Fixes to documentation files

docs/source/conf.py

@@ -120,7 +120,7 @@
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-html_theme = 'alabaster'
+html_theme = 'sphinx_rtd_theme'
 
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the

docs/source/dataset_about.rst

@@ -6,28 +6,29 @@ Describing what the dataset is about (i.e what was the scope, objective, materia
 
 * Document the nature of information available in a dataset through the Biocaddie **'data type'** object.
 
-.. image:: ./img/DATS-v2.1-alpha-Distribution-Relation-and-Qualifiers.png
+.. image:: ./_static/DATS-v2.1-alpha-Distribution-Relation-and-Qualifiers.png
    :alt: A conceptual map detailing Biocaddie DATS data-type qualifiers and data distribution descriptors .
 
 In this context, the *‘data type’* required to annotate a DataSet should be viewed as a *content type* [terminology needs to be specified]). This encompasses the nature of the signal recorded in a dataset or information content of interest. For instance: gene expression data or phenotypic data, electronic health records 
 But mime-type may be used.
-		* chemical
-		* sequence
-		* spectrum
-		* audio
-		* image
-		* video
-		* ...	
+* chemical
+* sequence
+* spectrum
+* audio
+* image
+* video
+* ...
 
-	but other descriptors may be used such as Biosharing, Scicrunch or re3data category/data domain descriptors.
+but other descriptors may be used such as Biosharing, Scicrunch or re3data category/data domain descriptors.
+
+* Data aggregation type:
 
-  * Data aggregation type:
   In the context of DataMed indexing, the information obtained from repositories may correspond to datasets served individually or may correspond to collections or records. As these 2 situations represent a very different metadata context, the Biocaddie DATS model allows to distinguish between the two cases.
+* collection (as in 'collection of instances')
+* singleton (as in ‘individual instance’)
 
-		* collection (as in 'collection of instances')
-		* singleton (as in ‘individual instance’)
+* Data refinement type:
 
-  * Data refinement type: 
 To describe the level of data processing associated with the data available from the dataset and its distributions....[terminology needs to be specified])
 
 		* raw data
@@ -52,6 +53,7 @@ To describe the level of data processing associated with the data available from
 * Document the nature of intervention and Treatment applied to the Material, if any or if applicable.
 
 * Data Types and specific Platform
+
 Currently, in DataMed, datasets can be search according to Data Type (.e.g Proteomics data) and/or by Platform (e.g. Illumina)
 DATS provides a mechanism via DataType object to qualify the nature of the data collected in a Dataset. The 4 facets/attributes allow to incrementally specify the type of information contained by the data and how it has been produced
 

docs/source/dataset_distribution.rst

@@ -27,7 +27,7 @@ The same Dataset identified by accession number DRP000443 can be accessed throug
 While the distributions use the same Format, the accessURL are different as are the Repository but these distributions are all about the same dataset 
 
 
-.. image:: ./img/DATS-v2.0-postSanDiego-Meeting-Dataset-Distribution-SRA-examples.png
+.. image:: ./_static/DATS-v2.0-postSanDiego-Meeting-Dataset-Distribution-SRA-examples.png
    :alt: A conceptual map detailing Biocaddie DATS distribution for an nucleic acid sequencing dataset as mirrored by 3 INSDC repositories: NCBI SRA, EBI ENA and DDBJ.	
 
 The block below shows a snippet of a Biocaddie DATS JSON document holding key information about dataset distribution. Note the link to *access information* and *data file format* information.