Publishing the Norwegian Petroleum Directorate s FactPages as Semantic Web Data
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1 Publishing the Norwegian Petroleum Directorate s FactPages as Semantic Web Data Martin G. Skjæveland, Espen H. Lian, Ian Horrocks Presented by Evgeny Kharlamov (Oxford University) ISWC, October 24, 2013
2 Synopsis Our work presents a case study of how to convert tabular data to semantic web data using a semi-automated process, to give high quality semantic data: RDF data, ontology, and database to ontology mappings. We evaluate the result, i.e., what are the benefits of having semantic web data and tools, specifically through a query evaluation Lessons learnt towards a best practice 2 / 13
3 Norwegian Petroleum Directorate (NPD) What is it? A governmental specialist directorate and administrative body. Reports to the Ministry of Petroleum and Energy. Main objective is to contribute to creating the greatest possible values for society from the oil and gas activities by means of prudent resource management based on safety, emergency preparedness and safeguarding of the external environment. The NPD looks after the national interests in the energy sector. The NPD has a national responsibility for data from the Norwegian continental shelf (NCS). NCS 3 / 13
4 What is it? The FactPages contain data about petroleum activities on the NCS. Data is collected from companies that operate on the NCS. Important functions for dataset: forms the basis for the authorities planning of future activity and their judgement of existing activity, makes companies share information, provides information to the general public. A national reference data library for information about the NCS. 4 / 13
5 Web site demonstration 5 / 13
6 Web site demonstration 11 main categories 5 / 13
7 Web site demonstration Selecting Field main categories 5 / 13
8 Web site demonstration Selecting Field main categories... lists available views and subviews. Selecting Page view All... 5 / 13
9 Web site demonstration Selecting Field main categories... lists available views and subviews. Selecting Page view All lists recorded members for the view. Selecting TROLL... 5 / 13
10 Web site demonstration Selecting Field main categories... lists available views and subviews. Selecting Page view All lists recorded members for the view. Selecting TROLL displays a (page view) report, i.e., all data,about the field Troll 5 / 13
11 Web site demonstration Selecting Field main categories Download, XML, Excel... lists available views and subviews. Selecting Page view All lists recorded members for the view. Selecting TROLL displays a (page view) report, i.e., all data,about the field Troll 5 / 13
12 Web site demonstration Selecting Field main categories... lists available views and subviews. Selecting Page view All... Shortcomings to the NPD FactPages:... lists recorded members for the view. Selecting TROLL displays a (page view) report, i.e., all data,about the field Troll Download, XML, Excel No query interface Arbitrary queries not possible, only predefined categories and views No proper URIs Difficult information retrieval Integration impossible 5 / 13
13 Case study Nice features of our case study: Prominent and heavily used dataset by Norway s biggest industry 3-star (linked) open data: Open licence Available as, XML, Excel Non-trivial size (but not big data) Diverse content: Usual: names, descriptions, relationships Geography: WKT, coordinates Measurements: length, pressure; in different UOMs Historical/temporal data: data back to 1970s Different languages: English, Norwegian Different registries: FactPages, PetReg, Diskos Covers many aspects of NCS operations Upper domain ontology candidate 6 / 13
14 Conversion process SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
15 Conversion process 1. Create relational database representation SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
16 Conversion process 1. Create relational database representation a) Download files from NPD FactPages website SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
17 Conversion process 1. Create relational database representation b) Generate database schema based on files and transformation spec. (Transformation spec. will be explained later) SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
18 Conversion process 1. Create relational database representation c) Create and d) load the database SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
19 Conversion process 2. Create RDF/LOD representation SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
20 Conversion process 2. Create RDF/LOD representation a) Generate D2RQ map based on transformation spec. and data SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
21 Conversion process 2. Create RDF/LOD representation b) Dump database to RDF using map SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
22 Conversion process 2. Create RDF/LOD representation c) and load into triple store SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
23 Conversion process 3. Create ontology representation SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
24 Conversion process 3. Create ontology representation a) Generate ontology based on transformation spec. and data and extend manually SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
25 Conversion process 3. Create ontology representation b) Load RDF + into triple store SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
26 Conversion process We test the different representations in our query evaluation experiment SQL SPARQL 1a. download 1d. load Rel. DB 2b. dump 2c. load RDF Transformation specification 1c. create 3b. load 1b. gen. DB schema D2RQ map 2a. generate 3a. generate 7 / 13
27 Conversion process Transformation specification Specifies key constructs of all representation formats Concepts, i.e., tables, classes Identifiers, i.e., primary keys, URIs Relationships, i.e., foreign keys, object properties Attributes, i.e., columns, datatype properties Restrictions, i.e., NOT NULLs, domain/range Datatypes Metadata, e.g., labels, definitions One specification for whole process gives coherent representations, and rapid prototyping For details of representation transformations, see paper. 8 / 13
28 Conversion process Results Conversion process RDF Files/Tables/Classes Columns/Properties SQL D2RQ Map RDF triples 4.5 hours to dump 9 / 13
29 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. 10 / 13
30 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side 10 / 13
31 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side Predefined queries only 10 / 13
32 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side Predefined queries only Map results only 10 / 13
33 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side Predefined queries only Map results only Generic map app 10 / 13
34 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side Predefined queries only Map results only Generic map app Client side, SPARQL based, open source 10 / 13
35 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side Predefined queries only Map results only Generic map app Client side, SPARQL based, open source Predefined generic ontology driven queries and any SPARQL query 10 / 13
36 Benefits of semantic web data by example NPD FactMap vs. our SPARQL map visualiser. Official map app. Server side Predefined queries only Map results only Generic map app Client side, SPARQL based, open source Predefined generic ontology driven queries and any SPARQL query Results link to LOD 10 / 13
37 Query evaluation Introduction Translated domain expert questions to SQL and SPARQL queries Simple cost-benefit analysis of different representations We tested querying relational database LOD representation ontology representation under different reasoning configurations (no reasoning, RDFS, QL, EL, QL) Recorded results returned and time spent to return 11 / 13
38 Query evaluation Results No question was easily answered directly using the NPD FactPages alone All questions were translatable to SPARQL queries, but not all to simple SQL queries, due to missing vocabulary. Only queries involving manually built ontology vocabulary gave more answers with reasoning Most queries returned the same answers, but in some cases different profiles gave more answers. Only when more answers were returned for different reasoning configurations did it cost in terms of slower query answering 12 / 13
39 Project website For more information: Available for download: SQL D2RQ map RDF dumps ontologies SPARQL endpoint LOD front-end Queries 13 / 13
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