Scipediacontent: Scipediacontent moved page Draft Content 893723967 to Espinosa-Oviedo et al 2020a

2021-01-21T13:39:32Z

Scipediacontent moved page Draft Content 893723967 to Espinosa-Oviedo et al 2020a

Scipediacontent: Created page with " == Abstract == This paper proposes a study of existing environments used to enact data science pipelines applied to graphs. Data science pipelines are a new form of queries..."

2021-01-21T13:39:29Z

Created page with " == Abstract == This paper proposes a study of existing environments used to enact data science pipelines applied to graphs. Data science pipelines are a new form of queries..."

New page

== Abstract ==

This paper proposes a study of existing environments used to enact data science pipelines applied to graphs. Data science pipelines are a new form of queries combining classic graph operations with artificial intelligence graph analytics operations. A pipeline defines a data flow consisting of tasks for querying, exploring and analysing graphs. Different environments and systems can be used for enacting pipelines. They range from graph NoSQL stores, programming languages extended with libraries providing graph processing and analytics functions, to full machine learning and artificial intelligence studios. The paper describes these environments and the design principles that they promote for enacting data science pipelines intended to query, process and explore data collections and particularly graphs.

== Original document ==

The different versions of the original document can be found in:

* [https://hal.archives-ouvertes.fr/hal-03002550 https://hal.archives-ouvertes.fr/hal-03002550]

* [http://link.springer.com/content/pdf/10.1007/978-3-030-55814-7_23 http://link.springer.com/content/pdf/10.1007/978-3-030-55814-7_23],
: [http://dx.doi.org/10.1007/978-3-030-55814-7_23 http://dx.doi.org/10.1007/978-3-030-55814-7_23] under the license http://www.springer.com/tdm

* [https://link.springer.com/10.1007/978-3-030-55814-7_23 https://link.springer.com/10.1007/978-3-030-55814-7_23],
: [http://doi.org/10.1007/978-3-030-55814-7_23 http://doi.org/10.1007/978-3-030-55814-7_23],
: [https://doi.org/10.1007/978-3-030-55814-7_23 https://doi.org/10.1007/978-3-030-55814-7_23],
: [https://dblp.uni-trier.de/db/conf/adbis/adbis2020w.html#Vargas-SolarZE20 https://dblp.uni-trier.de/db/conf/adbis/adbis2020w.html#Vargas-SolarZE20],
: [https://academic.microsoft.com/#/detail/3051330280 https://academic.microsoft.com/#/detail/3051330280]

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Espinosa-Oviedo et al 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 893723967 to Espinosa-Oviedo et al 2020a

Scipediacontent: Created page with " == Abstract == This paper proposes a study of existing environments used to enact data science pipelines applied to graphs. Data science pipelines are a new form of queries..."