forked from D-Net/openaire-graph-docs
merged commit
This commit is contained in:
Sandro La Bruzzo
commit
f05888e637
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@ -30,14 +30,16 @@ The collection workflow is responsible for aggregating new records. Each record
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The metadata collection process identifies the most recent record date available locally and uses such date to requests the records to the Datacite API, populating the **FROM_DATE_TIMESAMP** variable. The records in the API response are included in the local storage in upsert mode.
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## Datacite Mapping
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### Entity Mapping
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The table below describes the mapping from the XML baseline records to the OpenAIRE Graph dump format.
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| OpenAIRE Result field path | Datacite record JSON path | # Notes |
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|--------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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|--------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| `id` | `\attributes\doi` | id in the form `doi_________::md5(doi)` |
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| <ul><li>`instance`</li> <li>`instance.type`</li></ul> | <ul><li>`\attributes\types\resourceType`</li> <li> `\attributes\types\resourceTypeGeneral` </li> <li>`attributes\types\schemaOrg`</li></ul> | Use the vocabulary **_dnet:publication_resource_** to find a synonym to one of these terms and get the `instance.type`. |
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|`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> |
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| `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> |
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| `pid` | `\attributes\doi` | `scheme = doi` |
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| `originalid` | `\attributes\doi` | |
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| `dateofcollection` | `attributes\updated` | the timestamp is defined in milliseconds we convert to "yyyy-MM-dd'T'HH:mm:ssZ" format |
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@ -60,18 +62,30 @@ The table below describes the mapping from the XML baseline records to the OpenA
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| `publisher` | `\attributes\publisher` | |
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| `language` | `\attributes\language` | cleaned by using vocabulary `dnet:languages` |
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| `publisher` | `\attributes\publisher` | |
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| `instance.license` | `\attributes\rightsList` | if right value starts with http and matches a particular regex |
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| `instance.accessright` | `\attributes\rightsList` | <ul> <li>if not present :`unknown`</li><li>if datasource is _figshare_:`open`</li><li>If `embargo_date < today()`: _OPEN_ </li> </ul> |
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| `instance.license` | `\attributes\rightsList` | if the rights value starts with http and matches a particular regex |
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| `instance.accessright` | `\attributes\rightsList` | <ul><li>if not present :`unknown`</li><li>if datasource is Figshare:`open`</li><li>If `embargo_date < today()`: OPEN</li></ul> |
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### Mapping Relation
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### Relation Mapping
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<<<<<<< HEAD
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| OpenAIRE Relation Semantic and inverse | Datacite record JSON path | Source/Tartget type | #Notes |
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|-------------------------------------------|-------------------------------|-------------------------------|---------|
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| `isProducedBy` |`attributes\fundingReferences` | `Result/Project`| we must identifi if match this pattern `(info:eu-repo/grantagreement/ec/h2020/)(\d{6})(.*)`|
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| `IsProvidedBy` | | `Result/DataSource` | Datasource is always Datacite|
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| `IsHostedBy` | `\attributes\relationships\client\id` | `Result/DataSource` |we defined a curated map clientId/Datasource if we found a match we create an _hostedBy Relation_ |
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| | `\attribute\relatedIdentifiers` | result/result | we create relationships whenever the pid of the target is resolved on the Research Graph |
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=======
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| OpenAIRE Relation Semantic and inverse | Datacite record JSON path | Source/Tartget type | #Notes |
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|----------------------------------------|---------------------------------------|----------------------|---------------------------------------------------------------------------------------------------|
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| `isProducedBy` | `attributes\fundingReferences` | `Result/Project` | we must identifi if match this pattern `(info:eu-repo/grantagreement/ec/h2020/)(\d{6})(.*)` |
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| `IsProvidedBy` | | `Result/DataSource` | Datasource is always Datacite |
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| `IsHostedBy` | `\attributes\relationships\client\id` | `Result/DataSource` | we defined a curated map clientId/Datasource if we found a match we create an _hostedBy Relation_ |
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### Relation Resolution
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>>>>>>> 92baad5acb3ecfb774510b48fee6aeeba92738df
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@ -2,13 +2,403 @@
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This section describes the mapping implemented for [EMBL-EBIs Protein Data Bank in Europe](https://www.ebi.ac.uk/).
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The Europe PMC RESTful Web Service gives the [datalinks API](https://europepmc.org/RestfulWebService#!/Europe32PMC32Articles32RESTful32API)to retrieve data-literature links in Scholix format .
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The Europe PMC RESTful Web Service gives the [datalinks API](https://europepmc.org/RestfulWebService#!/Europe32PMC32Articles32RESTful32API) to retrieve data-literature links in Scholix format.
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## how data is collected
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Starting from the Pubmed collection, we exploit this API to get all the related bioentities related to a Publication with a specific PubMed identifier.
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## How the data is collected
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Following this request: `https://www.ebi.ac.uk/europepmc/webservices/rest/MED/$PMID/datalinks?format=json` we store for each pubmedID the links related.
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Starting from the Pubmed collection, the API below is used to obtain the bioentities related to publications for each PubMed identifier.
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Example:
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```commandline
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curl -s "https://www.ebi.ac.uk/europepmc/webservices/rest/MED/33024307/datalinks?format=json" | jq '.'
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{
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"version": "6.8",
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"hitCount": 9,
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"request": {
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"id": "33024307",
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"source": "MED"
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},
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"dataLinkList": {
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"Category": [
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{
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"Name": "Nucleotide Sequences",
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"CategoryLinkCount": 5,
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"Section": [
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{
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"ObtainedBy": "tm_accession",
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"Tags": [
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"supporting_data"
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],
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"SectionLinkCount": 5,
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"Linklist": {
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"Link": [
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "AY278488",
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"IDScheme": "ENA",
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"IDURL": "http://identifiers.org/ebi/ena.embl:AY278488"
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},
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"Title": "AY278488",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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},
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "MT121216",
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"IDScheme": "ENA",
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"IDURL": "http://identifiers.org/ebi/ena.embl:MT121216"
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},
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"Title": "MT121216",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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},
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "KF367457",
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"IDScheme": "ENA",
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"IDURL": "http://identifiers.org/ebi/ena.embl:KF367457"
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},
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"Title": "KF367457",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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},
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "MN996532",
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"IDScheme": "ENA",
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"IDURL": "http://identifiers.org/ebi/ena.embl:MN996532"
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},
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"Title": "MN996532",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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},
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "MT072864",
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"IDScheme": "ENA",
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"IDURL": "http://identifiers.org/ebi/ena.embl:MT072864"
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},
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"Title": "MT072864",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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}
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]
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}
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}
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]
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},
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{
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"Name": "Protein Structures",
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"NameLong": "Protein structures in PDBe",
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"CategoryLinkCount": 2,
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"Section": [
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{
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"ObtainedBy": "tm_accession",
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"Tags": [
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"supporting_data"
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],
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"SectionLinkCount": 2,
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"Linklist": {
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"Link": [
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "6VW1",
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"IDScheme": "PDB",
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"IDURL": "http://identifiers.org/pdbe/pdb:6VW1"
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},
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"Title": "6VW1",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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},
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{
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"ObtainedBy": "tm_accession",
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"PublicationDate": "04-11-2022",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "References"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "MED"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "2AJF",
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"IDScheme": "PDB",
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"IDURL": "http://identifiers.org/pdbe/pdb:2AJF"
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},
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"Title": "2AJF",
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"Publisher": {
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"Name": "Europe PMC"
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}
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},
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"Frequency": 1
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}
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]
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}
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}
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]
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},
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{
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"Name": "Altmetric",
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"CategoryLinkCount": 1,
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"Section": [
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{
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"ObtainedBy": "ext_links",
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"Tags": [
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"altmetrics"
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],
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"SectionLinkCount": 1,
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"Linklist": {
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"Link": [
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{
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"ObtainedBy": "ext_links",
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"PublicationDate": "15-10-2020",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "IsReferencedBy"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "PMID"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "https://www.altmetric.com/details/91880755",
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"IDScheme": "URL",
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"IDURL": "https://www.altmetric.com/details/91880755"
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},
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"Title": "Characteristics of SARS-CoV-2 and COVID-19",
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"Publisher": {
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"Name": "Altmetric"
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},
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"ImageURL": "https://api.altmetric.com/v1/donut/91880755_64.png"
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}
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}
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]
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}
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}
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]
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},
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{
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"Name": "BioStudies: supplemental material and supporting data",
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"CategoryLinkCount": 1,
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"Section": [
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{
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"ObtainedBy": "ext_links",
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"Tags": [
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"supporting_data"
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],
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"SectionLinkCount": 1,
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"Linklist": {
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"Link": [
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{
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"ObtainedBy": "ext_links",
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"PublicationDate": "11-03-2021",
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"LinkProvider": {
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"Name": "Europe PMC"
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},
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"RelationshipType": {
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"Name": "IsReferencedBy"
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},
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"Source": {
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"Type": {
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"Name": "literature"
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},
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"Identifier": {
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"ID": "33024307",
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"IDScheme": "PMID"
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}
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},
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"Target": {
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"Type": {
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"Name": "dataset"
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},
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"Identifier": {
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"ID": "http://www.ebi.ac.uk/biostudies/studies/S-EPMC7537588?xr=true",
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"IDScheme": "URL",
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"IDURL": "http://www.ebi.ac.uk/biostudies/studies/S-EPMC7537588?xr=true"
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},
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"Title": "Characteristics of SARS-CoV-2 and COVID-19.",
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"Publisher": {
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"Name": "BioStudies: supplemental material and supporting data"
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}
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}
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}
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]
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}
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}
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]
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}
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]
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}
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}
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```
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## Mapping
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The table below describes the mapping from the EBI links records to the OpenAIRE Graph dump format.
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|
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@ -9,7 +9,8 @@ It contains XML records compliant with the schema available at https://www.nlm.n
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## Incremental harvesting
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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.
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## Mapping
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||||
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## Entity Mapping
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||||
|
||||
The table below describes the mapping from the XML baseline records to the OpenAIRE Graph dump format.
|
||||
|
||||
|
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|
|||
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