Introduction.md

-This repository consist in a collection of R-scripts to homogenise platform 
+This repository is a collection of R-scripts to homogenise platform 
 identifier information and to identify duplicate observations in the 
-**International Comprehensive Ocean-Atmosphere Data Set** (ICOADS) marine data source.
+**International Comprehensive Ocean-Atmosphere Data Set** (ICOADS) marine data source. **BOLD** denotes an ICOADS variable name.
 
 ICOADS is the world most extensive surface marine meteorological data collection. 
 Contains ocean surface and atmospheric observations from the 1600's 
@@ -8,7 +8,7 @@ to present and is still receiving more data every year.
 The data base is made up of observation reports from many different sources, 
 there are several hundred combinations of the **DCK** (deck) and **SID** (sources) 
 flags that indicate the origin of the data. 
-Typically, **DCK** indicates the **type of data** 
+Typically, **DCK** indicates the type of data 
 (e.g. US Navy ships; Japanese Whaling Fleet) and **SID** provides more information
  about the data system or format 
  (e.g. data stream extracted from the WMO global telecommunications systems, GIS). 
@@ -37,12 +37,9 @@ likely to have different formats, precision, conversions and metadata.
 
 *  Planned redundancy, for example the ingestion of several near real time data streams. 
 
-The processing software used by ICOADS (https://icoads.noaa.gov/software/) is written in FORTRAN and includes code to translate software to the IMMA1 format [Smith. *et al.,* (2016)], to apply QC and flags, and to identify (and in earlier releases remove) reports likely to be duplicates [Freeman. *et al.,* (2017)](https://doi.org/10.1002/joc.4775). 
+The processing software used by ICOADS (https://icoads.noaa.gov/software/) is written in FORTRAN and includes code to translate software to the IMMA1 format [Smith. *et al.,* (2016)](https://icoads.noaa.gov/e-doc/imma/R3.0-imma1_short.pdf), to apply QC and flags, and to identify (and in earlier releases remove) reports likely to be duplicates [Freeman. *et al.,* (2017)](https://doi.org/10.1002/joc.4775). 
 
-The code in this repository offer additional quality control
-on the data, duplicate identification and linking of IDs between each pair of duplicate reports. 
-It also provides an identification of the best duplicate by assessing the track 
-(path in lat/lon) of the observation. 
+The code in this repository offers additional quality control on the data, homogenisation of ID information between different **DCK** and **SID** and duplicate identification (DI) preserving information on reports associated by the DI through the use of ICOADS unique identifiers (**UID**). 
 
 References
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