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招待講演1: [SIG-SWO-A1402-02] 地理空間情報分野における オープンデータ化とその動向 34回セマンティックウェブとオントロジー研究会 「オープンデータとセマンティックWeb技術」 慶応義塾大学日吉キャンパス来往舎|201411201 瀬戸 寿一 (@tosseto) 東京大学空間情報科学研究センター・特任助教 OpenStreetMapファウンデーションジャパン・OSGeo財団Charter Member

20141120 sig swo-seto

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第34回セマンティックウェブとオントロジー研究会 「オープンデータとセマンティックWeb技術」 慶応義塾大学日吉キャンパス来往舎|2014年11月20日 地理空間情報におけるオープンデータ化とその動向

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  • 1. 34Web201411201: [SIG-SWO-A1402-02]1 (@tosseto)OpenStreetMapOSGeoCharter Member

2. 2 3. Open Government 3200912Open Government Directive cf. G8(, 2011; , 2014)3 4. OpenData) OKFN, 2005=2014 Source: http://okfn.jp/2014/03/23/defining-open-data/ 4 5. G8H25.6.18 Source:https://www.gov.uk/government/publications/open-data-charter/g8-open-data-charter-and-technical-annexhttp://www.mofa.go.jp/mofaj/gaiko/page4_000099.html 5 6. 2011 GeoplatformCKANDrupalSources: https://geoplatform.gov/ 6 7. DATA.GOV.UK + Ordnance Survey (OS)Source: https://data.gov.uk/ 7 8. AzaveaGitHub8 9. G8ODOpen Data Census4404254105155105908559405%10%0% 20% 40% 60% 80%DB0 100 200 300 400 500 600 700 800 900 10001210(15)16)(27)30(3870%70%70%45%35%40%35%60% DB10 9Source: https://index.okfn.org/countryOPEN DATA INDEX 9 10. Source: https://index.okfn.org/country 10 11. 11 12. 1 Linked Open Data 5 StarTim Berners-LeePDFExcelWordCSVURILinked Open Data Level 0Level 1Level 2Level 3Level 4PDFWebWebXLS, DOC CSV9RDFXMLAPICSVLevel 1RDFSPARQLLevel 0Level 0URLWebWebWebWebWebSource: http://www.opendata.gr.jp/news/1407/140731_000866.php 13. 44()137/4714.9%7/2035.0%5/43(11.6%) 24/1,742(1.3%) 14. 14: 44CC-BY20148311,963]F[077d[0-,7-,7[0BN]F[077d[0-,7-,7[0BNJg b) z} x z} | x yxxwxu=9T x z z y | xwxu YQT@2) yy } y~ y y ~wuXT {| {} ~ { y |w{u XTG_) yx y y y ||w|u$mT { z } y y ~xwxu OT) x y~ y~ y y xwxuo%T ~ y x ~ y w~u `TH#) {x yz |z y z yw|u1UT yz y y{ y y zw{u W(T) } x } y x yxxwxutT y y | ywyu W(TaE) ~ ~ yz y y }xwxu/T zxy |y ~zx } ~ {zw|u W(Tk ) x z~ z~ y z xwxu8LTZr() z { } y y |xwxuOT) y x y y x yxxwxu 8LT:) y y y }zwu`T`) z yxz yx| y y ywu V(T MR | x | y x yxxwxuW(T@I) | | z { }xwxu V(Ti)) z | ~ y { {{w{uW(T(') y| y z }xwxu XTX) y z| y z xwuW(TS?) y} ~ zy y { yw|u XTC*!R yx x yx y x yxxwxu1UT) x | | x y xwxu XTf) y y {| y y }xwxun+n) |z }x z { y~wxu XT) yy x yy z x yxxwxuXTsD) y z ~ { ~~wuV(TjE) x y~ y~ z y xwxu XT6e) ~ x ~ y x yxxwxu;h 15. P) x z}{ z}{ { } xwxu liTp) x y| y| x y xwxu^T^) x }| }| x z xwxu $mT) yz x yz z x yxxwxuqTA) y~ z y y y wu o%Tci) y| ~ zx y z xwxuKeTG) y{ x y{ y x yxxwxu o%T.') z z | z y }xwxuW(T@I)jE y y { y y |w~u o%T4() x z z x z xwxuo%T) } y{ y y ~yw}ud ~| yvz yv~{T53h)h) 16. PDFXLSCSVAPISHPjson/kml 652410383332316.5% 0036001371.9% 00341301482.4% 092231919027013.8% 68714833 62531.8% 21129150 1658.4% 38263420 34317.5% 3418721 1527.7% 1365181,1615657351,963100%Linked Open Data 5 Star 15 17. 16 644144722.8% 6925232116.4% 1794522411.4% 10111521611.0% 128171457.4% 72701427.2% 141011155.9% 39641035.2% 2558834.2% 2161824.2% 1551663.4% 59140.7% 550.3% 6741,2891,963100.0% 18. 17 19. 18 20. 20119(AIGID)20134201319 Source: http://aigid.jp/?page_id=310 21. Source: http://pingineer.net/apps/hazard_map/ 20 22. Night Street Advisor Source: http://siz-nightstreetadvisor.herokuapp.com/ 21 23. (1SHP22Source: 2014 24. 23 25. UDC2014 11. CC-BY2. Web (10) 24 26. UDC201412/7in11/29WS11/24LOD12/7 25 27. http://i.csis.u-tokyo.ac.jp/news/opendata/index.html26 28. http://udct-data.aigid.jp/27 29. 20147261528 30. 2014920 UDC2014 in 2529 31. 3020141117UDC2014xLOD2014 in GEXPO40 32. Knowledge Connectorhttp://idea.linkdata.org/ideas?tag=UDC201431 33. 32 34. 4 UDC2014WebOK 33 35. 34 36. Open Cities: ()RAWAPISource: http://opencitiesproject.com/ 35 37. Open DRI (Open Data for Resilience Initiative) Field GuideSource: Crowley(2014) 36 38. OpenCitiesSource: http://opencitiesproject.com/casestudy/building-use/ 37 39. 38 Source: http://dev.citysdk.waag.org/buildings 40. UCL-CASA39Source: http://citydashboard.org/london/ 41. 40Maynooth UniversitySource: http://www.dublindashboard.ie/ 42. 41SocrataSource: https://dashboard.edmonton.ca/ 43. BigOpen Data42Additional outputin 2020AdditionalGDP by 2020Source: WISE Institute with BOUDICATotalbn cappeirt a NorthNMSSouthEU-28Additional increase in GDP levelby country and sectors%EU-28Finance insuranceHealthPublicadministrationTradeInformation communicationManufacturing2020 Additional annualAdditional GDP%by sectorin which data-driven solutionsare introducedData-drivendecision making(BigOpen Data)Information communicationTrade FinanceinsuranceManufacturingOtherPublic administration Health social careBig and open data in EuropeA growth engine or a missed oportunity?2,52,01,51,00,5LuxembourgIrelandSwedenUKBelgiumAustriaDenmarkCzech Rep.GermanyFinlandNetherlandsPolandLithuaniaPortugalFranceSloveniaCroatiaMaltaHungarySlovakiaSpainLatviaItalyBulgariaGreeceCyprusEstoniaRomaniaEU-28NorthNMSSouth2502001501005002013201420152016201720182019GDP in bn in the EU-28increasedcompetition(Open Data)Business processeseffi ciency(Big Data)Source: http://www.bigopendata.eu/full-report/ 44. OpenBig Data( Smart City Real-time cityKitchin, 2013 43 45. (Source: http://www.thehubway.com/ 44 46. CSVshprawSource: http://hubwaydatachallenge.org/ 45 47. Source: http://zsobhani.github.com/hubway-team-viz/ 46 48. 18700NY(2013)47Source:https://www.mapbox.com/blog/nyc-taxi/ 49. NYC Taxis: A Day in the LifeSource: http://nyctaxi.herokuapp.com/# 48 50. 49 51. (Code for Japan, UDC2014)50(GeoJSONRDF? 52. () (cf. )(cf. WebGIS) 51 53. (2014) API 52 54. Thank you Questions [email protected]://researchmap.jp/tosseto53