Merge pull request #36 from Protohedgehog/patch-1

Update 06_dataanalysis.srt

subtitlesvideo/06_dataanalysis.srt

@@ -1,70 +1,70 @@
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-Research is a long process that relies on research data.
+Research is a long process that often relies on data.
 
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-Data is collected, documented, processed,
+Data are collected, documented, processed,
 
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-preserved, shared, and archived,
+preserved, shared, and archived.
 
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-It is a long, fastidious, sometimes repetitive work.
+It is a long, intricate, and sometimes repetitive work process.
 
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 But all of it is necessary for climbing the research ladder,
 
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-getting to the final door before the results:
+and getting to the last step to the results:
 
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-The data analysis.
+the data analysis.
 
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-But analysis fails with data lacking quality.
+But analyses will fail with data that lacks high quality.
 
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-The research may tumble. The problems causing failure
+The research may tumble. The errors that produce problems 
 
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-are often born during the project youth.
+are often born during the early stage of a project.
 
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-Research is providing a large amount of valuable data, but,
+Research provides a large amount of valuable data, but,
 
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-even when the data is easy to retrieve,
+even when the data are easy for us to retrieve,
 
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 small problems in its processing
 
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-can impact tremendously the operability of the data.
+can have a tremendous impact on the operability of the data.
 
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 Problems which are marginal issues at the start
 
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-steadily assumes more importance
+steadily gain more importance.
 
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-The data is there, but it cannot be used or analyzed.
+The data are there, but they cannot be used or analyzed properly.
 
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@@ -76,11 +76,11 @@ In the end, in order to save the project,
 
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-the data needs to be decomposed or cleaned,
+the data need to be decomposed or cleaned,
 
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-a process which is difficult, sometimes dangerous,
+a process which is often difficult, sometimes dangerous,
 
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@@ -96,11 +96,11 @@ one can best choose how the data should be collected
 
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-such that the data ends in its most well fitted position.
+such that the data ends in its optimal position.
 
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-While surprises are always expected,
+While surprises can always be expected,
 
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@@ -116,7 +116,7 @@ But even more important than the data,
 
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-its documentation must be designed and filled cautiously
+is its documentation, which must be cautiously designed and entered
 
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@@ -140,15 +140,15 @@ It is easy to underestimate the problem,
 
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-it is tempting to think one will craft something later.
+and it is tempting to think you will craft something later.
 
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 But "later" might become "too late".
 
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-Sometimes the data must be re-evaluated completely.
+There is a risk of total data loss.
 
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@@ -160,30 +160,29 @@ the data can be saved.
 
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-But counting on luck is not very sound, is it?
+But sometimes, the data must be evaluated or collected again.
 
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-Instead, start early with your research data management:
+Because you do not want to build from scratch: 
 
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-Write a plan, document every step, produce tidy datasets:
+Write a plan, document every step, produce tidy datasets,
 
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-Be clever and your data will be easy to analyze
+Be clever and your data will be easy to analyze,
 
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-and share.
+share, and re-use.
 
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-Learn more about data formats, structures, and documentation, 
- seek for help at a Research Data Management Helpdesk or online !
+To learn more about data formats, structures, and documentation, look for help at a Research Data Management Helpdesk or online!
 
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-In our next episode, we will learn more about research data managers, stay tuned !
+In our next episode, we will learn more about research data managers, stay tuned!