€cdocutils.nodes document q)q}q(U nametypesq}q(X ���r projectqˆX���user storiesqNX���synopsisqNX���classes, fields, and methodsq NX���cranq ˆX���package designqNX���dataone r client packageqNuUsubstitution_defsq }qUparse_messagesq]qUcurrent_sourceqNU decorationqNUautofootnote_startqKUnameidsq}q(hU r-projectqhUuser-storiesqhUsynopsisqh Uclasses-fields-and-methodsqh UcranqhUpackage-designqhUdataone-r-client-packagequUchildrenq]qcdocutils.nodes section q)q }q!(U rawsourceq"U�U referencedq#KUparentq$hUsourceq%Xc���/var/lib/jenkins/jobs/API_Documentation_trunk/workspace/api-documentation/source/design/itk-d1r.txtq&Utagnameq'Usectionq(U attributesq)}q*(Udupnamesq+]Uclassesq,]Ubackrefsq-]Uidsq.]q/haUnamesq0]q1hauUlineq2KUdocumentq3hh]q4(cdocutils.nodes title q5)q6}q7(h"X���DataONE R Client Packageq8h$h h%h&h'Utitleq9h)}q:(h+]h,]h-]h.]h0]uh2Kh3hh]q;cdocutils.nodes Text q<X���DataONE R Client Packageq=…q>}q?(h"h8h$h6ubaubh)q@}qA(h"U�h$h h%h&h'h(h)}qB(h+]h,]h-]h.]qChah0]qDhauh2Kh3hh]qE(h5)qF}qG(h"X���SynopsisqHh$h@h%h&h'h9h)}qI(h+]h,]h-]h.]h0]uh2Kh3hh]qJh<X���SynopsisqK…qL}qM(h"hHh$hFubaubcdocutils.nodes paragraph qN)qO}qP(h"X³��Environmental scientists commonly use the `R Project`_ software system for statistical analysis and modeling. The R framework is a flexible statistical computing environment with robust, extensive packages to perform a large variety of analysis and modeling tasks. Because R is open source and extensible, it has been widely adopted by the environmental science community, and it is easy to extend to provide new analysis capabilities.h$h@h%h&h'U paragraphqQh)}qR(h+]h,]h-]h.]h0]uh2Kh3hh]qS(h<X*���Environmental scientists commonly use the qT…qU}qV(h"X*���Environmental scientists commonly use the h$hOubcdocutils.nodes reference qW)qX}qY(h"X���`R Project`_UresolvedqZKh$hOh'U referenceq[h)}q\(UnameX ���R ProjectUrefuriq]X���http://www.r-project.orgq^h.]h-]h+]h,]h0]uh]q_h<X ���R Projectq`…qa}qb(h"U�h$hXubaubh<X}�� software system for statistical analysis and modeling. The R framework is a flexible statistical computing environment with robust, extensive packages to perform a large variety of analysis and modeling tasks. Because R is open source and extensible, it has been widely adopted by the environmental science community, and it is easy to extend to provide new analysis capabilities.qc…qd}qe(h"X}�� software system for statistical analysis and modeling. The R framework is a flexible statistical computing environment with robust, extensive packages to perform a large variety of analysis and modeling tasks. Because R is open source and extensible, it has been widely adopted by the environmental science community, and it is easy to extend to provide new analysis capabilities.h$hOubeubhN)qf}qg(h"X»��The `DataONE R Client Package`_ is an R package that provides access to the DataONE services that are present at Coordinating Nodes and Member Nodes. The tool will allow an R user to easily load the d1r package (using CRAN_) and then use functions in R to search the DataONE system, locate data of interest, load that data into the R environment, process it using R's various tools, and then upload derived data and metadata back into DataONE.h$h@h%h&h'hQh)}qh(h+]h,]h-]h.]h0]uh2Kh3hh]qi(h<X���The qj…qk}ql(h"X���The h$hfubhW)qm}qn(h"X���`DataONE R Client Package`_hZKh$hfh'h[h)}qo(UnameX���DataONE R Client Packageh.]h-]h+]h,]h0]Urefidqphuh]qqh<X���DataONE R Client Packageqr…qs}qt(h"U�h$hmubaubh<X»��� is an R package that provides access to the DataONE services that are present at Coordinating Nodes and Member Nodes. The tool will allow an R user to easily load the d1r package (using qu…qv}qw(h"X»��� is an R package that provides access to the DataONE services that are present at Coordinating Nodes and Member Nodes. The tool will allow an R user to easily load the d1r package (using h$hfubhW)qx}qy(h"X���CRAN_hZKh$hfh'h[h)}qz(UnameX���CRANh]X���http://cran.r-project.orgq{h.]h-]h+]h,]h0]uh]q|h<X���CRANq}…q~}q(h"U�h$hxubaubh<XÜ���) and then use functions in R to search the DataONE system, locate data of interest, load that data into the R environment, process it using R's various tools, and then upload derived data and metadata back into DataONE.q€…q}q‚(h"XÜ���) and then use functions in R to search the DataONE system, locate data of interest, load that data into the R environment, process it using R's various tools, and then upload derived data and metadata back into DataONE.h$hfubeubhN)qƒ}q„(h"X¤��By targeting R in the Investigator Toolkit, we enable a wide variety of scientists to harness data within the network of Member Nodes, and to reference the data sets within their R scripts using their unique identifiers from DataONE. This allows anyone to execute the R script from a paper or analysis, and the `dataone` library handles the details of finding and accessing the data needed for analysis or visualization.h$h@h%h&h'hQh)}q…(h+]h,]h-]h.]h0]uh2Kh3hh]q†(h<X7��By targeting R in the Investigator Toolkit, we enable a wide variety of scientists to harness data within the network of Member Nodes, and to reference the data sets within their R scripts using their unique identifiers from DataONE. This allows anyone to execute the R script from a paper or analysis, and the q‡…qˆ}q‰(h"X7��By targeting R in the Investigator Toolkit, we enable a wide variety of scientists to harness data within the network of Member Nodes, and to reference the data sets within their R scripts using their unique identifiers from DataONE. This allows anyone to execute the R script from a paper or analysis, and the h$hƒubcdocutils.nodes title_reference qŠ)q‹}qŒ(h"X ���`dataone`h)}q(h+]h,]h-]h.]h0]uh$hƒh]qŽh<X���dataoneq…q}q‘(h"U�h$h‹ubah'Utitle_referenceq’ubh<Xd��� library handles the details of finding and accessing the data needed for analysis or visualization.q“…q”}q•(h"Xd��� library handles the details of finding and accessing the data needed for analysis or visualization.h$hƒubeubcdocutils.nodes target q–)q—}q˜(h"X'���.. _R Project: http://www.r-project.orgh#Kh$h@h%h&h'Utargetq™h)}qš(h]h^h.]q›hah-]h+]h,]h0]qœhauh2Kh3hh]ubh–)q}qž(h"X#���.. _CRAN: http://cran.r-project.orgh#Kh$h@h%h&h'h™h)}qŸ(h]h{h.]q hah-]h+]h,]h0]q¡h auh2Kh3hh]ubeubh)q¢}q£(h"U�h$h h%h&h'h(h)}q¤(h+]h,]h-]h.]q¥hah0]q¦hauh2K h3hh]q§(h5)q¨}q©(h"X���User storiesqªh$h¢h%h&h'h9h)}q«(h+]h,]h-]h.]h0]uh2K h3hh]q¬h<X���User storiesq…q®}q¯(h"hªh$h¨ubaubcdocutils.nodes bullet_list q°)q±}q²(h"U�h$h¢h%h&h'Ubullet_listq³h)}q´(UbulletqµX���*h.]h-]h+]h,]h0]uh2K"h3hh]q¶(cdocutils.nodes list_item q·)q¸}q¹(h"XE���A scientist with R on their system can easily install d1r from CRAN_ h$h±h%h&h'U list_itemqºh)}q»(h+]h,]h-]h.]h0]uh2Nh3hh]q¼hN)q½}q¾(h"XD���A scientist with R on their system can easily install d1r from CRAN_h$h¸h%h&h'hQh)}q¿(h+]h,]h-]h.]h0]uh2K"h]qÀ(h<X?���A scientist with R on their system can easily install d1r from qÁ…qÂ}qÃ(h"X?���A scientist with R on their system can easily install d1r from h$h½ubhW)qÄ}qÅ(h"X���CRAN_hZKh$h½h'h[h)}qÆ(UnameX���CRANh]h{h.]h-]h+]h,]h0]uh]qÇh<X���CRANqÈ…qÉ}qÊ(h"U�h$hÄubaubeubaubh·)qË}qÌ(h"X(��A scientist can load a data object using its DataONE identifier from the DataONE system into R for further processing by other R functions. The data objects supported should minimally include: * Data Tables in CSV and other delimited formats * NetCDF files * Raster images in various formats h$h±h%h&h'hºh)}qÍ(h+]h,]h-]h.]h0]uh2Nh3hh]qÎ(hN)qÏ}qÐ(h"XÀ���A scientist can load a data object using its DataONE identifier from the DataONE system into R for further processing by other R functions. The data objects supported should minimally include:qÑh$hËh%h&h'hQh)}qÒ(h+]h,]h-]h.]h0]uh2K$h]qÓh<XÀ���A scientist can load a data object using its DataONE identifier from the DataONE system into R for further processing by other R functions. The data objects supported should minimally include:qÔ…qÕ}qÖ(h"hÑh$hÏubaubcdocutils.nodes block_quote q×)qØ}qÙ(h"U�h)}qÚ(h+]h,]h-]h.]h0]uh$hËh]qÛh°)qÜ}qÝ(h"U�h)}qÞ(hµX���*h.]h-]h+]h,]h0]uh$hØh]qß(h·)qà}qá(h"X.���Data Tables in CSV and other delimited formatsqâh)}qã(h+]h,]h-]h.]h0]uh$hÜh]qähN)qå}qæ(h"hâh$hàh%h&h'hQh)}qç(h+]h,]h-]h.]h0]uh2K(h]qèh<X.���Data Tables in CSV and other delimited formatsqé…qê}që(h"hâh$håubaubah'hºubh·)qì}qí(h"X���NetCDF filesqîh)}qï(h+]h,]h-]h.]h0]uh$hÜh]qðhN)qñ}qò(h"hîh$hìh%h&h'hQh)}qó(h+]h,]h-]h.]h0]uh2K)h]qôh<X���NetCDF filesqõ…qö}q÷(h"hîh$hñubaubah'hºubh·)qø}qù(h"X!���Raster images in various formats h)}qú(h+]h,]h-]h.]h0]uh$hÜh]qûhN)qü}qý(h"X ���Raster images in various formatsqþh$høh%h&h'hQh)}qÿ(h+]h,]h-]h.]h0]uh2K*h]r���h<X ���Raster images in various formatsr��…r��}r��(h"hþh$hüubaubah'hºubeh'h³ubah'Ublock_quoter��ubeubh·)r��}r��(h"XÈ���A scientist can use d1r to search for data based on critical metadata, including title, creator, keywords, abstract, spatial location, temporal coverage, taxonomic coverage, and other relevant fields h$h±h%h&h'hºh)}r��(h+]h,]h-]h.]h0]uh2Nh3hh]r��hN)r ��}r ��(h"XÇ���A scientist can use d1r to search for data based on critical metadata, including title, creator, keywords, abstract, spatial location, temporal coverage, taxonomic coverage, and other relevant fieldsr��h$j��h%h&h'hQh)}r��(h+]h,]h-]h.]h0]uh2K,h]r ��h<XÇ���A scientist can use d1r to search for data based on critical metadata, including title, creator, keywords, abstract, spatial location, temporal coverage, taxonomic coverage, and other relevant fieldsr��…r��}r��(h"j��h$j ��ubaubaubh·)r��}r��(h"X´���A scientist can load all of the supported data objects into R by using the metadata found in a metadata search without directly knowing the identifiers for individual data objects h$h±h%h&h'hºh)}r��(h+]h,]h-]h.]h0]uh2Nh3hh]r��hN)r��}r��(h"X³���A scientist can load all of the supported data objects into R by using the metadata found in a metadata search without directly knowing the identifiers for individual data objectsr��h$j��h%h&h'hQh)}r��(h+]h,]h-]h.]h0]uh2K0h]r��h<X³���A scientist can load all of the supported data objects into R by using the metadata found in a metadata search without directly knowing the identifiers for individual data objectsr��…r��}r��(h"j��h$j��ubaubaubh·)r��}r��(h"X��Given a data object loaded from DataONE into R, a scientist can display the science metadata associated with that object from within the R system (this might include a link to an external web URI that provides a nice human readable version of the metadata too) h$h±h%h&h'hºh)}r��(h+]h,]h-]h.]h0]uh2Nh3hh]r ��hN)r!��}r"��(h"X��Given a data object loaded from DataONE into R, a scientist can display the science metadata associated with that object from within the R system (this might include a link to an external web URI that provides a nice human readable version of the metadata too)r#��h$j��h%h&h'hQh)}r$��(h+]h,]h-]h.]h0]uh2K4h]r%��h<X��Given a data object loaded from DataONE into R, a scientist can display the science metadata associated with that object from within the R system (this might include a link to an external web URI that provides a nice human readable version of the metadata too)r&��…r'��}r(��(h"j#��h$j!��ubaubaubh·)r)��}r*��(h"X„���A scientist can authenticate with the DataONE system in order to establish their identity to access restricted objects and services h$h±h%h&h'hºh)}r+��(h+]h,]h-]h.]h0]uh2Nh3hh]r,��hN)r-��}r.��(h"Xƒ���A scientist can authenticate with the DataONE system in order to establish their identity to access restricted objects and servicesr/��h$j)��h%h&h'hQh)}r0��(h+]h,]h-]h.]h0]uh2K9h]r1��h<Xƒ���A scientist can authenticate with the DataONE system in order to establish their identity to access restricted objects and servicesr2��…r3��}r4��(h"j/��h$j-��ubaubaubh·)r5��}r6��(h"XŽ���A scientist can upload an R dataframe as a data set with associated science and system metadata for that object from within the R environment h$h±h%h&h'hºh)}r7��(h+]h,]h-]h.]h0]uh2Nh3hh]r8��hN)r9��}r:��(h"X���A scientist can upload an R dataframe as a data set with associated science and system metadata for that object from within the R environmentr;��h$j5��h%h&h'hQh)}r<��(h+]h,]h-]h.]h0]uh2K<h]r=��h<X���A scientist can upload an R dataframe as a data set with associated science and system metadata for that object from within the R environmentr>��…r?��}r@��(h"j;��h$j9��ubaubaubeubeubh)rA��}rB��(h"U�h$h h%h&h'h(h)}rC��(h+]h,]h-]h.]rD��hah0]rE��hauh2K@h3hh]rF��(h5)rG��}rH��(h"X���Package designrI��h$jA��h%h&h'h9h)}rJ��(h+]h,]h-]h.]h0]uh2K@h3hh]rK��h<X���Package designrL��…rM��}rN��(h"jI��h$jG��ubaubh)rO��}rP��(h"U�h$jA��h%h&h'h(h)}rQ��(h+]h,]h-]h.]rR��hah0]rS��h auh2KCh3hh]rT��(h5)rU��}rV��(h"X���Classes, fields, and methodsrW��h$jO��h%h&h'h9h)}rX��(h+]h,]h-]h.]h0]uh2KCh3hh]rY��h<X���Classes, fields, and methodsrZ��…r[��}r\��(h"jW��h$jU��ubaubcdocutils.nodes note r]��)r^��}r_��(h"XE��All of the classes and methods in R are inverted (ie, classes don't contain methods per se, instead, methods are specialized to work on particular classes, and the class is generally passed in as the first parameter of the method call. So, all signatures below need to have an added parameter for this object to be passed in.h$jO��h%h&h'Unoter`��h)}ra��(h+]h,]h-]h.]h0]uh2Nh3hh]rb��hN)rc��}rd��(h"XE��All of the classes and methods in R are inverted (ie, classes don't contain methods per se, instead, methods are specialized to work on particular classes, and the class is generally passed in as the first parameter of the method call. So, all signatures below need to have an added parameter for this object to be passed in.re��h$j^��h%h&h'hQh)}rf��(h+]h,]h-]h.]h0]uh2KFh]rg��h<XE��All of the classes and methods in R are inverted (ie, classes don't contain methods per se, instead, methods are specialized to work on particular classes, and the class is generally passed in as the first parameter of the method call. So, all signatures below need to have an added parameter for this object to be passed in.rh��…ri��}rj��(h"je��h$jc��ubaubaubj]��)rk��}rl��(h"X��This design is out of date, and instead follows the design in DataPackage. The R package mainly follows and uses the Java implementation, so does not need to reimplement this structure. Probably can delete this section, but leaving for now until DataPackage design is completed.h$jO��h%h&h'j`��h)}rm��(h+]h,]h-]h.]h0]uh2Nh3hh]rn��hN)ro��}rp��(h"X��This design is out of date, and instead follows the design in DataPackage. The R package mainly follows and uses the Java implementation, so does not need to reimplement this structure. Probably can delete this section, but leaving for now until DataPackage design is completed.rq��h$jk��h%h&h'hQh)}rr��(h+]h,]h-]h.]h0]uh2KMh]rs��h<X��This design is out of date, and instead follows the design in DataPackage. The R package mainly follows and uses the Java implementation, so does not need to reimplement this structure. Probably can delete this section, but leaving for now until DataPackage design is completed.rt��…ru��}rv��(h"jq��h$jo��ubaubaubh°)rw��}rx��(h"U�h$jO��h%h&h'h³h)}ry��(hµX���*h.]h-]h+]h,]h0]uh2KRh3hh]rz��(h·)r{��}r|��(h"XŒ��D1Client * Fields * endpoint * username * cli <D1Client> * token <AuthToken> * Constructors * D1Client(CN_URI) * Methods * login(username, password): AuthToken * logout() * getEndpoint(): String * getPackage(pid): DataPackage * getUsername(): String * getToken(): AuthToken * search(): ResultSet * resolve(pid): [MemberNodeURI] h$jw��h%Nh'hºh)}r}��(h+]h,]h-]h.]h0]uh2Nh3hh]r~��cdocutils.nodes definition_list r��)r€��}r��(h"U�h)}r‚��(h+]h,]h-]h.]h0]uh$j{��h]rƒ��cdocutils.nodes definition_list_item r„��)r…��}r†��(h"X|��D1Client * Fields * endpoint * username * cli <D1Client> * token <AuthToken> * Constructors * D1Client(CN_URI) * Methods * login(username, password): AuthToken * logout() * getEndpoint(): String * getPackage(pid): DataPackage * getUsername(): String * getToken(): AuthToken * search(): ResultSet * resolve(pid): [MemberNodeURI] h$j€��h%h&h'Udefinition_list_itemr‡��h)}rˆ��(h+]h,]h-]h.]h0]uh2Kbh]r‰��(cdocutils.nodes term rŠ��)r‹��}rŒ��(h"X���D1Clientr��h$j…��h%h&h'UtermrŽ��h)}r��(h+]h,]h-]h.]h0]uh2Kbh]r��h<X���D1Clientr‘��…r’��}r“��(h"j��h$j‹��ubaubcdocutils.nodes definition r”��)r•��}r–��(h"U�h)}r—��(h+]h,]h-]h.]h0]uh$j…��h]r˜��h°)r™��}rš��(h"U�h)}r›��(hµX���*h.]h-]h+]h,]h0]uh$j•��h]rœ��(h·)r��}rž��(h"XI���Fields * endpoint * username * cli <D1Client> * token <AuthToken>h)}rŸ��(h+]h,]h-]h.]h0]uh$j™��h]r ��j��)r¡��}r¢��(h"U�h)}r£��(h+]h,]h-]h.]h0]uh$j��h]r¤��j„��)r¥��}r¦��(h"XA���Fields * endpoint * username * cli <D1Client> * token 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