NISO Virtual Conference 19 February 2014 Ralph Swick, W3C The Web of Data NISO Virtual Conference 19 February 2014 Ralph Swick, W3C

Agenda Data is changing our lives W3C’s traditional focus Expanding scope of W3C’s data activities

Web has transformed our relation to computers and to data A computer in every pocket Apps leveraging context geolocation and other sensors social context (“I’m at the conference, too!”) Change in the use of search people search for answers, not sites answers from aggregated data (Siri, Google Now, Wolfram Alpha)

Apps are using data from many sources Social networking Mobile devices Sensors Open data

Imagine… A “Web” where documents are available for download on the Internet but there would be no hyperlinks among them

Data on the Web is not enough… We need a proper infrastructure for a real Web of Data where: data are available on the Web accessible via standard Web technologies data are interlinked over the Web data can be integrated over the Web This is Linked Data

Agenda Data is changing our lives W3C’s traditional focus Expanding scope of W3C’s data activities

Semantic Web Core RDF data model RDF Schema vocabulary design RDB2RDF relational DB export SPARQL query SKOS vocabulary description OWL ontological inference RIF rules interchange LDP read-write Web of Data POWDER description resources GRDDL app-specific XML

Need for RDF schemas First step towards the “extra knowledge”: define the terms we can use what restrictions apply what extra relationships are there? “RDF Vocabulary Description Language” the term “Schema” is retained for historical reasons…

Vocabularies There is a need for “languages” to define such vocabularies to define those vocabularies to assign clear “semantics” on how new relationships can be deduced

SKOS SKOS provides a simple bridge between the “print world” and the (Semantic) Web Thesauri, glossaries, etc., from the library community can be made available SKOS can also be used to organize, e.g., tags, annotate other vocabularies, …

Semantic Web/Linked Data Today Standards are mature some level of maintenance work is always needed Server-side applications dominate Commercial applications exist, e.g.: direct integration/usage of linked data on the Web consumption of other formats converted internally to a common format (RDF)

Challenge: leverage data in interoperable apps Public, private, behind enterprise firewalls From informal to highly curated From machine readable to human readable HTML tables, twitter feeds, local vocabularies, spreadsheets, … Expressed in diverse data models tree, graph, table, … Serialized in many ways XML, CSV, RDF, PDF, JSON, HTML Tables,…

The Linking Open Data Project

Linked Data Principles Is your data 5 Star? Available on the Web in some format (i.e., use URI to access the data) Available as machine-readable structured data (e.g., excel instead of an image scan) As before, but using a non-proprietary format (e.g., CSV instead of excel) All the above, plus use open standards (RDF & Co.) to identify things, so that people could point at your stuff All the above, plus link your data to other people’s data to provide context

A Three Star Example

The importance of Linked Data Provide a core set of data that applications can build on stable references for “things”, e.g., http://dbpedia.org/resource/Kolkata/ many many relationships that applications may reuse a “nucleus” for a larger, semantically enabled Web!

Linked Data Platform (LDP) Define an HTTP/RESTful based infrastructure to publish, read, write, or modify linked data typical usage: data intensive application in a browser, application integration using shared data… The infrastructure should be easy to implement and install provides an “entry point” for Linked Data applications! The work is nearing completion

RDF with HTML: RDFa By adding some “meta” information, the same source can be reused typical example: your personal information, like address, should be readable for humans and processable by machines Some solutions have emerged: add extra statements in microdata or RDFa that can be converted to RDF microdata can be used for a (useful) subset of RDF RDFa is, essentially, a complete serialization of RDF

schema.org Schema.org is a cooperation of search engines (Bing, Google, Yahoo!, and Yandex) It is a large vocabulary that they all understand The terms are extracted from HTML5+microdata or HTML5+RDFa the various partners use it for different purposes it can be used by anyone outside of the search world!

Some things to remember when you publish data Publish your data first, do user interfaces later! the “raw data” can become useful on its own right and others may use it you can add your added value later by providing nice user access If possible, publish your data in RDF but if you cannot, others may help you in conversions trust the community… Add links to other data. “Just” publishing isn’t enough…

Some things to remember when you publish data (2) Think about persistence and versioning others may depend on the data you publish… Be thoughtful about the URIs you choose Try to avoid reinventing the wheel when choosing vocabularies

Some things to remember when you publish data (3) Document your data, i.e., provide metadata there are vocabularies to do this Data Catalog Vocabulary (DCAT) Vocabulary of Interlinked Datasets (VoID) DCTERMS vocabularies for licensing (Open Data Commons, government licenses) this area is still very much in development…

Agenda Data is changing our lives W3C’s work on data integration Expanding scope of W3C’s data activities

New work underway CSV on the Web Data on the Web Best Practices Vocabulary management

What we are hearing CSV is everywhere Metadata is essential can be huge data sets, not easily readable in a spreadsheet or Google refine meaning of data not in machine-readable form data is not necessarily used for web-scale integration but rather immediate usage Metadata is essential Conversion is an issue European Commission Study on business models for Linked Open Government Data (BM4LOGD)

Linked Data Benefits (BM4LOD) Flexible data integration Streamlined internal processes Where working relationships already exist, much easier to share Linking reference collections; discovery of new relationships Increase in data quality More use of data internally brings errors to light Use of open standards increases quality of system New services Cost reduction Increased efficiency Increase in data usage due to LOD enrichment

CSV on the Web How W3C can help metadata vocabulary to describe CSV data (structure, reference to access rights, annotations, etc.) metadata discovery (e.g., part of an HTTP header, special rows and columns, packaging formats…) mapping content to RDF, JSON, XML - The WG is planned for about 18 months to publish a REC, with the technical design being done in about a year, ie, end of 2014 - but the timeline is not yet finalized. - The experiences of the RDB2RDF will be very helpful for the mapping part.

Best practices Document best practices for the data publishers URI design, management of persistence, versioning business models use of core metadata vocabularies (provenance, access control, ownership) Specific vocabularies quality, application descriptions, … - Quality and Granularity Description Vocabulary (what is the quality of the data, how frequently is it updated, does it accept user corrections). Application description vocabulary (what does the application do, what problem does it help to solve, which data sets does it use). The timeline is not yet finalized, the vocabularies-s should be available at the end of 2014. The best practices may take longer.

Vocabulary management: challenge Interoperable vocabularies are key for (meta)data At the moment, it is a fairly chaotic world… many, possibly overlapping vocabularies difficult to locate the one that is needed vocabularies may not be properly managed, maintained, versioned, provided persistence…

Vocabulary management: how W3C can help Provide a space where communities can develop vocabularies (through, e.g., CGs, possibly WGs) host vocabularies at W3C if requested annotate vocabularies with a proper set of metadata terms establish a vocabulary directory The exact structure is still being discussed

Summary Data-driven smart apps are one of the major growth engines for the worldwide software market. We need to meet developers where they are. 5 Star Benefits of LOD Greater efficiency, better provision of the task Greater flexibility leads to lower costs for future projects New services, new connections, new discoveries Improved navigation within and between datasets Others can build apps based on your data

Available specifications: Primers, Guides` RDF Primer OWL Guide SKOS Primer GRDDL Primer RDFa Primer The W3C Semantic Web Activity Wiki has links to all the specifications

These slides are in the Web at http://www.w3.org/2014/Talks /0219-NISO-RRS with thanks to Ivan Herman, W3C and Phil Archer, W3C