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= What is Organic Data Science? =  
 
= What is Organic Data Science? =  
  
[[File:OrganicDataScience.jpg|thumb|left|Organic data science diagram goes here.]]
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We are investigating [[What_Is_Organic_Data_Science| Organic Data Science]], a new approach aimed to allow scientists to formulate and resolve science processes through an open framework that facilitates ad-hoc participation and entice collaborators based on attractive science goals. [[What_Is_Organic_Data_Science| Organic Data Science]] allows scientists to formulate and resolve science processes through an open framework that facilitates ad-hoc participation and entice collaborators based on attractive science goals.
  
We are investigating [[What_Is_Organic_Data_Science| Organic Data Science]], a new approach aimed to allow scientists to formulate and resolve science processes through an open framework that facilitates ad-hoc participation and entice collaborators based on attractive science goals.  Organic Data Science]] allows scientists to formulate and resolve science processes through an open framework that facilitates ad-hoc participation and entice collaborators based on attractive science goals. 
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= Technical and Social Aspects of Organic Data Science =
  
Accomplishing this requires three elements:
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We are pursuing a social computing approach that takes into account human aspects such as incentives and participation, while providing the fabric for representing and coordinating tasks involved in accomplishing science goals. Our approach will openly expose science tasks, facilitating inspection and engagement of new potential contributors. The collaboration will grow in an organic way, drawing in people and other contributions from existing data providers and cyberinfrastruture resources. 
  
# a science approach to tackle the problem of the age of water,
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=== Ongoing Technical Activities ===
# a technical substrate that facilitates transdisciplinary collaborations, and
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# a social approach to engage the community.
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<b><i>[[What_Is_Organic_Data_Science| Read more about Organic Data Science]].</i></b>
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We are working on several major activities:
  
= Our Science Goal: The Age of Water and Carbon =
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# [[Framework Design | Design the technical aspects of our organic data science framework]]
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# [[Human_Centered_Computing_to_Support_Organic_Data_Science | Understand the human-centered computing aspects of organic data science]]
  
[[File:VirtualOverlayNetworks.jpg|thumb|left|Organic team science would enable the creation of “virtual overlay networks” over existing cyberinfrastructure and other related activities.]]
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= Contributing to this project =
  
This study focuses on long-standing problems of coupled water and carbon budgets through development of a new scientific paradigm, <i>The Age of Water and Carbon,</i> that melds  theory and practice from limnology and hydrology within the new collaborative paradigm of [[Organic_Data_Science | Organic Data Science]]. We are integrating analytical frameworks from two communities – hydrology and isotope modeling in [http://criticalzone.org Critical Zone Observatories (CZOs)] and hydrodynamic water quality modeling from the [http://www.gleon.org Global Lake Ecological Observatory Network (GLEON)]  – to quantify water and material fluxes from two research sites, the Shales Hills CZO and the GLEON member site, [http://www.lternet.edu/sites/ntl North Temperate Lakes LTER]. This foundation will serve as a nexus for participation by multiple communities and will seed the growth of additional science through shared ideas, knowledge, and data. <b><i>[[Age_of_Water:_Example| Read more about Modeling the Age of Water and Carbon in Lake-Catchment Systems]].</i></b>  or <b><i>[[PIHM_Software| Read more about the PIHM catchment model]].</i></b>
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<b>[[Contributors | There is a growing set of contributors to the project]].</b>
  
= Ongoing Activities =
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We are testing this framework with a collaborative research project focused on the theoretical and experimental aspects of the isotopic age of water.  [http://www.organicdatascience.org/ageofwater Visit that project site].
  
* [[Develop a computational model for water and carbon isotopes in lake-catchment systems]]
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The contents of this wiki are accessible to everyone.  If you would like to contribute new content, please contact us to obtain an account by emailing us at <b>organic.data.science@gmail.com.</b>
* [[Select core lake and catchment models]]
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* [[Implement the catchment model for North Temperate Lakes]]
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* [[Implement the lake model for North Temperate Lakes]]
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* [[Couple the lake and catchment models]]
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=Software=
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=== Learning to Use the Organic Data Science Framework ===
  
<b>We are starting to describe models, help us fill in the blanks:</b>
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Get an account to learn in our [http://www.organicdatascience.org/training/ Training site].  You can also browse the [[How_to_use_this_semantic_wiki |documentation pages]].
 
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{{ #ask: [[Is a::model]]
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| ?author
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| ?software_license
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| ?language
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| default=No models are described in this site
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}}
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= Contributing to Organic Data Science =
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<b>We have [[Special Information for Newcomers]] to catch up with what we have been doing so far and our plans for the future.  </b>
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We are using a semantic wiki framework with significant extensions to structure collaboration processes. <b><i>[[Organic_Data_Science_through_a_Semantic_Wiki | Read more about how this framework works and how to participate and contribute]].</i></b>
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<b>[[How_to_use_this_organic_data_science_wiki | Get an account, and learn how to use this wiki]].</b>
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<b>There is a growing set of contributors to the project.  Here are some highlights about their expertise and affiliations.  You can help us fill in the empty cells by editing their individual pages, once you do that the information will be shown here:</b>
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{{ #ask: [[Is a::researcher]]
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| ?expertise
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| ?affiliation
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| format=template
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| template=Researcher
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| introtemplate=Researcher_Header
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| outrotemplate=Researcher_Footer
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| link=object
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| default=No researchers are described in this site
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}}
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= Acknowledgments =
 
= Acknowledgments =
  
 
This work is supported by the National Science Foundation through the INSPIRE program with grant number IIS-1344272.
 
This work is supported by the National Science Foundation through the INSPIRE program with grant number IIS-1344272.

Latest revision as of 10:56, 2 December 2014

What is Organic Data Science?

We are investigating Organic Data Science, a new approach aimed to allow scientists to formulate and resolve science processes through an open framework that facilitates ad-hoc participation and entice collaborators based on attractive science goals. Organic Data Science allows scientists to formulate and resolve science processes through an open framework that facilitates ad-hoc participation and entice collaborators based on attractive science goals.

Technical and Social Aspects of Organic Data Science

We are pursuing a social computing approach that takes into account human aspects such as incentives and participation, while providing the fabric for representing and coordinating tasks involved in accomplishing science goals. Our approach will openly expose science tasks, facilitating inspection and engagement of new potential contributors. The collaboration will grow in an organic way, drawing in people and other contributions from existing data providers and cyberinfrastruture resources.

Ongoing Technical Activities

We are working on several major activities:

  1. Design the technical aspects of our organic data science framework
  2. Understand the human-centered computing aspects of organic data science

Contributing to this project

There is a growing set of contributors to the project.

We are testing this framework with a collaborative research project focused on the theoretical and experimental aspects of the isotopic age of water. Visit that project site.

The contents of this wiki are accessible to everyone. If you would like to contribute new content, please contact us to obtain an account by emailing us at organic.data.science@gmail.com.

Learning to Use the Organic Data Science Framework

Get an account to learn in our Training site. You can also browse the documentation pages.

Acknowledgments

This work is supported by the National Science Foundation through the INSPIRE program with grant number IIS-1344272.

Yandex.Metrica