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+=================================
+Data Attributes and Data Locators
+=================================
+
+Datashape types provide a way to give an array-oriented schema for
+data to conform to, but do not specify how that data is laid out
+in memory or on disk. To be useful for exchanging data in memory
+between disparate systems, datashape additional defines data
+attributes and data locators (dattr and dloc) to define this precisely.
+
+Data Attributes
+===============
+
+Data attributes are specified as JSON objects associated with the type
+constructors in a datashape type. Let's start with some simple examples
+for various datashape dtypes.
+
+Simple integer and floating point types have the endianness of their
+storage specified::
+
+    # datashape
+    "int32", "float64", etc.
+
+    # dattr
+    {
+        "endian" : "big"
+    }
+
+For the pointer type, the pointer could be pointing to a structure and
+we're only interested in a field of it, so it's useful to provide
+attributes like ``offset``::
+
+    # datashape
+    "pointer[int32]"
+
+    # dattr
+    {
+        "offset" : 32,
+        "target" : { "endian" : "little" }
+    }
+
+Dimension types follow a nested structure as follows::
+
+    # datashape
+    "3 * 4 * int32"
+
+    # dattr
+    {
+        "stride" : 16,
+        "element" : {
+            "stride" : 4,
+            "element" : {
+                "endian" : "little"
+            }
+        }
+    }
+
+Data Locators
+=============
+
+Together, dshape and dattr can describe precisely how an array looks in memory or
+on disk. The last piece of the puzzle is to describe where that data is. Data
+locators fulfill this role.