added Erika's edits to blogpost

content/news/data_layers.md

@@ -26,9 +26,9 @@ The Ocean Health Index monitors [10 key goals](https://oceanhealthindex.org/goal
 
 -   **Goal Score:** Each data layer influences the score for one or more goals or subgoals. The calculations used are dependent on the goal and data layer and can be found in the [methods](https://oceanhealthindex.org/images/htmls/Supplement.html#6_Goal_models_and_data).
 
-To really breakdown this process let's look take a look at one of the many data preparation processes utilized in OHI, the mariculture data prep.
+To really breakdown this process let's look take a look at one of the many data preparation processes utilized in OHI: the mariculture data prep.
 
-The mariculture data prep is contained within a single R script: **Mar_dataprep.RMD**. In this script we take two different datasets [FAO Global Aquaculture Production (Quantity)](https://www.fao.org/fishery/statistics-query/en/aquaculture/aquaculture_quantity) and [Monterey Bay Aquarium Seafood Watch Recommendations](https://www.seafoodwatch.org/) and turn them into data layers. This data prep creates three layers: **Mariculture Harvest tonnes**, which has values for how many tonnes of mariculture each region produces each year, **Mariculture sustainability score** which scores how sustainable the mariculture is for each region, and finally the **Genetic escapes** data layer, which quantifies the potential for harmful genetic escapement from mariculture species. Once the data layers have been created, OHI coding infrastructure is used to calculate the scores for each of the goals they affect. Each of these layers impact the scores for different goals. The Mariculture harvest tonnes and Mariculture sustainability score layers impact the Mariculture subgoal. The genetic escapes pressure layer impacts multiple subgoals including livelihoods, economies, fisheries, and species condition.
+The mariculture data prep is contained within a single R script: **Mar_dataprep.RMD**. In this script we take two different datasets ([FAO Global Aquaculture Production (Quantity)](https://www.fao.org/fishery/statistics-query/en/aquaculture/aquaculture_quantity) and [Monterey Bay Aquarium Seafood Watch Recommendations](https://www.seafoodwatch.org/)) and turn them into data layers. This data prep creates three layers: **Mariculture harvest**, which has values for how many tonnes of mariculture each region produces each year; **Mariculture sustainability score** which scores how sustainable the mariculture is for each region; and finally the **Genetic escapes** data layer, which quantifies the potential for harmful genetic escapement from mariculture species. Once the data layers have been created, OHI coding infrastructure is used to calculate the scores for each of the goals they affect. Each of these layers impact the scores for different goals. The Mariculture harvest and Mariculture sustainability score layers impact the Mariculture subgoal. The genetic escapes pressure layer impacts multiple subgoals including Livelihoods, Economies, Fisheries, and Species Condition.
 
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   <iframe seamless src="/images/layers_blog/mar_connections.html" width="1000" height="500" style="margin-left: -150px; margin-right: -500px; margin-top: -20px; border: none;" scrolling="no"></iframe>
@@ -38,7 +38,7 @@ The mariculture data prep is contained within a single R script: **Mar_dataprep.
 
 As OHI fellows we spend a large proportion of our time creating data layers. Data layers are the foundational components used to calculate OHI scores. As a reminder: each data layer is a new data set created from one or more raw data sources.
 
-Now that we have a better idea of what a data layer is, and how they fit into OHI we can explore at all of the data layers to see which goals they affect. Currently there are 108 different data layers included in the OHI framework.
+Now that we have a better idea of what a data layer is, we can take a deeper look at how they fit into the OHI model. Below you'll find an interactive visualization that shows the relationships between all layers included in OHI and the goals that they are incorporated into.
 
 *Click on a goal or data layer icon, or select a goal from the dropdown list to see which data layers impact each goal score. Hover over the goal and data layer icons to see their titles.*