tasks Makes repetitive tasks take far less time Facilitates tool creation by developers Allows research questions to be addressed more quickly Facilitates reproducibility · · · · 5/37
data to consumers Makes data consumption easy from any programming language Base URI, e.g. http://foo.com Media type, e.g., json, xml HTTP verbs, like GET, POST, PUT, PATCH, HEAD, etc... · · · 7/37
clients Good place to include altmetrics standards... # % R A M L 0 . 8 – – – t i t l e : W o r l d M u s i c A P I b a s e U r i : h t t p : / / e x a m p l e . a p i . c o m / { v e r s i o n } v e r s i o n : v 1 / s o n g s : g e t : p o s t : . . . 12/37
and Ten Other... - via Altmetric.com Tweeting biomedicine: an analysis of tweets... - via Altmetric.com The Spread of Scientific Information... - via PLOS ALM Can Tweets Predict Citations? ... - via Twitter Search API Altmetrics in the Wild... - via PLOS ALM, various APIs, WebofSci citations Social Media Release Increases Dissemination... - via manual collection Identifying Audiences of E-Infrastructures... - via Google Analytics How the Scientific Community Reacts to... - via Twitter Search API, Google Scholar citations · · · · · · · · 17/37
- G E T ( " h t t p : / / a l m . p l o s . o r g / a p i / v 3 / a r t i c l e s ? d o i = 1 0 . 1 3 7 1 / j o u r n a l . p m e d . 1 0 0 1 3 6 1 & k e y = < k e y > " ) s t o p _ f o r _ s t a t u s ( o u t ) c o n t e n t ( o u t ) { d o i : " 1 0 . 1 3 7 1 / j o u r n a l . p m e d . 1 0 0 1 3 6 1 " , t i t l e : " P e r s o n a l i z e d P r e d i c t i o n o f L i f e t i m e B e n e f i t s w i t h S t a t i n T h e r a p y f o r A s y m p t o m a t i c I n d i v i d u a l s : A M o d e l i n g S t u d y " , u r l : " h t t p : / / w w w . p l o s m e d i c i n e . o r g / a r t i c l e / i n f o % 3 A d o i % 2 F 1 0 . 1 3 7 1 % 2 F j o u r n a l . p m e d . 1 0 0 1 3 6 1 " , m e n d e l e y : " 4 3 7 b 0 7 d 9 - b c 4 0 - 4 c 5 7 - b 6 0 e - 1 f 6 0 f e f e 2 3 0 0 " , p m i d : " 2 3 3 0 0 3 8 8 " , p m c i d : " 3 5 3 1 5 0 1 " , p u b l i c a t i o n _ d a t e : " 2 0 1 2 - 1 2 - 2 7 T 0 8 : 0 0 : 0 0 Z " , u p d a t e _ d a t e : " 2 0 1 3 - 1 0 - 0 7 T 1 1 : 0 6 : 5 8 Z " , v i e w s : 9 3 2 9 , s h a r e s : 6 2 , b o o k m a r k s : 5 , c i t a t i o n s : 1 } 22/37
( d o i = " 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 2 9 7 9 7 " ) A n o b j e c t o f c l a s s " a l m t o t " S l o t " m e t a " : $ d o i [ 1 ] " 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 2 9 7 9 7 " . . . < m o r e m e t a d a t a > S l o t " s u m m a r y " : v i e w s s h a r e s b o o k m a r k s c i t a t i o n s 1 2 9 2 2 9 2 3 7 5 1 7 S l o t " d a t a " : . i d p d f h t m l s h a r e s g r o u p s c o m m e n t s l i k e s c i t a t i o n s t o t a l 1 b l o g l i n e s N A N A N A N A N A N A 0 0 2 c i t e u l i k e N A N A 1 N A N A N A N A 1 3 c o n n o t e a N A N A N A N A N A N A 0 0 4 c r o s s r e f N A N A N A N A N A N A 7 7 5 n a t u r e N A N A N A N A N A N A 4 4 . . . 23/37
data with a single function, and highlight inconsistencies p l o s _ d a t a < - a l m ( < d o i > ) i m p a c t s t o r y _ d a t a < - m e t r i c s ( < d o i > ) a l t m e t r i c _ d a t a < - a l t m e t r i c _ d a t a ( a l t m e t r i c s ( < d o i > ) ) a l t _ c o m b i n e ( p l o s _ d a t a , i m p a c t s t o r y _ d a t a , a l t m e t r i c _ d a t a ) W a r n i n g : I n c o n s i s t e n c y i n f a c e b o o k L i k e s , c h e c k m e t a d a t a d a t a S o u r c e f r o m P r o v i d e r v a l u e s 1 t w i t t e r P L O S A L M 1 0 0 2 f a c e b o o k L i k e s I m p a c t S t o r y 5 0 3 f a c e b o o k L i k e s A l t m e t r i c 4 0 4 s c o p u s C i t a t i o n s A l t m e t r i c 1 5 0 26/37
data, plot l i b r a r y ( r p l o s ) ; l i b r a r y ( a l m ) ; l i b r a r y ( p l y r ) d o i s < - s e a r c h p l o s ( t e r m s = ' * : * ' , f i e l d s = " i d " , l i m i t = 2 0 0 ) a l m < - l d p l y ( a l m ( d o i = d o . c a l l ( c , d o i s $ i d ) , t o t a l _ d e t a i l s = T R U E ) ) p l o t _ d e n s i t y ( a l m , c ( " c o u n t e r _ p d f " , " m e n d e l e y _ s h a r e s " , " p m c _ p d f " , " p m c _ t o t a l " ) , c ( " # 8 3 D F B 4 " , " # E F A 5 A 5 " , " # C F D 4 7 0 " , " # B 2 C 9 E 4 " ) , p l o t _ t y p e = " h " ) 27/37
29,208.0 views shares bookmarks citations Grouped Stacked l i b r a r y ( r p l o s ) ; l i b r a r y ( a l m ) ; l i b r a r y ( r C h a r t s ) d o i s < - c ( ' 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 0 1 5 4 3 ' , ' 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 4 0 1 1 7 ' , ' 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 2 9 7 9 7 ' , ' 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 3 9 3 9 5 ' ) d a t < - s i g n p o s t s ( d o i = d o i s ) p l o t _ s i g n p o s t s ( i n p u t = d a t , t y p e = " m u l t i B a r C h a r t " , h e i g h t = 4 0 0 ) 28/37
Consistency (tweets from source A and B should be =) Correlation (is metric A strongly corr. with B?) Interpretation (open source the interpretation) Gaming (security through obscurity doesn't work) · · · · 31/37
Open data makes all this easier Consistency (tweets from source A and B should be =) Correlation (is metric A strongly corr. with B?) Interpretation (open source the interpretation) Gaming (security through obscurity doesn't work) · · · · 32/37
For-profit products Who knows? Making data open allows many experiments, some of which will stick · Doesn't require open data I suppose :(, but helps facilitate research e.g., think how hard text-mining is - we don't want that in altmetrics - - · ReaderMeter ScienceCard - - · · 33/37