Content-Infused OGC Web Services    Enabling Dynamic Quality Assessment in Observing Systems             Janet	  J.	  	   ...
Data	  Provider	                       NOAA/NDBC	                                                      provides	  24/7	  Q...
Data	  Provider	                                                                                                          ...
Data	  Provider	                        NOAA/NDBC	         	  (and	  Consumer)	                      provides	  24/7	  QC;...
GOAL:	  two	  paths	  	               Described	  well	  enough	  for	  assessment	  of	                                  ...
Data	  Provider	  needs	  to	  communicate	  how	  the	  sensible	           proper=es	  were	  turned	  into	  observa=on...
Project	  	  to	  Address	  Data	  Quality	  in	  Sensor	  Web	  Enablement	  Frameworks	                                 ...
Community-­‐based	  Development	                                                           Domain	                        ...
Data	                                                                                              CL	  	  SensorML	  	   ...
Data	                                                                                     CL	  	  SensorML	  	       HARVE...
Data	                                                                                            CL	  	  SensorML	  	     ...
Building	  ontologies	                               12	  
Five	  Role-­‐based	  Categories	  of	  SensorML	                                                                      Obs...
Five	  Role-­‐based	  Categories	  of	  SensorML	                                                                        O...
Five	  Role-­‐based	  Categories	  of	  SensorML	            ConfiguraKon	  and	                                Observable	...
Five	  Role-­‐based	  Categories	  of	  SensorML	                                                                 Observab...
Five	  Role-­‐based	  Categories	  of	  SensorML	                                                                  Observa...
Five	  Role-­‐based	  Categories	  of	  SensorML	                                                                        O...
How	  does	  this	  model	  enable	  dynamic	  quality	  assessment?	  1)      ROLES	  -­‐	  Provides	  a	  template	  for...
Next	  Steps	  •  Build	  beker	  SensorML	  editors	  	  and	  registries	  -­‐-­‐	  making	     things	  easier	  and	  ...
Conclusions	  •  Structured	  Q2O	  (hkp://q2o.whoi.edu)	  SensorML	  serves	  as	  a	       model	  for	  any	  sensor-­‐...
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Content-Infused OGC Web Services Enabling Dynamic Quality Assessment in Observing Systems

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Presentation by Janet Fredericks during the Sensor Web Ontology and Semantics paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).

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Content-Infused OGC Web Services Enabling Dynamic Quality Assessment in Observing Systems

  1. 1. Content-Infused OGC Web Services Enabling Dynamic Quality Assessment in Observing Systems Janet  J.     redericks   F Applied  Ocean  Physics  &  Engineering   Woods  Hole  Oceanographic  Ins=tu=on     Carlos  Rueda   Monterey  Bay  Aquarium  Research  Ins=tute     Workshop  on  Sensor  Web  Enablement  2011  (SWE  2011)   As  part  of  The  2011  Cybera  Summit  on     Data  For  All  -­‐  Opening  up  the  Cloud   October  6-­‐7,  2011,  Banff,  AB,  Canada   1  
  2. 2. Data  Provider   NOAA/NDBC   provides  24/7  QC;   Nightmare!   Feeds  National  IOOS  backbone;   NOAA/NODC   provides  national  archival  for  valued   data  sets  (they  can  determine  the  value)   NSF/OOI;  NSF/R2R;  NSF/BCODMO  Sensor  Manufacturers   provides  community-­‐based  integration  <html/>  and  manuals   with  tools  and  QC,  along  with  discovery   and  mapping  opportunities   Real-­‐time  Rapid  Response   integration  can  be  accomplished  quickly   and  reliably  by  communicating  metadata   Research  and  survey   in  standards-­‐based  systems   data  served  with   associated  metadata   in  a  few  speci5ic   Modeling   formats  with   using  translation  tools  from  the  cloud,   associated  software   modelers  have  access  to  a  broader   installations   source  of  information   ANYONE   By  fully  describing  data,  sensors  and   processing  with  associated  provenance,   data  can  be  discovered  and  explored  for   any  program  User-­‐based    Output   2  
  3. 3. Data  Provider   IOOS    (and  Consumer)   Nightmare!   GEOSS  Sensor  Manufacturers   NOAA/NDBC  <html/>  and  manuals   provides  24/7  QC;   Feeds  National  IOOS  backbone;   Research  and  survey   data  served  with   associated  metadata   in  a  few  speci5ic   formats  with   Research  and  survey   Research  and  survey   associated  software   data  served  with   data  served  with   installations   associated  metadata   associated  metadata   in  a  few  speci5ic   in  a  few  speci5ic   formats  with   formats  with   associated  software   associated  software   installations   installations  User-­‐based    Output   3  
  4. 4. Data  Provider   NOAA/NDBC    (and  Consumer)   provides  24/7  QC;   Feeds  National  IOOS  backbone;   Nightmare!   NOAA/NODC   provides  national  archival  for  valued   data  sets  (they  can  determine  the  value)   NSF/OOI;  NSF/R2R;  NSF/BCODMO  Sensor  Manufacturers   provides  community-­‐based  integration  <html/>  and  manuals   with  tools  and  QC,  along  with  discovery   and  mapping  opportunities   Real-­‐time  Rapid  Response   integration  can  be  accomplished  quickly   and  reliably  by  communicating  metadata   Research  and  survey   in  standards-­‐based  systems   data  served  with   associated  metadata   in  a  few  speci5ic   Modeling   formats  with   using  translation  tools  from  the  cloud,   associated  software   modelers  have  access  to  a  broader   installations   source  of  information   ANYONE   By  fully  describing  data,  sensors  and   processing  with  associated  provenance,   data  can  be  discovered  and  explored  for   any  program  User-­‐based    Output   4  
  5. 5. GOAL:  two  paths     Described  well  enough  for  assessment  of   NOAA/NDBC   data  for  specified  use  and  for  a   provides  24/7  QC;   repurposed  applica<on   Feeds  National  IOOS  backbone;   NOAA/NODC   provides  national  archival  for  valued   Sensor  Manufacturers   data  sets  (they  can  determine  the  value)   and  domain  experts   develop  sensor  and   NSF/OOI;  NSF/R2R;  NSF/BCODMO   processing   provides  community-­‐based  integration   descriptions  in   with  tools  and  QC,  along  with  discovery   standards-­‐based   Converters;   and  mapping  opportunities   encodings   QC  algorithms;   vocabularies  &   Real-­‐time  Rapid  Response   ontologies;   integration  can  be  accomplished  quickly   analysis  and   and  reliably  by  communicating  metadata   visualization  tools   in  standards-­‐based  systems   Research  and  survey   data  served  with   associated  metadata   Modeling   in  a  community-­‐ using  translation  tools  from  the  cloud,   adopted,  standards-­‐ modelers  have  access  to  a  broader   based  framework   source  of  information   ANYONE                                                                  Standards-­‐based     By  fully  describing  data,  sensors  and   processing  with  associated  provenance,  (machine-­‐to-­‐machine  harves=ng)   data  can  be  discovered  and  explored  for   any  program   User-­‐based    Frameworks   5  
  6. 6. Data  Provider  needs  to  communicate  how  the  sensible   proper=es  were  turned  into  observa=ons!   Logging/ Web   Sensor     Processing   Service   6  
  7. 7. Project    to  Address  Data  Quality  in  Sensor  Web  Enablement  Frameworks   BACKGROUND   Quality  Assurance   Guides/Implementa=on   (QARTOD)   Seman=c  Tools  (MMI)   Standards  (OGC)   (OOStethys/OGC-­‐OIE/OpenIOOS)   Vocabulary  Registry  &  Term   Syntactac=c  Interoperabilty   So_ware  Packages/   QC  Tests   Mapping   (SensorML/O&M)   cookbooks   Ontology  Development  &   Standards-­‐based  web  MetaData  Requirements   Registry   services  (SOS)   Observa=ons  Based  SOS   Quality  –  to  –  OGC  (Q2O)    -­‐  IntegraKon  of    sensor  &  processing   descripKons  aimed  towards  the  ability  to  assess  quality  of  observaKons   7  
  8. 8. Community-­‐based  Development   Domain   Experts   Sensor   Mfgrs   Content   Specifica=ons/   SWE   Implementa=on   Model   Operators  What  informaKon  is  needed  to  assess  quality  of  data    and  how  do  we  implement  it  into  an  Sensor  ObservaKon  Services    (SOS)?   IT   Specialists   8  
  9. 9. Data   CL    SensorML     HARVESTS   I   DescribeSensor  (SensorML)   E SOS   N GetObserva@on  (O&M)   T   REFERENCES   RESOLVES   OWL/RDF   Vocabularies/ ontologies   9  
  10. 10. Data   CL    SensorML     HARVESTS   I   DescribeSystem  (SensorML)   E SOS   N GetObserva@on  (O&M)   T  <sml:output  name="swell">  <swe:Quan=ty  defini=on="hkp://mmisw.org/ont/mvco/proper=es/swell">   REFERENCES  <swe:uom  code="cm"/>   RESOLVES  </swe:Quan=ty>  </sml:output>   OWL/RDF   Vocabularies/ ontologies   10  
  11. 11. Data   CL    SensorML     HARVESTS   I   DescribeSystem  (SensorML)   E SOS   N GetObserva@on  (O&M)   T   REFERENCES   RESOLVES   OWL/RDF   Vocabularies/ ontologies   11  
  12. 12. Building  ontologies   12  
  13. 13. Five  Role-­‐based  Categories  of  SensorML   Observable  Proper=es    SML  system   Sensor/Deployment  Files  (SensorML  -­‐>  DescribeSensor)   Configura=on/Ownership/Deployment  (CONDEP)File   Original  Equipment  Manufacturer  (OEM)  File     Descrip=on  of  Sensor  Configura=on,    Deployment  and   Descrip=on  of  Sensor  Model   Event  History    Details   Process  Files  (SensorML  -­‐>  DescribeSensor)  QC  Tests  -­‐  are  classified  as  QC  tests  (QcCategory)  and   Processing  Descrip=ons  -­‐  to  describe  how  an   may  have  associated  QC  flags  as  output   observa=on  is  derived  from  sensor  output   Observed  and  Derived  Proper=es  and  QC  Flags      (O&M  -­‐>  GetObserva=on)   13  
  14. 14. Five  Role-­‐based  Categories  of  SensorML   Observable  Proper=es    SML  system   OEM  Model   DescripKon   Sensor/Deployment  Files  (SensorML  -­‐>  DescribeSensor)   Created  by   Original  Equipment  Manufacturer  (OEM)  File     manufacturer  and   Configura=on/Ownership/Deployment  (CONDEP)File   Descrip=on  of  Sensor  Configura=on,    Deployment  and   Event  History    Details   anyone   available  for   Descrip=on  of  Sensor  Model   using  the  par<cular   model  –  accuracy;   error  analysis  etc   specific  to  the  model   Process  Files  (SensorML  -­‐>  DescribeSensor)   QC  Tests  -­‐  are  classified  as  QC  tests  (QcCategory)  and   Processing  Descrip=ons  -­‐  to  describe  how  an   may  have  associated  QC  flags  as  output   observa=on  is  derived  from  sensor  output   Observed  and  Derived  Proper=es  and  QC  Flags      (O&M  -­‐>  GetObserva=on)   14  
  15. 15. Five  Role-­‐based  Categories  of  SensorML   ConfiguraKon  and   Observable  Proper=es   Deployment  File   Working  with  OEM    SML  system   file/Sensor   Manufacturers  and   Marine  Operator   Sensor/Deployment  Files  (SensorML  -­‐>  DescribeSensor)   describe  this  instance:   Original  Equipment  Manufacturer  (OEM)  File     Configura=on/Ownership/Deployment  (CONDEP)File   Descrip=on  of  Sensor  Configura=on,    Deployment  and   contacts  (operator),  Model   Descrip=on  of  Sensor   Event  History    Details   parameters    (set-­‐up   specifica=on  that  can   affect  accuracy  or   relevance  to   repurposed   Process  Files  (SensorML  -­‐>  DescribeSensor)   applica=on),  posi=ons,   QC  Tests  -­‐  are  classified  as  QC  tests  (QcCategory)  and   Processing  Descrip=ons  -­‐  to  describe  how  an   may  have  arela=ng  to  ags  as  output   events   ssociated  QC  fl observa=on  is  derived  from  sensor  output   sensor  health   Observed  and  Derived  Proper=es  and  QC  Flags      (O&M  -­‐>  GetObserva=on)   15  
  16. 16. Five  Role-­‐based  Categories  of  SensorML   Observable  Proper=es    SML  system   Sensor/Deployment  Files  (SensorML  -­‐>  DescribeSensor)   Configura=on/Ownership/Deployment  (CONDEP)File   Original  Equipment  Manufacturer  (OEM)  File     Descrip=on  of  Sensor  Configura=on,    Deployment  and   Descrip=on  of  Sensor  Model   Event  History    Details   QC  Tests   Data  manager   Process  Files  (SensorML  -­‐>  DescribeSensor)  describes  QC  tests  and   associated  flags;  inputs   QC  Tests  -­‐  are  classified  as  QC  tests  (QcCategory)  and   Processing  Descrip=ons  -­‐  to  describe  how  an   may  have  associated  QC  flags  as  output   to  tests  and   observa=on  is  derived  from  sensor  output   parameters  are   specified  –  the   parameters  can  be   =me-­‐stamped   Observed  and  Derived  Proper=es  and  QC  Flags      (O&M  -­‐>  GetObserva=on)   16  
  17. 17. Five  Role-­‐based  Categories  of  SensorML   Observable  Proper=es    SML  system   Sensor/Deployment  Files  (SensorML  -­‐>  DescribeSensor)   Configura=on/Ownership/Deployment  (CONDEP)File   Original  Equipment  Manufacturer  (OEM)  File     Descrip=on  of  Sensor  Configura=on,    Deployment  and   Descrip=on  of  Sensor  Model   Event  History    Details   Processing   DescripKons   Process  Files  (SensorML  -­‐>  DescribeSensor)   Data  managers  and   domain    are  classified  as  QC  tests  (QcCategory)  and   QC  Tests  -­‐ experts  provide   Processing  Descrip=ons  -­‐  to  describe  how  an   may  have  associated  QC  flags  as  output   observa=on  is  derived  from  sensor  output   authorita<ve  reference   and  descrip<ons  of   processing  used  for   derived  proper=es   Observed  and  Derived  Proper=es  and  QC  Flags      (O&M  -­‐>  GetObserva=on)   17  
  18. 18. Five  Role-­‐based  Categories  of  SensorML   Observable  Proper=es    SML  system   Sensor/Deployment  Files  (SensorML  -­‐>  DescribeSensor)   Configura=on/Ownership/Deployment  (CONDEP)File   Original  Equipment  Manufacturer  (OEM)  File     Descrip=on  of  Sensor  Configura=on,    Deployment  and   Descrip=on  of  Sensor  Model   Event  History    Details   Process  Files  (SensorML  -­‐>  DescribeSensor)   QC  Tests  -­‐  are  classified  as  QC  tests  (QcCategory)  and   Processing  Descrip=ons  -­‐  to  describe  how  an   may  have  associated  QC  flags  as  output   observa=on  is  derived  from  sensor  output   Observed  and  Derived  Proper=es  and  QC  Flags      (O&M  -­‐>  GetObserva=on)   18  
  19. 19. How  does  this  model  enable  dynamic  quality  assessment?  1)  ROLES  -­‐  Provides  a  template  for  instrument  manufacturers/data  managers/ marine  operators  to  describe  details  that  describe  quality  related  informa=on  in   a  standards-­‐based  encoding  2)  CONNECTIONS  -­‐  Through  the  connec=ons  list  in  SensorML,  the  QC  flags  can  be   associated  with  the  QC  tests  with  associated  parameters  3)  ENABLING  SEMANTIC  MAPPINGS  -­‐  Through  inclusion  of  associated  URLs  encoded   with  each  term,  ontologies  and  mappings  can  be  built  to  define  rela=onships   across  poli=cal  and  research  domains  promo=ng  interoperability  and   interdisciplinary  research  for  all  geospa=al,  sensor-­‐based  observa=ons.    4)  Encoding  thorough  descrip=ons  of  processing  and  process  lineage   promotes  beker  understanding  of  the  observa=ons,  which     enhances  the  value  and  reliability  of  the  data.    The  original  provider  has  no  knowledge  of  how  the  data  may  be  used!    We  need  to  communicate  enough  informa=on  to  enable  assessment  for  a  par=cular  use  beyond  the  project  design!    Did  they  sample  fast  enough  for  the  new  applica=on?  Or  long  enough?  Is  the  repor=ng  frequency  adequate?     19  
  20. 20. Next  Steps  •  Build  beker  SensorML  editors    and  registries  -­‐-­‐  making   things  easier  and  promo=ng  fully-­‐described  sensor  and   processing  lineage.    This  will  promote  adop<on  of  the   use  of  standards  and  more  fully-­‐described  systems!      •  Encourage  manufactures,  data  managers  and  domain   experts  to  create  meaningful  vocabularies    including   authorita=ve  references  to  processing  algorithms,     with  figures,  equa=ons,  etc.  and  to  register  the   vocabularies,  providing  resolvable  links  in  a  standards-­‐ based  encoding  (OWL)  •  Provide  tools  and  opportuni=es  for  domain  experts  to   create  and  register  ontologies,  associa=ng  terms  in   RDF  (Is  ThisQCtest  the  same  as  ThatQCtest?  Does  this   QC  flag  have  th  same  meaning  as  thatQCflag)   20  
  21. 21. Conclusions  •  Structured  Q2O  (hkp://q2o.whoi.edu)  SensorML  serves  as  a   model  for  any  sensor-­‐based,  in  situ  observa=ons;    each   component  can  be  implemented  by  the  responsible  party  and   adop=on  of  the  model  can  happen  in  stages.  •  By  associa=ng  QC  flags  with  qc  tests,  processing  methods  with   observa=ons,  and  fully-­‐describing  how  observable  proper=es   become  observa=ons  knowledge  about  quality  will  be  shared.  •  By  referencing  (encoding)  resolvable  terms,  ontologies  can  be   built  and  registered  to  foster  interoperability  across-­‐domains   and  poli=cal  boundaries.     The  ability  to  dynamically    assess  data  quality  will  provide  a   trusted  founda<on  for  observing  systems     21  
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