container`, in case of the dump?
* [TO BE REMOVED] instances with URL from MAG * [TO BE REMOVED] instances with URL from MAG
## 6. Enrich DOIBoost3 with hosting data sources (`hostedby`) and access right information ### Enrich DOIBoost3 with hosting data sources (`hostedby`) and access right information
In this phase, we intersect DOIBoost3 with a dataset composed of journals from OpenAIRE, Crossref, and the ISSN gold list. Each journal comes with its International Standard Serial Numbers (`issn`, `eissn`, `lissn`) and, when available, a flag that tells if the journal is open access. The intersection is done on the basis of the International Standard Serial Numbers. The records with a `journal.[l|e]issn` that match are enriched as follows: In this phase, we intersect DOIBoost3 with a dataset composed of journals from OpenAIRE, Crossref, and the ISSN gold list. Each journal comes with its International Standard Serial Numbers (`issn`, `eissn`, `lissn`) and, when available, a flag that tells if the journal is open access. The intersection is done on the basis of the International Standard Serial Numbers. The records with a `journal.[l|e]issn` that match are enriched as follows:
* Each instance gain the `hostedby` information corresponding to the journal * Each instance gain the `hostedby` information corresponding to the journal
* If the journal is open access, the access rights of the instances are also set to `Open Access` with `gold` route (because by construction, the journals we know are open are from DOAJ or Gold ISSN list) * If the journal is open access, the access rights of the instances are also set to `Open Access` with `gold` route (because by construction, the journals we know are open are from DOAJ or Gold ISSN list)
The hostedby of records that do not match are set to the `Unknown Repository`. The hostedby of records that do not match are set to the `Unknown Repository`.
## References
The idea behind DOIBoost and its origin can be found in the paper (and related resources) at:
* La Bruzzo S., Manghi P., Mannocci A. (2019) OpenAIRE's DOIBoost - Boosting CrossRef for Research. In: Manghi P., Candela L., Silvello G. (eds) Digital Libraries: Supporting Open Science. IRCDL 2019. Communications in Computer and Information Science, vol 988. Springer, doi:10.1007/978-3-030-11226-4_11 . Open Access version available at: [10.5281/zenodo.1441071](https://doi.org/10.5281/zenodo.1441071)

340
docs/data-provision/aggregation/ebi.md
View File

@ -65,339 +65,7 @@ curl -s "https://www.ebi.ac.uk/europepmc/webservices/rest/MED/33024307/datalinks
"Name": "Europe PMC" "Name": "Europe PMC"
} }
}, },
"Frequency": 1 [...]
},
{
"ObtainedBy": "tm_accession",
"PublicationDate": "04-11-2022",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "References"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "MED"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "MT121216",
"IDScheme": "ENA",
"IDURL": "http://identifiers.org/ebi/ena.embl:MT121216"
},
"Title": "MT121216",
"Publisher": {
"Name": "Europe PMC"
}
},
"Frequency": 1
},
{
"ObtainedBy": "tm_accession",
"PublicationDate": "04-11-2022",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "References"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "MED"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "KF367457",
"IDScheme": "ENA",
"IDURL": "http://identifiers.org/ebi/ena.embl:KF367457"
},
"Title": "KF367457",
"Publisher": {
"Name": "Europe PMC"
}
},
"Frequency": 1
},
{
"ObtainedBy": "tm_accession",
"PublicationDate": "04-11-2022",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "References"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "MED"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "MN996532",
"IDScheme": "ENA",
"IDURL": "http://identifiers.org/ebi/ena.embl:MN996532"
},
"Title": "MN996532",
"Publisher": {
"Name": "Europe PMC"
}
},
"Frequency": 1
},
{
"ObtainedBy": "tm_accession",
"PublicationDate": "04-11-2022",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "References"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "MED"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "MT072864",
"IDScheme": "ENA",
"IDURL": "http://identifiers.org/ebi/ena.embl:MT072864"
},
"Title": "MT072864",
"Publisher": {
"Name": "Europe PMC"
}
},
"Frequency": 1
}
]
}
}
]
},
{
"Name": "Protein Structures",
"NameLong": "Protein structures in PDBe",
"CategoryLinkCount": 2,
"Section": [
{
"ObtainedBy": "tm_accession",
"Tags": [
"supporting_data"
],
"SectionLinkCount": 2,
"Linklist": {
"Link": [
{
"ObtainedBy": "tm_accession",
"PublicationDate": "04-11-2022",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "References"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "MED"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "6VW1",
"IDScheme": "PDB",
"IDURL": "http://identifiers.org/pdbe/pdb:6VW1"
},
"Title": "6VW1",
"Publisher": {
"Name": "Europe PMC"
}
},
"Frequency": 1
},
{
"ObtainedBy": "tm_accession",
"PublicationDate": "04-11-2022",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "References"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "MED"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "2AJF",
"IDScheme": "PDB",
"IDURL": "http://identifiers.org/pdbe/pdb:2AJF"
},
"Title": "2AJF",
"Publisher": {
"Name": "Europe PMC"
}
},
"Frequency": 1
}
]
}
}
]
},
{
"Name": "Altmetric",
"CategoryLinkCount": 1,
"Section": [
{
"ObtainedBy": "ext_links",
"Tags": [
"altmetrics"
],
"SectionLinkCount": 1,
"Linklist": {
"Link": [
{
"ObtainedBy": "ext_links",
"PublicationDate": "15-10-2020",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "IsReferencedBy"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "PMID"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "https://www.altmetric.com/details/91880755",
"IDScheme": "URL",
"IDURL": "https://www.altmetric.com/details/91880755"
},
"Title": "Characteristics of SARS-CoV-2 and COVID-19",
"Publisher": {
"Name": "Altmetric"
},
"ImageURL": "https://api.altmetric.com/v1/donut/91880755_64.png"
}
}
]
}
}
]
},
{
"Name": "BioStudies: supplemental material and supporting data",
"CategoryLinkCount": 1,
"Section": [
{
"ObtainedBy": "ext_links",
"Tags": [
"supporting_data"
],
"SectionLinkCount": 1,
"Linklist": {
"Link": [
{
"ObtainedBy": "ext_links",
"PublicationDate": "11-03-2021",
"LinkProvider": {
"Name": "Europe PMC"
},
"RelationshipType": {
"Name": "IsReferencedBy"
},
"Source": {
"Type": {
"Name": "literature"
},
"Identifier": {
"ID": "33024307",
"IDScheme": "PMID"
}
},
"Target": {
"Type": {
"Name": "dataset"
},
"Identifier": {
"ID": "http://www.ebi.ac.uk/biostudies/studies/S-EPMC7537588?xr=true",
"IDScheme": "URL",
"IDURL": "http://www.ebi.ac.uk/biostudies/studies/S-EPMC7537588?xr=true"
},
"Title": "Characteristics of SARS-CoV-2 and COVID-19.",
"Publisher": {
"Name": "BioStudies: supplemental material and supporting data"
}
}
}
]
}
}
]
}
]
}
}
``` ```
## Mapping ## Mapping
@ -406,8 +74,8 @@ We filter all the target links with pid type **ena**, **pdb** or **uniprot**
For each target we construct a Bioentity with the following mapping For each target we construct a Bioentity with the following mapping
| *OpenAIRE Result field path* | EBI record field xpath | Notes | | OpenAIRE Result field path | EBI record field xpath | Notes |
|------------------------------|----------------------------------------------------------|---------------------------------------------------------------| |-----------------------------|----------------------------------------------------------|---------------------------------------------------------------|
| `id` | `target/identifier/ID` and `target/identifier/IDScheme` | id in the form `SCHEMA_________::md5(pid)` | | `id` | `target/identifier/ID` and `target/identifier/IDScheme` | id in the form `SCHEMA_________::md5(pid)` |
| `pid` | `target/identifier/ID` and `target/identifier/IDScheme` | `classid = classname = schema` | | `pid` | `target/identifier/ID` and `target/identifier/IDScheme` | `classid = classname = schema` |
| `publicationdate` | `target/PublicationDate` | clean and normalize the format of the date to be `YYYY-mm-dd` | | `publicationdate` | `target/PublicationDate` | clean and normalize the format of the date to be `YYYY-mm-dd` |
@ -421,6 +89,6 @@ For each target we construct a Bioentity with the following mapping
### Relation Mapping ### Relation Mapping
| OpenAIRE Relation Semantic and inverse | Source/Target type | #Notes | | OpenAIRE Relation Semantic and inverse | Source/Target type | Notes |
|----------------------------------------|---------------------|--------------------------------------------------------------------------| |----------------------------------------|---------------------|--------------------------------------------------------------------------|
| `IsRelatedTo` | `result/result` | we create relationships between the BioEntity and the pubmed publication | | `IsRelatedTo` | `result/result` | we create relationships between the BioEntity and the pubmed publication |

11
docs/data-provision/aggregation/pubmed.md
View File

@ -5,7 +5,7 @@ This section describes the mapping implemented for [MEDLINE/PubMed](https://pubm
## Input ## Input
The native data is collected from the [ftp baseline](https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/) site. The native data is collected from the [ftp baseline](https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/) site.
It contains XML records compliant with the schema available at https://www.nlm.nih.gov/bsd/licensee/elements_descriptions.html. It contains XML records compliant with the schema available at [www.nlm.nih.gov](https://www.nlm.nih.gov/bsd/licensee/elements_descriptions.html).
## Incremental harvesting ## Incremental harvesting
Pubmed exposes an entry point FTP with all the updates for each one. [ftp baseline update](https://ftp.ncbi.nlm.nih.gov/pubmed/updatefiles/). We collect the new file and generate the new dataset by upserting the existing item. Pubmed exposes an entry point FTP with all the updates for each one. [ftp baseline update](https://ftp.ncbi.nlm.nih.gov/pubmed/updatefiles/). We collect the new file and generate the new dataset by upserting the existing item.
@ -14,11 +14,10 @@ Pubmed exposes an entry point FTP with all the updates for each one. [ftp baseli
The table below describes the mapping from the XML baseline records to the OpenAIRE Graph dump format. The table below describes the mapping from the XML baseline records to the OpenAIRE Graph dump format.
| OpenAIRE Result field path | PubMed record field xpath | Notes |
| *OpenAIRE Result field path* | PubMed record field xpath | Notes | |--------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|--------------------------------|--------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **Publication Mapping** | | | | **Publication Mapping** | | |
| `id` | ?? | id in the form `pmid_________::md5(pmid)` | | `id` | `//PMID` | id in the form `pmid_________::md5(pmid)` |
| `pid` | `//PMID` | `classid = classname = pmid` | | `pid` | `//PMID` | `classid = classname = pmid` |
| `publicationdate` | `//PubmedPubDate` | clean and normalize the format of the date to be YYYY-mm-dd | | `publicationdate` | `//PubmedPubDate` | clean and normalize the format of the date to be YYYY-mm-dd |
| `maintitle` | `//Title` | | | `maintitle` | `//Title` | |
@ -38,7 +37,7 @@ The table below describes the mapping from the XML baseline records to the OpenA
| `container.iss` | `//Journal/Issue` | The journal issue | | `container.iss` | `//Journal/Issue` | The journal issue |
| **Instance Mapping** | | | | **Instance Mapping** | | |
| `instance.type` | `//PublicationType` | if the article contains the typology `Journal Article` then we apply this type else We have to find a terms that match the vocabulary otherwise we discard it | | `instance.type` | `//PublicationType` | if the article contains the typology `Journal Article` then we apply this type else We have to find a terms that match the vocabulary otherwise we discard it |
|`type` | <ul><li>`\attributes\types\resourceType`</li> <li> `\attributes\types\resourceTypeGeneral` </li> <li>`attributes\types\schemaOrg`</li></ul> | Using the **_dnet:result_typologies_** vocabulary, we look up the `instance.type` synonym to generate one of the following main entities: <ul><li>`publication`</li> <li>`dataset`</li> <li> `software`</li> <li>`otherresearchproduct`</li></ul> | | `type` | <ul><li>`\attributes\types\resourceType`</li> <li> `\attributes\types\resourceTypeGeneral` </li> <li>`attributes\types\schemaOrg`</li></ul> | Using the **_dnet:result_typologies_** vocabulary, we look up the `instance.type` synonym to generate one of the following main entities: <ul><li>`publication`</li> <li>`dataset`</li> <li> `software`</li> <li>`otherresearchproduct`</li></ul> |
| `instance.pid` | `//PMID` | map the pmid in the pid in the instance | | `instance.pid` | `//PMID` | map the pmid in the pid in the instance |
| `instance.url` | `//PMID` | creates the URL by prepending `https://pubmed.ncbi.nlm.nih.gov/` to the PMId | | `instance.url` | `//PMID` | creates the URL by prepending `https://pubmed.ncbi.nlm.nih.gov/` to the PMId |
| `instance.alternateIdentifier` | `//ArticleId[./@IdType="doi"]` | | | `instance.alternateIdentifier` | `//ArticleId[./@IdType="doi"]` | |