descriptions updated
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### SSHOC Multilingual Data Stewardship terminology and Multilingual Metadata SKOSifying mapping
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### SSHOC Multilingual Data Stewardship terminology and Multilingual Metadata SKOSifying mapping
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This Jupyter Notebook implements a simple parser used to transform the SSHOC Multilingual Data Stewardship Terminology (http://hdl.handle.net/20.500.11752/ILC-567) and the SSHOC Multilingual Metadata (http://hdl.handle.net/20.500.11752/ILC-568), created in task 3.1 of the Social Sciences & Humanities Open Cloud (SSHOC) project, into SKOS resources.
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These Jupyter Notebooks implement a parser used to transform the [SSHOC Multilingual Data Stewardship Terminology](http://hdl.handle.net/20.500.11752/ILC-567) and the [SSHOC Multilingual Metadata](http://hdl.handle.net/20.500.11752/ILC-568), created during the Social Sciences & Humanities Open Cloud (SSHOC) project, into SKOS resources.
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The parser transforms the content in SKOS data following a set of mapping rules, the result is stored in *Turtle* and *rdf* files.
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The parsers transform the content in SKOS data following a set of mapping rules, the result is stored in *Turtle* and *rdf* files.
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##### Installation
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##### Installation
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It is recommended to install this notebook in a virtual environment to avoid dependency clash.
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It is recommended to install this notebook in a virtual environment to avoid dependency clash.
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@ -10,7 +10,7 @@ prefixes:
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mappings:
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mappings:
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conceptscheme:
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conceptscheme:
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sources:
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sources:
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- ['data.json~jsonpath', '$']
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- ['this~jsonpath', '$']
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s: skos:_
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s: skos:_
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po:
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po:
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- [a, skos:conceptScheme]
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- [a, skos:conceptScheme]
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@ -20,7 +20,7 @@ mappings:
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concept:
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concept:
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sources:
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sources:
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- ['data.json~jsonpath', '$.concepts[*]']
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- ['this~jsonpath', '$.concepts[*]']
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s: sshoccmd:$(ConceptId)
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s: sshoccmd:$(ConceptId)
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po:
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po:
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- [a, skos:Concept]
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- [a, skos:Concept]
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@ -7,8 +7,7 @@
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"source": [
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"source": [
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"## Mapping *SSHOC Multilingual Metadata* to SKOS resources \n",
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"## Mapping *SSHOC Multilingual Metadata* to SKOS resources \n",
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"\n",
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"\n",
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"This Notebook implements a simple parser used to transform the SSHOC Multilingual Metadata, created in the Task 3.1 of the SSHOC project and published as spreadsheets, into SKOS resources. The parser reads the spreadsheet and transforms the content in SKOS data following a set of mapping rules defined using [YRRRML](https://rml.io/yarrrml/) , the result is stored in Turtle files, and downloaded in a Fuseki server.\n",
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"This Notebook implements a simple parser used to transform the SSHOC Multilingual Metadata, created in the Task 3.1 of the SSHOC project and published as spreadsheet, into a SKOS resource. The parser reads the spreadsheet and transforms the content following a set of mapping rules defined using [YRRRML](https://rml.io/yarrrml/) , the result is stored in Turtle files, and downloaded in a Fuseki server."
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"\n"
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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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@ -161,7 +161,7 @@
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{
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{
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"data": {
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"data": {
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"text/plain": [
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"text/plain": [
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"<Graph identifier=N7b4b69840f2f484db36d3362b518a9b0 (<class 'rdflib.graph.Graph'>)>"
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"<Graph identifier=Nfbc9b96ef4c047d9a72e68d22f8fc441 (<class 'rdflib.graph.Graph'>)>"
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]
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]
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},
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},
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"execution_count": 7,
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"execution_count": 7,
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@ -217,18 +217,10 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": null,
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"id": "failing-relative",
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"id": "failing-relative",
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [],
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4577\n"
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]
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}
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],
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"source": [
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"source": [
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"for index, row in df_data.iterrows():\n",
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"for index, row in df_data.iterrows():\n",
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" \n",
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" \n",
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@ -317,7 +309,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": null,
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"id": "earlier-slovak",
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"id": "earlier-slovak",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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@ -336,7 +328,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": null,
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"id": "treated-spotlight",
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"id": "treated-spotlight",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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@ -355,7 +347,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": null,
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"id": "olive-archive",
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"id": "olive-archive",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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@ -366,7 +358,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": null,
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"id": "square-michael",
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"id": "square-michael",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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@ -389,7 +381,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": null,
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"id": "patient-winner",
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"id": "patient-winner",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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@ -409,21 +401,10 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": null,
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"id": "least-waterproof",
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"id": "least-waterproof",
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [],
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{
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"data": {
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"text/plain": [
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"<Graph identifier=N55bbc6f024264113946ce17315badffc (<class 'rdflib.graph.Graph'>)>"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"source": [
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"now = datetime.datetime.today()\n",
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"now = datetime.datetime.today()\n",
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"today_date=now.date()\n",
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"today_date=now.date()\n",
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@ -461,18 +442,10 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": null,
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"id": "confirmed-montana",
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"id": "confirmed-montana",
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [],
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"3494\n"
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]
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}
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],
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"source": [
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"source": [
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"topconcepts=[]\n",
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"topconcepts=[]\n",
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"for index, row in df_metadata.iterrows():\n",
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"for index, row in df_metadata.iterrows():\n",
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@ -539,7 +512,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": null,
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"id": "greater-thunder",
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"id": "greater-thunder",
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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@ -573,7 +546,7 @@
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"name": "python",
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"name": "python",
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"nbconvert_exporter": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"pygments_lexer": "ipython3",
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"version": "3.10.0"
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"version": "3.11.1"
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}
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}
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},
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},
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"nbformat": 4,
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"nbformat": 4,
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