WP 5 Data management & analysis

1. WP 5 Data management & analysis • Michel Bohms and Philomena M. Bluyssen – TNO • Isabella Annesi-Maesano - UMPC Paris 06 • Aileen Yang and Alena Bartonova – NILU Objectives • 1. To build a common database on IAQ and other environmental parameters and related health effects • 2. To facilitate the coordination of the different groups that will use the experimental data obtained on both school environmental characteristics and health

2. WP 5 Data management & analysis • Task 1 Specification Database structures and functionalities (months: 3-6) • Task 2 Implementation Database structures, content creation and functionalities (months: 7-14) (old task 2 and 3) • Task 3 Analysis (old task 4 Source analysis and 5 Epidemiological Analysis?) (months: 14-20) • Task 6. Recommendation-design tool (with WP7) (months: 18-22) transfer to WP7???

3. -building and HVAC characteristics of the investigated schools (including inventory of possible sources, design criteria, maintenance and occupancy); - outdoor situation and outdoor air conditions; - indoor air conditions (including content) and ventilation situations; - health and comfort of pupils and teachers; - potential confounders of the relationships between school environment and health. Type of data in database

4. -Analysis of the data resulting in possible links between exposure concentrations of air pollutants and sources and activities (old task 4)-Analysis of the data resulting in possible links between health in children and teachers and sources and activities (old task 5) Type of analysis

5. Task 1 Specification Database structures and functionalities (months: 3-6) • Data/parameters for structure (input): WP2, 3, 4 • Data/parameters for analysis (output): WP5 and WP6 • Functionalities for analysis: WP2, WP5, WP6 • Functionalities for other purposes: WP2, 8? • What do we put in and what do we want to get out? • How do we prefer to put it in and get it out?

6. WP 5 Who will do what? Person-months? Co-leaders: TNO, UMPC Paris 06 and NILU? Task 1: to provide data and functionalities for structure from WP leaders or directly from partners? Task 2 Implementation database structures and functionalities – TNO? Task 3 Analysis – TNO, NILU, and ????

7. Relation with other WP’s? Will there be different databases? • WP2 will be enhanced by an information web-based system providing Internet access as well as a search function to: • Data as available both from the reviewed studies, publications & reports as well as current study later on as they become available. • WP 3.2 Task 5: Database on IAQ in European schools • The collected data in the main and the case studies will be reported in a database, which will be easily accessible for the project partners, in order to facilitate the application of the data in the next WPs. • WP 3.3 European wide dataset for input in WP5 (cross-analyses) • WP8 web-site on IAQ

8. Perhaps two databases?A database for the public and a database for SINPHONIE to make analysis.

9. Possible approaches data management • Semantic web approach and open source implementation • Standard way of saving and retrieving data on Internet via a Web server, open to every one. • User control is possible. • Closed database: assessed via login etc. (i.e. oracle, SQL server) • Or something even more innovative: Google..

10. Next steps • Partners: Who is involved? • Task distribution: • Who will supply which data? • Who will do which analysis? • Database: • Which type of data and functionalities? • What type of database(s)? WP5 Meeting – Medio January – in Delft?

11. Semantic web approach and open source implementation • W3C Semantic Web technologies • Web Ontology Language (OWL) • On top of RDF/RDFS • SPARQL Quering • OSS Joseki Semantic Web (RDF) Server • With Triple DataBase (TDB) back-end

12. Benefits of proposed approach • 100% ‘Open Standards’-based • For Data Storage & Access • Independent of any particular platform, software vendor or user group • 100% Open Source Software (OSS) implementation (of those open standards) • 100% free of charge • Semantic (model-driven) • Flexible • Generic • International • Web-based (distributed, universal access, …) • Already successfully applied in other EU initiatives like IntUBE

13. An ExampleInformal • Sinphonie Ontology, small part as example: • Sites (150x, 5 per country) • Environment • Outdoor Air Quality Measurements (18x) • CO2 in ppm • RelativeHumidity in % • School • ClassRooms (3x) • RoomType • Indoor Air Quality Measurments (18x) • CO2 in ppm • RelativeHumidity in % • (Health/Well-being measurements)

14. An ExampleFormalisation XLS OWL Sinphonie BIM/SIM/PIM Workbook Sinphonie BIM/SIM/PIM Ontology Semantic Content * (Excel-2-OWL Converter) OWL Configurator * Joseki RDF Server/TDB

15. Example: Excel workbook /1

16. Example: Excel workbook /2

17. Example: Excel workbook /3

18. Example: Excel workbook /4

19. Example: Excel workbook /5

20. Example:Excel-2-owl mapping

21. Example: ManualInstantiationwithPMOConfiguratorsaved as:Instance_School_1.owlat:www.bimtoolset.org/ontologies

22. Example: Put in on the Joseki RDF Server (in TDB data store) • SPARQL Update query: • LOAD <http://www.bimtoolset.org/ontologies/Instance_School_1.owl>

23. Example: Query the data /1 #################################################### # Get all triples #################################################### SELECT * { GRAPH<http://www.bimtoolset.org/ontologies/IntUBE-EnergyBIM-Data> { ?x ?y ?z } }

24. Example: Query the data /2

25. Example:Query the data /3 • ########################################################## • ## Get all triples of the bim_data • ########################################################## • PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> • PREFIX sin: <http://www.bimtoolset.org/ontologies/Sinphonie.owl#> • SELECT * • { GRAPH <http://www.bimtoolset.org/ontologies/IntUBE-EnergyBIM-Data> • {?x a sin:School} • }

26. Example: Sensor dataQuery the data /4 SPARQLer Query Results

27. Example:Query the data /5 • ################################################ • # Get the amount of rooms • ################################################ • PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> • PREFIX sin: <http://www.bimtoolset.org/ontologies/Sinphonie.owl#> • SELECT count (?y) • WHERE • { • GRAPH <http://www.bimtoolset.org/ontologies/IntUBE-EnergyBIM-Data> • {?y a sin:Room} • }

28. Example:Query the data /6 SPARQLer Query Results The four non-optional rooms for the one school instantiated (without site context).

29. Final example ################################################ # Get all relative humidities per room, per school, per site ################################################ PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX sin: <http://www.bimtoolset.org/ontologies/Sinphonie.owl#> SELECT ?x ?y ?z ?z2 WHERE { GRAPH <http://www.bimtoolset.org/ontologies/IntUBE-EnergyBIM-Data> { OPTIONAL {?x a sin:Site}. OPTIONAL {?y a sin:School}. OPTIONAL {?z a sin:Room}. OPTIONAL {?x sin:School ?y}. OPTIONAL {?y sin:Room ?z}. {?z sin:RelativeHumidity-Measurement ?z1}. {?z1 sin:RelativeHumidity-value ?z2}. }}

30. Final exampleQuery Result, now in JSON syntax output { "head": { "vars": [ "x" , "y" , "z" , "z2" ] } , "results": { "bindings": [ { "y": { "type": "uri" , "value": "http://www.bimtoolset.org/ontologies/Instance_School_1.owl#Instance_School_1" } , "z": { "type": "uri" , "value": "http://www.bimtoolset.org/ontologies/Instance_School_1.owl#Instance_Room_4" } , "z2": { "datatype": "xsd:float" , "type": "typed-literal" , "value": "90." } } ] }}

31. Example:More • Much more beyond Sparql Select: • Construct/Describe • No “XML Result” results but RDF/XML code • Sparql Update (beyond “load”) • Insert new triples • Jena ARQ beyond standard Sparql • LET () • Various functionalities / “magic properties” • Like Membership of SET • Very powerfull ! Especially in combination with SPIN • > OO Ontologies