Introduction to metadata cleansing using SPARQL update queries. April 2014 PwC EU Services

Transcription

1 Introduction to metadata cleansing using SPARQL update queries April 2014 PwC EU Services

2 Learning objectives By the end of this module, you will have an understanding of: How to transform your metadata using simple SPARQL Update queries How to conform to the ADMS-AP to get your interoperability solutions ready to be shared on Joinup The main types of errors that you could face when uploading metadata of interoperability solutions on Joinup 2

3 How can this tutorial help you? Interoperability solutions owners may have the possibility to generate automatically in RDF the descriptive metadata of their solutions. Sometimes, this metadata may not be conform to the ADMS Application Profile for Joinup (ADMS-AP), preventing it from being uploaded on Joinup. This tutorial provides basic knowledge on how to transform and cleanse RDF metadata using SPARQL Update queries in order to conform to the ADMS- AP. Since its launch in 2011 Joinup has been steadily growing in popularity. It currently receives more than visits per month and is hosting some 130 online communities. SPARQL is the query language for RDF and also allows for creating, updating and deleting RDF triples. ADMS-AP: 3

4 Outline 1. The context ADMS-AP for describing your interoperability solutions About SPARQL About RDF 2. Construct ADMS-AP compliant RDF Why? Construct queries 3. Metadata cleansing Why? The main queries 3 examples 4. Metadata upload to Joinup 4

5 What is the ADMS Application Profile for Joinup (ADMS-AP) The Asset Description Metadata Schema Application Profile is a common vocabulary used for all type of interoperability solutions. It allows interoperability solutions providers to describe their solutions and easily upload the descriptions on Joinup. It allows users to easily discover and re-use interoperability solutions coming from Joinup using a common vocabulary. 5

6 ADMS-AP for describing your interoperability solutions on Joinup Public administrations Repository Academic Explore Find Select Obtain Using the ADMS Application Profile ADMS-AP Your repository Standardisation bodies Repository Businesses Repository 6

7 Automatic or manual path to generate ADMS-AP Transformation with Open Refine Interoperability solutions Cleansing with SPARQL This tutorial focuses on the automatic path to generate ADMS-AP compliant RDF. See how to transform with Open Refine: tion_to_open_refine_rdf_tool.pptx 7

8 SPARQL Protocol and RDF Query Language (SPARQL) SPARQL is the standard language to query graph data represented as RDF triples. o One of the three core standards of the Semantic Web, along with RDF and OWL. o Became a W3C standard January o SPARQL 1.1 standard as of

9 The Resource Description Framework (RDF) RDF represents data as (subject, predicate, object) triples. A set of triples is an RDF graph. rdf:type dct:title adms:asset My asset name Resources (URIs), often abbreviated NB: subjects and objects may also be blank nodes. Resources Plain literals: Text, Typed literals: 42 ^^xsd:integer, ^^xsd:date 9

10 A graph can be represented with different syntaxes RDF/XML required by Joinup <rdf:description about= > <rdf:type rdf:resource= /> <dct:title>my asset name</dct:title> <dct:description>description of the asset</dct:description> <dct:modified rdf:datatype= > T00:00:00Z </dct:modified> </rdf:description> Turtle used in SPARQL and in this tutorial dct:title My asset name ; dct:description Description of the asset ; dct:modified T00:00:00Z ^^xsd:datetime. Syntaxes are equivalent. It is easy to transform one into another. 10

11 SPARQL is a query language for RDF data Query: SELECT * WHERE {?asset dct:title?title. } Graph pattern: an RDF graph with placeholder variables (e.g.,?asset) dct:title My asset name ; dct:description Description of the asset ; dct:modified T00:00:00Z ^^xsd:datetime. < dct:title Your asset name ; dct:description Another asset. Results:?asset < My asset name Your asset name 11

12 SPARQL queries have many forms SPARQL SELECT to query data from a graph (not used in this tutorial) SPARQL CONSTRUCT to transform one graph into another (used for creating ADMS-AP from existing RDF) SPARQL Update to modify a graph in place (used to cleanse ADMS-AP metadata) 12

13 A useful tool to transform RDF files Used to create and edit RDF files and run SPARQL queries over them. A free version is also available. TopBraid Composer is the leading industrial-strength RDF editor and OWL ontology editor, as well as the best SPARQL tool on the market. Source: For download: 13

14 Outline 1. The context ADMS-AP for describing your interoperability solutions About SPARQL About RDF 2. Construct ADMS-AP compliant RDF Why? Construct queries 3. Cleanse metadata Why? The main queries 3 examples 4. Metadata upload to Joinup 14

15 Construct ADMS-AP from existing RDF Why? You may already have the metadata description of your interoperability solutions in a RDF file that is not compliant with ADMS-AP (e.g. missing out on mandatory properties or on the use of recommended controlled vocabularies). The following slides help you to create a compliant ADMS-AP RDF graph from your initial RDF. 15

16 Construct ADMS-AP from existing RDF using a SPARQL CONSTRUCT query CONSTRUCT {?asset dct:title?title ; dct:description?description ; dct:modified?modified ; dct:type < ; dct:relation?related ; dcat:distribution?d.?d a adms:assetdistribution ; dcat:accessurl?asset. Result graph to construct } WHERE { }?asset a voaf:vocabulary ; dct:title?title ; dct:description?description ; dct:modified?modified. OPTIONAL {?asset voaf:similar?related } BIND(IRI(CONCAT(STR(?asset), "?type=distribution")) AS?d) Graph pattern to query Recommended and optional fields Construct new URIs using expressions 16

17 Construct ADMS-AP from existing RDF the result is a new RDF graph < a voaf:vocabulary ; dct:title Food ; dct:description This ; dct:modified ; voaf:similar < /food>. < a voaf:vocabulary ; dct:title Food Ontology in ; dct:description Along ; dct:modified < dct:title Food ; dct:description This ; dct:modified ; dct:type < ; dct:relation < ; dcat:distribution < < a adms:assetdistribution ; dcat:accessurl < < dct:title Food Ontology in ; dct:description Along ; dct:modified ; dct:type < ; dcat:distribution < /food?type=distribution>. Example from the Linked Open Vocabulary repository. < /food?type=distribution> a adms:assetdistribution ; dcat:accessurl < /food>

18 Outline 1. The context ADMS-AP for describing your interoperability solutions About SPARQL About RDF 2. Construct ADMS-AP compliant RDF Why? Construct queries 3. Metadata cleansing Why? The main queries 3 examples 4. Metadata upload to Joinup 18

19 Metadata cleansing Why? You may need to make some small modifications to your RDF graph in order to have it fully compliant to ADMS-AP Only ADMS-AP compliant descriptive metadata can be uploaded on Joinup. Joinup has a built-in ADMS-AP validation feature to help you pinpoint inconsistencies with the standard. 19

20 Metadata cleansing with SPARQL update queries Add static triples (INSERT DATA) Remove static triples (DELETE DATA) Modify static triples (combine INSERT DATA and DELETE DATA) Add triples based on query results (INSERT) Remove triples based on query results (DELETE) Modify triples based on query results (DELETE/INSERT) For more info:

21 Metadata cleansing add static triples Example: add the title of a specific interoperability solution (modelled as an adms:asset) Query: INSERT DATA { dct:title Asset } Before: dct:description Description. After: dct:title Asset ; dct:description Description. 21

22 Metadata cleansing remove static triples Example: remove an erroneous date of a specific asset Query: DELETE DATA { dct:issued ^^xsd:date. } Before: dct:title Asset ; dct:description Description ; dct:issued ^^xsd:date. After: dct:title Asset ; dct:description Description. 22

23 Metadata cleansing modify static triples Example: modify the title of a specific asset Query: DELETE DATA { dct:title Asset } INSERT DATA { dct:title My asset } Before: dct:title Asset ; dct:description Description. After: dct:title My asset ; dct:description Description. 23

24 Metadata cleansing add triples based on query results Example: add asset type for all assets whose name contain Schema Query: INSERT {?asset dct:type < } WHERE {?asset dct:title?title. FILTER(CONTAINS(?title, Schema )) } Before: dct:title My Asset Schema ; dct:description Description. < dct:title Your Asset Vocabulary. After: dct:title My Asset Schema ; dct:description Description ; dct:type < < dct:title Your Asset Vocabulary. 24

25 Metadata cleansing remove triples based on query results Example: remove all asset modification dates in the future Before: Query: DELETE {?asset dct:modified?date. } WHERE {?asset dct:modified?date. FILTER(?date > NOW()) } dct:title Asset ; dct:modified T00:00:00Z ^^xsd:datetime. < dct:title Your Asset Vocabulary ; dct:modified T11:42:22Z ^^xsd:datetime. After: dct:title Asset ; dct:description Description. < dct:title Your Asset Vocabulary ; dct:modified T11:42:22Z ^^xsd:datetime. 25

26 Metadata cleansing modify triples based on query results Example: replace a word in all asset titles Query: DELETE {?asset dct:title?title. } INSERT {?asset dct:title?newtitle. } WHERE {?asset dct:title?title. BIND(REPLACE(?title, grt, great ) AS?newtitle) } Before: dct:title My grt asset. < dct:title Your asset. After: dct:title My great asset. < dct:title Your asset. 26

27 Metadata cleansing Proposed fixes for 3 common issues Ensure all text fields have a language tag Transform date strings into xsd:datetime values Add missing asset modification dates 27

28 Metadata cleansing Ensure all text fields have a language tag Query: DELETE {?s?p?o. } INSERT {?s?p?olang. } WHERE {?s?p?o. FILTER(?p IN (foaf:name, dct:title, dct:description)) FILTER(LANG(?o) = ) BIND(STRLANG(?o, en ) AS?olang) } Before: dct:title Asset name ; dct:description After: dct:title Asset ; dct:description 28

29 Metadata cleansing Transform YYYY-MM-DD strings into xsd:datetime values Query: DELETE {?s dct:modified?str. } INSERT {?s dct:modified?date. } WHERE {?s dct:modified?str. BIND(xsd:dateTime(CONCAT(?str, T00:00:00Z )) AS?date) } Before: dct:title Asset ; dct:description ; dct:modified After: dct:title Asset ; dct:description ; dct:modified T00:00:00Z ^^xsd:datetime. 29

30 Metadata cleansing Add missing asset modification dates, copying the creation date Before: Query: INSERT {?asset dct:modified?date. } WHERE {?asset dct:issued?date. FILTER NOT EXISTS {?asset dct:modified?modified } } dct:title Asset ; dct:issued T00:00:00Z ^^xsd:datetime. < dct:title Your ; dct:issued T00:00:00Z ^^xsd:datetime ; dct:modified T00:00:00Z ^^xsd:datetime. After: dct:title Asset ; dct:issued T00:00:00Z ^^xsd:datetime ; dct:modified T00:00:00Z ^^xsd:datetime. < dct:title Your ; dct:issued T00:00:00Z ^^xsd:datetime ; dct:modified T00:00:00Z ^^xsd:datetime. 30

31 Outline 1. The context ADMS-AP for describing your interoperability solutions About SPARQL About RDF 2. Construct ADMS-AP compliant RDF Why? Construct queries 3. Metadata cleansing Why? The main queries 3 examples 4. Metadata upload to Joinup 31

32 Metadata upload to Joinup Upload an RDF/XML file to Joinup 1. On your repository page, click on Upload metadata 2. Select the RDF/XML file 3. Click on Upload the metadata file

33 Metadata upload to Joinup Get the upload status 1. Log in with your account 2. Go to the repository page 3. Click on Report file 33

34 Metadata upload to Joinup Reading the upload log Lines have the format: :36:02 INFO - Treatment of the repository Timestamp Level Message INFO WARN ERROR Information message Warning (you may ignore it) Error (you should fix it) 34

35 Related learning resources Introduction to ADMS-AP How to import and export ADMS-AP conform metadata of interoperability solutions on Joinup Introduction to the Open Refine RDF tool Using Joinup as catalogue for interoperability solutions Introduction to the advanced search functionality of EFIR 35

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