as we may link: a model to support aggregated scientific knowledge

As  We  May  Link  A  model  to  support  aggregated  scien7fic  knowledge  

Centre  for  eResearch  Dept.  of  Computer  Science  University  of  Auckland  

Prashant  Gupta  (PhD  student)  Prof.  Mark  Gahegan  Prof.  Gillian  Dobbie    

The  current  state  of  scien7fic  prac7ces  

The  current  state  of  scien7fic  prac7ces  

How  well  are  we  carrying  forward  the  core  principles  of  science  (reproducibility,  

communica7on,  etc.  )  with  these  new  prac7ces?  

Learning  from  the  past  

Map  

Categories  

Learning  from  the  past  

Map  

Categories  

How  do  we  connect  them  back  to  synthesize  an  integrated  view  ?  

Learning  from  the  past  

“As  we  may  think”  (The  Atlan*c,  1945)      

hSp://thesciencebookstore.com/2009/10/the-­‐history-­‐of-­‐the-­‐internet-­‐remembering-­‐vannevar-­‐bush-­‐and-­‐the-­‐memex-­‐1945/  

Making  conceptual  connec7ons  explicit  

Map  

Associa7onist  view  

A  model  that  propose  connected  science  

A  model  that  propose  connected  science  

Associa7onist    view  

A  model  that  propose  connected  science  ^  

Live  and  

Associa7onist    view  

Organic  view  –  born,  evolve  and    

die  

Connec7ng  scien7fic  ar7facts  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

Connec7ng  scien7fic  ar7facts  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

Connec7ng  scien7fic  ar7facts  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

Live  connec7ons  among  scien7fic  

ar7facts  

Includes  e-­‐Science  tools  and  process  models  

Example  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

Example  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

1.  The  k-­‐means  classifier  used  for  land  cover  classifica7on  changes,  which  lead  to  change  in  the  categorical  model  

1  

Example  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

1.  The  k-­‐means  classifier  used  for  land  cover  classifica7on  changes,  which  lead  to  change  in  the  categorical  model  

2.  The  extension  of  category  ‘Forest’  changes  leading  to  change  in  the  data  stored  under  the  category.  

1  

2  

Example  

Data  Database  schema  

So]ware    tools  

Categories   Map  Ontology  

1.  The  k-­‐means  classifier  used  for  land  cover  classifica7on  changes,  which  lead  to  change  in  the  categorical  model  

2.  The  extension  of  category  ‘Forest’  changes  leading  to  change  in  the  data  stored  under  the  category.  

3.  Finally,  the  change  in  data  is  reflected  in  the  land  cover  map    

1  

2  

3  

Adventure  of  Categories  (AdvoCate)  

•  Allows  to  model  changes  in  categories  •  Maintains  a  category-­‐versioning  system  •  Connects  data,  methods  and  categories  along  with  the  different  versions  of  them  

•  Connect  changes  in  categories  with  the  tools  suppor7ng  database  and  ontology  evolu7on  tools  

Conclusion  

•  E-­‐Science  tools  not  only  enable  scien7fic  ac7vi7es,  but  also  provides  an  opportunity  to  bridge  the  gap  between  science  and  technology  and  ground  our  scien7fic  tools  in  the  process  of  science.  

•  This  model  supports  live  and  connected  science,  which  will  surface  up  more  scien7fic  processes  and  deeper  understanding  in  our  computa7onally  enabled  science.  

Ques7ons?  

Prashant  Gupta  p.gupta@auckland.ac.nz  

@pgupta_nz  

Special  thanks  to  Google  for  sponsored  7ckets  to  the  conference  J