Adds About Documentation. (#20)

* Adds About Documentation.

Signed-off-by: David Brown <dmlb2000@gmail.com>

* Incorporate Linda's requests

Signed-off-by: David Brown <dmlb2000@gmail.com>

* General operating model purpose paragraph

Signed-off-by: David Brown <dmlb2000@gmail.com>

* Update to remove project paragraph

Signed-off-by: David Brown <dmlb2000@gmail.com>

Author: dmlb2000

project/about.md

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+# About Pacifica
+
+## History
+
+Pacifica was created from a collaboration in the
+[United States National Laboratory](https://en.wikipedia.org/wiki/United_States_Department_of_Energy_national_laboratories)
+system. The Environmental Molecular Sciences Laboratory ([EMSL](https://www.emsl.pnnl.gov))
+collaborated with its host institution Pacific Northwest National Laboratory
+([PNNL](https://www.pnnl.gov)) to help manage the scientific data generated
+by researchers.
+
+EMSL is a [user facility](https://www.energy.gov/science/science-innovation/office-science-user-facilities)
+sponsored by the Department of Energy ([DOE](https://www.energy.gov))
+Office of Science ([here](https://www.energy.gov/science)) Biological and
+Environmental Research ([BER](https://www.energy.gov/science/ber/biological-and-environmental-research)).
+
+Pacifica was created by EMSL and PNNL in response to 
+[DOE Data Management Policy](https://www.energy.gov/datamanagement/doe-policy-digital-research-data-management)
+to manage open research data to make it more transparent. EMSL and
+PNNL both have similar administrative challenges in that a single
+project can not shoulder the burden of meeting the policy on its
+own. This brought both EMSL and PNNL to the table to collaborate on
+developing an institutional data management system for open research
+science.
+
+## The Data Management Challenge
+
+The challenge is defined within the nexus of a large institution's
+operating model, and the data policies the institution is required
+to follow.
+
+### DOE Data Management Policy
+
+The DOE Data Management policy covers a lot, but we will only highlight
+the guiding principles here.
+
+#### Effective Data Management
+
+```
+ 1. Effective data management has the potential to increase the pace of
+    scientific discovery and promote more efficient and effective use of
+    government funding and resources. Data management planning should be
+    an integral part of research planning.
+```
+
+Pacifica addresses these challenges by offering an effective mechanism
+for data sharing, thus maximizing the impact of research across all
+participating organizations.
+
+#### Sharing Proves Integrity
+
+```
+ 2. Sharing and preserving data are central to protecting the integrity of
+    science by facilitating validation of results and to advancing science
+    by broadening the value of research data to disciplines other than the
+    originating one and to society at large. To the greatest extent, with
+    the fewest constraints possible, and consistent with the requirements
+    and other principles stated in this document, data sharing should make
+    digital research data available to and useful for the scientific
+    community, industry, and the public.
+```
+
+Sharing scientific data with the public proves the scientific work being done
+is of the highest integrity. A dependency of this is to share the software
+system managing the data in an open source model. Without an open source 
+software model the integrity of the data and the science could be suspect.
+This is why Pacifica is an open source software project.
+
+#### Preserve What You Can
+
+```
+ 3. Not all data need to be shared or preserved. The costs and benefits of
+    doing so should be considered in data management planning.
+```
+
+The task of sharing and preserving all data generated by open science is
+costly, especially for small projects. The overhead required to adhere to
+meeting the policy must be addressed by the supporting institution.
+
+### The Operating Model
+
+Research institutions allocate and spend funds they recieve in different
+ways. Whatever that model is, data is created at every level of the
+model. Hense, it is important to capture the funding model and the
+relationships to data the internally, Pacifica can fill that requirement.
+
+However, the operating model does not reflect the evolution of scientific
+data. In order to understand what data were created within the spending
+scope, including related projects and sub-tasks, a system needs to be
+integrated in the project from initiation to end.
+
+### The Scientific Data Life-Cycle
+
+The scientific data life-cycle more closely maps to a tree or bush. The
+start of the tree extends back in time. Each branch of the tree a piece
+of scientific data critical to supporting science being done today. The
+leaves of the branch represent the cutting edge of science. Some leaves
+prove to be more sturdy than others and go on to grow into their own
+branch. The most important part of the analogy is that the tree did
+start from somewhere, and we know a little about the immediate future.
+However, the sky is the limit and we do not know how big the tree will
+grow. So, we need to keep the knowledge and data generated in the past
+preserved to keep the tree strong and healthy.