Simplified minimalistic workflows for the publication of Linked Open Data
•Als PPTX, PDF herunterladen•
0 gefällt mir•326 views
Our colleague Yuri Glikman of Fraunhofer FOKUS (LinDA partner) presented the LinDA transformation tool at the recent Samos Summit (http://samos-summit.blogspot.de/).
Empfohlen
Empfohlen
Weitere ähnliche Inhalte
Was ist angesagt?
Was ist angesagt? (19)
Ähnlich wie Simplified minimalistic workflows for the publication of Linked Open Data
Ähnlich wie Simplified minimalistic workflows for the publication of Linked Open Data (20)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
Simplified minimalistic workflows for the publication of Linked Open Data
- 1. LinDA-project.eu Simplified minimalistic workflows for the publication of Linked Open Data Yuri Glikman, Fraunhofer FOKUS
- 2. + Motivation behind LinDA Linked Data is an active research field with currently relatively little activity towards ease of use and accessibility for non- experts. LinDA’s motivation is to bring lay people, especially from SMEs, closer to Linked Data and help them unlock the potential of their data in an affordable manner. help expand the Linked Open Data Cloud by publishing Linked Open Data. 02.07.2015Samos Summit 2015
- 3. + LinDa is… The renovation of Public Sector Information (PSI) and private data A set of tools allowing for a rich holistic workflow that seamlessly facilitates the ease in: 02.07.2015Samos Summit 2015 Icons made by Picol, Freepik, Yannick, Mario Purisic from www.flaticon.com is licensed by CC BY 3.0 RDB CSV Excel … RDF 1. Transforming and semantically enriching your data 2. Publishing your data LOD Cloud Linked Enterprise Data 3. Linking and querying your data 4. Visualising and analysing your data
- 4. + The Transformation Tool The Transformation tool lays the ground work for the subsequent steps in the workflow The state of the Art analysis has shown shortcomings in the current available transformation tools: Most tools lack a simple intuitive UI, tailored for non-experts Rarely any reconciliation methods against LD resources – facilitating 5* Linked Data R2RML, the de-facto standard for mapping RDB to RDF, is not always supported Rarely simple, non technical user guidance is found Non or insufficient integrated ontology finding services 02.07.2015Samos Summit 2015
- 5. + The Transformation Tool: close-up RDF snapshots and on the fly transformation of semi-structured data (e.g. CSV, Excel) SQL re-write and publishing of SPARQL enpoints Re-use of transformation mappings (R2RML + tool specific) Intergration with intelligent vocabulary service for suggesting adequate classes and properties 02.07.2015Samos Summit 2015
- 6. + Upload and start renovating your data 02.07.2015Samos Summit 2015
- 7. + Ontology Finding Access to repository with all public ontologies Oracle Service for best matches Ranking based on popularity and re- use Cross-lingual suggestions 02.07.2015Samos Summit 2015
- 8. + LD resources reconciliation and type guessing Using ‚DBpedia Lookup‘ to reconcile against Linked Data resources Support for 5* Linked Data principles 02.07.2015Samos Summit 2015
- 9. + Semantic enrichment of RDF Allows describing data using the rdf:type for rich queries 02.07.2015Samos Summit 2015
- 10. + View and publish to Triple Store RDF download Publish to preferred Triple Store 02.07.2015Samos Summit 2015
- 11. + LinDA at a glance Grant Agreeement 610565 Start 1/12/2013 Duration 24 months Objective ICT-2013.4.3 - SME Initiative on Analytics Cost 1,931,624.00€ Coordinator National Technical University of Athens More info: http://www.linda-project.eu 02.07.2015Samos Summit 2015
- 13. info @ LinDA-project.eu @LinDA_FP7 + LiNDA-project.eu LinDAFP7 Thank you! Questions? Yuri Glikman, Fraunhofer FOKUS Project Contact @FOKUS Lena Farid (lena.farid@fokus.fraunhofer.de) Technical Project Coordinator Spiros Mouzakitis (smouzakitis@epu.ntua.gr) 02.07.2015 Samos Summit 2015
Hinweis der Redaktion
- - Linked Data is still an academic discipline and very hard for lay users to fathom. Furthermore, With the current state of the art the use of linked data concepts is costly and gives slow ROI as the learning curve is high. This needs to change by creating useful tools and tool chains that abstract its compelxity This is the motivation of linDA to bring lay…. And help expand…
- - The LinDA project will create a set of tools combined into a distinct workflow to help with the seamless renovation of PSI und private data . - By renovation we mean transforming data and semanticallly enriching it to be able to unlock ist potential. The workflow consists of the following steps 1. semantically enriching your data, 2. Publishing your data 3. Linking and querying your data 4. Visualising and analysing your data. Today we will focus on transforamtion as this is the corner stone for our workflow. But first lets look at a busniess scenario where the linda tools bring added value.
- The following questions may arise: How is OTC liberalisation related with healthcare expenditures and self-medicatiion? Is the economical and political stability of a country somehow related to the OTC liberalisation and/or sales? What are the trends in drug consumptions among different population groups? Which countries will benefit most from OTC liberalisation
- The focus of this presentation is on the transformation of structured and sem-strucured data into Linked Data. The transformation lays the ground work for the followin steps in the presented workflow (visualisation, analytics, query etc.) As in any project we conducted a SotA analysis that yielded the following results. Emphasis lies on the existence of a simple intuitive UI targeted at non-Linked Data experts. Reconcilation: is resolving a literal (e.g. Greece) to a unique linked data resource, such as http://dbpedia.org/resource/Greece
- The UI is designed to give the user a view over his/her data along each step of the transformation together with useful and simple guidance. In the case of csv or maybe excel files: first we upload the data then we select the columns containing the data we want to transform then we start descibing the data by using drag/drop mechanisms to aid in constructing a unique subject URI to identify the triples.
- As a next step we consult our Oracle Service to identify the most relevant and best matching classes in an ontology. With this ontology finding technique we aid the user in one simple step to automatically and effortlessly descibe his/her data using public ontologies.
- In order to enhance the RDF even more we first try to automatically reconcile each column to DB pedia resource (more linked data resouce sites will be added soon (e.g. wikidata, geoNames,etc)) while giving the user the option to select the best match out of a ranked list. With this approach we aid the user in getting closer to 5* linked data For the columns that are left unreconciled auto type guessing is performed.
- The final step in describing the data is the semantic enrichment. Here we again aid the user in finding adequate ontologies to describe the dataset, i.e what content is in each row. In this case the dataset is a listing of a companies employees.
- Add FB, TW links