Downloaded 31 times
![Conversions: JSON
countryCode latitude longitude name
AD 42.5 1.6 Andorra
AE 23.4 53.8 United Arab
Emirates
AF 33.9 67.7 Afghanistan
countries.csv
16
{
"tables": [{
"url": "http://example.org/countries.csv",
"row": [{
"url": "http://example.org/countries.csv#row=2",
"rownum": 1,
"describes": [{
"countryCoe": "AD",
"latitude": "42.5",
"longitude": "1.6",
"name": "Andorra"
}]
}, {
"url": "http://example.org/countries.csv#row=3",
"rownum": 2,
"describes": [{
"countryCode": "AE",
"latitude": "23.4",
"longitude": "53.8",
"name": "United Arab Emirates"
}]
}, {
"url": "http://example.org/countries.csv#row=4",
"rownum": 3,
"describes": [{
"countryCode": "AF",
"latitude": "33.9",
"longitude": "67.7",
"name": "Afghanistan"
}]
}]
}]
}
countries.json
countries-standard.json](https://image.slidesharecdn.com/smartdata2015-150725201812-lva1-app6891/75/Tabular-Data-on-the-Web-16-2048.jpg)
![Conversions: JSON (min)
countryCode latitude longitude name
AD 42.5 1.6 Andorra
AE 23.4 53.8 United Arab
Emirates
AF 33.9 67.7 Afghanistan
17
[{
"countryCode": "AD",
"latitude": "42.5",
"longitude": "1.6",
"name": "Andorra"
}, {
"countryCode": "AE",
"latitude": "23.4",
"longitude": "53.8",
"name": "United Arab Emirates"
}, {
"countryCode": "AF",
"latitude": "33.9",
"longitude": "67.7",
"name": "Afghanistan"
}]
countries.csv
countries.json
countries-minimal.json](https://image.slidesharecdn.com/smartdata2015-150725201812-lva1-app6891/75/Tabular-Data-on-the-Web-17-2048.jpg)
![Conversions: RDF
countryCode latitude longitude name
AD 42.5 1.6 Andorra
AE 23.4 53.8 United Arab
Emirates
AF 33.9 67.7 Afghanistan
18
@base <http://example.org/countries.csv> .
@prefix csvw: <http://www.w3.org/ns/csvw#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
_:tg a csvw:TableGroup ;
csvw:table [ a csvw:Table ;
csvw:url <http://example.org/countries.csv> ;
csvw:row [ a csvw:Row ;
csvw:rownum "1"^^xsd:integer ;
csvw:url <#row=2> ;
csvw:describes _:t1r1
], [ a csvw:Row ;
csvw:rownum "2"^^xsd:integer ;
csvw:url <#row=3> ;
csvw:describes _:t1r2
], [ a csvw:Row ;
csvw:rownum "3"^^xsd:integer ;
csvw:url <#row=4> ;
csvw:describes _:t1r3
]
] .
_:t1r1
<#countryCode> "AD" ;
<#latitude> "42.5" ;
<#longitude> "1.6" ;
<#name> "Andorra" .
_:t1r2
<#countryCode> "AE" ;
<#latitude> "23.4" ;
<#longitude> "53.8" ;
<#name> "United Arab Emirates" .
_:t1r3
<#countryCode> "AF" ;
<#latitude> "33.9" ;
<#longitude> "67.7" ;
<#name> "Afghanistan" .
countries.csv
countries.json
countries-standard.ttl](https://image.slidesharecdn.com/smartdata2015-150725201812-lva1-app6891/75/Tabular-Data-on-the-Web-18-2048.jpg)
Uploaded byGregg Kellogg
Tabular Data on the Web
Tabular data represents a large amount of published data on the web. The W3C CSV on the Web working group aims to improve interoperability of CSV and similar tabular formats by developing specifications for metadata, data models, and conversions between CSV, JSON, and RDF. The specifications define methods for parsing CSV into structured models, associating CSV with metadata to provide data typing and relationships, and converting between tabular and other common data formats.
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Tabular Data on the Web
- 1. Tabular Data onthe Web Intro to W3C CSV on the Web Specifications Gregg Kellogg gregg@greggkellogg.net @gkellogg 1
- 2. Impact of TabularData • Tabular Data represents a large amount of all data published on the Web • According to the Open Data Institute, the vast majority of published open data is tabular • “Over 90% of the data on data.gov.uk is tabular data.” • data.gov lists 158,631 datasets; largely in CSV 2
- 3. Sources of TabularData • Easiest way to publish data • Spreadsheet Dumps • Database Dumps • SPARQL results 3
- 4. CSV data isdumb • It’s a simple text format, data has no inherent meaning. • Cells may be data-typed or have a regular format: what does “08/09/2015” mean? • Cells may be related to data in other tables/ columns: Foreign Keys • Cells may be associated with different entities: Join results 4
- 5. Web CSV • 5-starLinked Data • CSV URLs • CSVs link to other CSVs • CSVs link to other Resources • RDF and JSON conversion 5
- 6. W3C CSV onthe Web • Working Group chartered to allow applications to provide higher interoperability with working with CSV, or similar formats. • Use Cases: http://www.w3.org/TR/csvw-ucr/ • Model for Tabular Data and Metadata on the Web: http:// www.w3.org/TR/tabular-data-model/ • Metadata Vocabulary for Tabular Data: http://www.w3.org/TR/tabular- metadata/ • Generating JSON from Tabular Data on the Web: http://www.w3.org/ TR/csv2json/ • Generating RDF from Tabular Data on the Web: http://www.w3.org/ TR/csv2rdf/ 6
- 7. Examples 7 countryCode latitude longitudename AD 42.5 1.6 Andorra AE 23.4 53.8 United Arab Emirates AF 33.9 67.7 Afghanistan countries.csv countryRef year population AF 1960 9,616,353 AF 1961 9,799,379 AF 1961 9,989,846 country_slice.csv
- 8. Model for TabularData id Table Group id Table notes transformations about URL cells datatype default Column lang name number ordered property URL required separator table text direction titles value URL virtual cells number primary key titles Row referenced rows source number table about URL column errors ordered Cell property URL row string value table text direction value value URL 8 notes foreign keys other annotations url other annotations tables columns rows table direction other annotations rows table
- 9. Mapping CSV toModel • Parse CSV: RFC4180 + dialect metadata. • delimiter, doubleQuote, headerRowCount, lineTerminators, quoteChar, … • Dialect Description comes from Metadata Document. • Match Headers to Columns. • Parse Cells using Column metadata/datatype. • Abstract data model used for viewing, validation, and conversions. 9
- 10. Metadata • Finding Metadatafrom a CSV • User-specified, Link Header, well-known locations • Matching Metadata to a CSV • CSV must be compatible with metadata (titles/ names) • Metadata must reference CSV URL 10
- 11. foreignKeys columns @id @type Schema primaryKey rowTitles 11 url targetFormat scriptFormat titles source @id @type Transformation Definition name titles required suppressOutput virtual @id @type Column Description columnReference reference Foreign Key Definition resource schemaReference columnReference ForeignKey Reference array property link property URI template property column reference property object property natural language property atomic property Legend: reference to an array of values of a specific category reference to a value of a specific category @language @base Top-Level Properties tables transformations tableDirection tableSchema dialect @context @id Table Group notes @type decimalChar groupChar pattern Number Format url transformations tableDirection tableSchema dialect notes Table @context @id @type suppressOutput null lang textDirection separator ordered default datatype Inherited Properties aboutUrl propertyUrl valueUrl required base format length minLength maxLength minimum maximum Datatype Description minInclusive maxInclusive minExclusive maxExclusive @id @type encoding lineTerminators quoteChar doubleQuote skipRows commentPrefix header Dialect Description headerRowCount skipBlankRows skipInitialSpace trim @id delimiter skipColumns
- 12. Schema • Column Descriptions •Names/Titles • Datatype • Primary Keys • Foreign Key Relationships 12
- 13. Embedded Metadata • GenerallyColumn Titles. • Formats may define CSV conventions for embedded metadata. • Principally used to determine metadata compatibility. • Also serves as default metadata if no file located. 13
- 14. Datatypes • Basic XSDdatatypes • maximum/minimum facets • minLength/maxLength facets • format/pattern • RegExp, Boolean, UAX35 date/time picture string, UAX35 number picture string 14
- 15. Other Features • Splitcells into multiple items • Validate Primary Keys and Foreign Key references (single and multiple columns) • Define URL properties for columns • Multiple subjects per column (may be URLs) • Values as URLs 15
- 16. Conversions: JSON countryCode latitudelongitude name AD 42.5 1.6 Andorra AE 23.4 53.8 United Arab Emirates AF 33.9 67.7 Afghanistan countries.csv 16 { "tables": [{ "url": "http://example.org/countries.csv", "row": [{ "url": "http://example.org/countries.csv#row=2", "rownum": 1, "describes": [{ "countryCoe": "AD", "latitude": "42.5", "longitude": "1.6", "name": "Andorra" }] }, { "url": "http://example.org/countries.csv#row=3", "rownum": 2, "describes": [{ "countryCode": "AE", "latitude": "23.4", "longitude": "53.8", "name": "United Arab Emirates" }] }, { "url": "http://example.org/countries.csv#row=4", "rownum": 3, "describes": [{ "countryCode": "AF", "latitude": "33.9", "longitude": "67.7", "name": "Afghanistan" }] }] }] } countries.json countries-standard.json
- 17. Conversions: JSON (min) countryCodelatitude longitude name AD 42.5 1.6 Andorra AE 23.4 53.8 United Arab Emirates AF 33.9 67.7 Afghanistan 17 [{ "countryCode": "AD", "latitude": "42.5", "longitude": "1.6", "name": "Andorra" }, { "countryCode": "AE", "latitude": "23.4", "longitude": "53.8", "name": "United Arab Emirates" }, { "countryCode": "AF", "latitude": "33.9", "longitude": "67.7", "name": "Afghanistan" }] countries.csv countries.json countries-minimal.json
- 18. Conversions: RDF countryCode latitudelongitude name AD 42.5 1.6 Andorra AE 23.4 53.8 United Arab Emirates AF 33.9 67.7 Afghanistan 18 @base <http://example.org/countries.csv> . @prefix csvw: <http://www.w3.org/ns/csvw#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . _:tg a csvw:TableGroup ; csvw:table [ a csvw:Table ; csvw:url <http://example.org/countries.csv> ; csvw:row [ a csvw:Row ; csvw:rownum "1"^^xsd:integer ; csvw:url <#row=2> ; csvw:describes _:t1r1 ], [ a csvw:Row ; csvw:rownum "2"^^xsd:integer ; csvw:url <#row=3> ; csvw:describes _:t1r2 ], [ a csvw:Row ; csvw:rownum "3"^^xsd:integer ; csvw:url <#row=4> ; csvw:describes _:t1r3 ] ] . _:t1r1 <#countryCode> "AD" ; <#latitude> "42.5" ; <#longitude> "1.6" ; <#name> "Andorra" . _:t1r2 <#countryCode> "AE" ; <#latitude> "23.4" ; <#longitude> "53.8" ; <#name> "United Arab Emirates" . _:t1r3 <#countryCode> "AF" ; <#latitude> "33.9" ; <#longitude> "67.7" ; <#name> "Afghanistan" . countries.csv countries.json countries-standard.ttl
- 19. Conversions: RDF (min) countryCodelatitude longitude name AD 42.5 1.6 Andorra AE 23.4 53.8 United Arab Emirates AF 33.9 67.7 Afghanistan 19 @base <http://example.org/countries.csv> . _:t1r1 <#countryCode> "AD" ; <#latitude> "42.5" ; <#longitude> "1.6" ; <#name> "Andorra" . _:t1r2 <#countryCode> "AE" ; <#latitude> "23.4" ; <#longitude> "53.8" ; <#name> "United Arab Emirates" . _:t1r3 <#countryCode> "AF" ; <#latitude> "33.9" ; <#longitude> "67.7" ; <#name> "Afghanistan" . countries.csv countries.json countries-minimal.ttl
- 20. Other examples • RichAnnotations: JSON RDF • Virtual Columns/Multiple Subjects: JSON RDF • For more see Specifications and Test Suite 20
- 21. Tools • CSVLint • CKAN– open source data portal platform • Socrata – cloud-based open data • Google Fusion Tables – data visualization • Ruby rdf-tabular – CSVW reference implementation • RDF Distiller • Structured Data Linter 21
- 22. Next Steps • At-Risk– /.well-known/csvm • More datatype formats • Metadata in HTML (embedded JSON-LD) • Tabular Data in HTML • More implementations! • Timeline • Candidate Recommendation – July 2015 • Proposed Recommendation – Oct 2015 • W3C Recommendation – Dec 2015 22
- 23.