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Linking American Art to the Cloud
 

Linking American Art to the Cloud

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Overview of the project at the Smithsonian American Art Museum to publish its collections data as 5-star Linked Open Data.

Overview of the project at the Smithsonian American Art Museum to publish its collections data as 5-star Linked Open Data.

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    Linking American Art to the Cloud Linking American Art to the Cloud Presentation Transcript

    • Linking  the  American  Art  Museum  to  the  Cloud  What  is  Linked  Open  Data?    Data  published  by  exis0ng  internet  protocols  that  use  a  URI  (Unique  Resource  Indicator)  as  the  primary  discoverable  en0ty  for  a  resource  (e.g.  person,  object,  web  page,  etc.)    THE  FIVE  STARS  OF  LOD:  ★  make  your  stuff  available  on  the  web  (whatever  format)  under  an  open  license    ★★  make  it  available  as  structured  data  (e.g.,  Excel  instead  of  image  scan  of  a  table)    ★★★  use  non-­‐proprietary  formats  (e.g.,  CSV  instead  of  Excel)    ★★★★  use  URIs  to  iden0fy  things,  so  that  people  can  point  at  your  stuff    ★★★★★  link  your  data  to  other  data  to  provide  context  
    • Linking  the  American  Art  Museum  to  the  Cloud  What  is  good  for?    •  Making  your  data  more  discoverable  and  useful  by  everybody  •  Making  the  web  machine-­‐readable  at  a  more  granular  level  •  Allowing  for  more  sophis0cated  queries  using  inference  •  Connec0ng  your  data  to  other  people’s  data  For  American  Art,  Linked  Open  Data  will:  •  Make  our  collec0ons  data  more  findable  on  the  web  •  Create  connec0ons  with  other  museums  that  have  related  artworks  •  Create  connec0ons  with  other  non-­‐museum  resources,  such  as  the  New  York  Times  •  Create  connec0ons  with  our  dispersed  content  on  social  media  (e.g.  Flickr)  •  Help  us  beSer  adapt  to  the  changing  web    
    • Linking  the  American  Art  Museum  to  the  Cloud  Examples    Europeana    •  Digi0zed  collec0ons  of  museums,  libraries,  archives  and  galleries  across  Europe.  •  Open  metadata  on  20  million  texts,  images,  videos  and  sounds  •  A  subset  of  2.4  millions  objects  from  8  direct  Europeana  providers  encompassing  over  200   cultural  ins0tu0ons  from  15  countries  is  served  according  to  the  Linked  Data  recipes.  •  Virtual  exhibi0ons  showcase  some  of  the  content  available.    
    • Linking  the  American  Art  Museum  to  the  Cloud  Examples    Pelagios    •  Stands  for  Pelagios:  Enable  Linked  Ancient  Geodata  In  Open  Systems’  •  Aim  is  to  help  introduce  Linked  Open  Data  into  online  resources  that  refer  to  places  in  the   Ancient  World.  •  Allows  you  to  find  content  related  to  a  specific  place  
    • Linking  the  American  Art  Museum  to  the  Cloud  GeJng  Started    IniKal  QuesKons  •  Will  it  take  a  lot  of  0me  and  resources  to  prepare  our  data?  •  How  does  LOD  differ  from  what  a  Google  search  can  do?  •  Is  it  foolish  to  be  doing  this  before  standards  are  in  place?  •  What  if  people  create  inappropriate  links  to  our  data?  •  Will  it  be  worth  the  0me  and  effort  in  the  end?  •  How  do  we  handle  all  of  the  non-­‐public  data  that  we  have?  •  Is  it  possible  to  make  sense  of  all  the  acronyms?  The  Project  •  Working  with  the  Informa0on  Sciences  Ins0tute  (ISI)  and  Department  of  Computer  Science  at   the  University  of  Southern  California.  •  Goal:  Publish  5-­‐star  Linked  Open  Data  of  our  complete  collec0ons  data  (41,000  objects,   8,000  ar0sts).  •  Project  Phases:  Prepare  the  data,  Create  an  ontology,  map  the  data  to  RDF,  link  the  data  to   hub  datasets,  publish  the  data.  
    • Linking  the  American  Art  Museum  to  the  Cloud  The  Process    Preparing  the  data  •  Collec0ons  data  is  stored  in  TMS.  We  have  over  100  tables  •  We  decided  to  publish  only  the  data  that  is  already  visible  on  our  website  •  We  used  an  exis0ng  output  report  from  our  database  •  Several  fields  needed  to  be  interpreted  first  before  they  could  be  mapped  to  RDF    Designing  the  Ontology  •  We  built  our  ontology  around  exis0ng  ontologies     •  An  augmented  version  of  Europeana  Data  Model  v.2  for  overall  framework;  SKOS  for   classifica0on  of  artworks,  ar0st  and  place  names;  Dublin  Core  for  tombstone  data;  RDA   Group  2  Elements  for  biographical  informa0on;  schema.org  for  geographical  data.  
    • Linking  the  American  Art  Museum  to  the  Cloud  The  American  Art  Ontology  
    • Linking  the  American  Art  Museum  to  the  Cloud  The  Process    Mapping  the  Data  to  RDF  (Resource  DescripKon  Framework)  •  Used  KARMA  tool  to  model  the  data  •  The  system  learns  with  each  dataset  so  the  process  becomes  easier  and  faster              For  Example:    Subject              Predicate      Object                  www.americanart.si.edu/linkeddata/person/3406      saam:Person      “Thomas  Moran”    www.americanart.si.edu/linkeddata/person/3406    rdaGr2:dateOfBirth    “1837”    www.americanart.si.edu/linkeddata/person/3406    owl:SameAs      hSp://live.dbpedia.org/page/Thomas_Moran    
    • Linking  the  American  Art  Museum  to  the  Cloud  The  Process    Linking  the  Data  to  External  Data  •  Verify  matches  before  publishing  •  Have  already  linked  ar0sts  to:   •  DBPedia  -­‐  2,194   •  New  York  Times  -­‐  70  •  Addi0onally,  can  link  ar0sts  to:   •  GeSy  Union  List  of  Ar0st  Names  -­‐  2,110  (ULAN  is  not  yet  published  as  LOD,  but  will  be)   •  Rijksmuseum  dataset  –  551  (links  are  not  yet  verified)  •  In  the  works:   •  Linking  places  to  GeoNames   •  Linking  concepts  to  AAT   •  Linking  to  datasets  from  other  museums   •  Linking  to  social  media  content  Publishing  •  Plan  to  publish  complete  dataset  and  all  verified  links  under  a  CC0  license   •  Data  will  be  CC0,  but  images  will  be  maintained  under  a  restricted  license   •  Include  example  records  and  SPARQL  endpoint  
    • Linking  the  American  Art  Museum  to  the  Cloud  Some  answers    Answers  to  IniKal  QuesKons:  •  Will  it  take  a  lot  of  0me  and  resources  to  prepare  our  data?   •  Using  KARMA  to  model  the  data  and  a  visual  interface  to  verify  the  links  reduced  the   staff  Eme  that  would  have  been  needed  to  do  this  manually.  Working  with  ISI  certainly     helped  kick-­‐start  the  process.  •  How  does  LOD  differ  from  what  a  Google  search  can  do?   •  LOD  eliminates  the  “noise”  of  a  Google  search.  With  LOD  you  can  query  specific  facts.   With  Google  you  query  documents  and  then  have  to  read  the  document  to  get  the  facts.      •  Is  it  foolish  to  be  doing  this  before  standards  are  in  place?   •  There  are  already  some  standards  in  place.  Plus,  being  one  of  the  first  means  that  we   have  the  opportunity  to  help  shape  the  standards.  •  What  if  people  create  inappropriate  links  to  our  data?   •  You  cannot  control  what  people  say  about  you  on  the  internet!  •  Will  it  be  worth  the  0me  and  effort  in  the  end?   •  We  believe  so!  It  will  allow  us  to  beTer  adapt  to  the  future  of  the  web.  •  How  do  we  handle  all  of  the  non-­‐public  data  that  we  have?   •  We  opted  to  publish  only  our  public  data.  •  Is  it  possible  to  make  sense  of  all  the  acronyms?   •  Yes!  It  takes  Eme,  but  you  do  eventually  grasp  all  the  different  terms.  
    • Linking  the  American  Art  Museum  to  the  Cloud  Some  conclusions    •  We  ini0ally  planned  to  use  only  a  sample  of  collec0ons  data.  In  the  end,  we  used  data  for   our  en0re  collec0on  –  over  41,000  objects!    •  Linking  to  datasets  like  DBPedia  and  the  New  York  Times  will  greatly  expand  the  content  we   offer  on  our  website.  •  Linking  to  datasets  from  other  art  museums  will  increase  the  accessibility  and  reach  of  art   collec0ons  and  cultural  heritage  online.  •  We’re  excited  for  the  poten0al  to  link  to  our  content  on  social  media  sites  –  an  object  page   as  a  “hub”  to  all  types  of  content  about  that  object.  •  We  see  great  poten0al  in  using  Linked  Open  Data  to  curate  stories  about  artworks  and   ar0sts  that  connect  museums  and  datasets  around  the  world  in  new  and  surprising  ways.  
    • Linking  the  American  Art  Museum  to  the  Cloud  What’s  next?    •  Embedding  linked  content  on  object  pages  and  ar0st  pages  on  our  website  (Wikipedia,  the   New  York  Times,  etc.)  •  Improve  representa0on  of  ar0sts  on  Wikipedia,  adding  ar0cles  and  infoboxes  where  possible   to  increase  the  number  of  matches  in  DBPedia.  •  Create  an  ongoing  maintenance  plan  to  ensure  that  the  linked  open  data  reflect  new  and   edited  museum  data.  •  Tag  object-­‐  and  person-­‐related  museum  content  on  social  sites  like  Flickr  and  YouTube  so   that  we  can  create  links  to  that  content  on  our  website,  too.  •  Inves0gate  mapping  and  linking  an  artwork’s  subject.  •  Expand  the  LOD  in  ways  that  will  enhance  research.  •  Create  a  tool  that  allows  users  to  “curate  stories”  using  LOD:   •  hSp://prezi.com/htrvh2jrcsio/cura0ng-­‐stories-­‐with-­‐linked-­‐open-­‐data/  •  Encourage  others  to  build  applica0ons  with  our  data.