Cleaned up guides references to download, explore, compute, configure…

… btns [ref #7081]

doc/sphinx-guides/source/developers/geospatial.rst

@@ -183,10 +183,10 @@ Saving Join Target Information to Geoconnect Database
 
 The ``get_latest_jointarget_information()`` in ``utils.py`` retrieves recent JoinTarget Information from the database. (See the `utils code in GitHub <https://github.com/IQSS/geoconnect/blob/master/gc_apps/worldmap_connect/utils.py#L16>`_.)
 
-Setting Up WorldMap Test Data
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Setting Up WorldMap Sample Data
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-For the dataset page, this script gives a query to add test WorldMap map data. After the query is run, the "Explore Map" button should appear for a tabular file or shapefile. In the example SQL queries below, substitute ``$DATASET_ID`` and ``$DATAFILE_ID`` with the appropriate ID's.
+This script gives a query to add sample WorldMap map data to your dataset. After the query is run, the WorldMap explore tool option should appear for the sample tabular file or shapefile. In the example SQL queries below, substitute ``$DATASET_ID`` and ``$DATAFILE_ID`` with the appropriate ID's.
 
 To add sample map data for a tabular file:
 

doc/sphinx-guides/source/installation/config.rst

@@ -348,15 +348,15 @@ Once you have set up ``:ComputeBaseUrl`` properly in both Dataverse and your clo
 - Compute on multiple datasets
 - Compute on a single datafile
 
-The compute buttons on dataset and file pages will link validated users to your computing environment. If a user is computing on one dataset, the compute button will redirect to:
+The compute tool options on dataset and file pages will link validated users to your computing environment. If a user is computing on one dataset, the compute tool option will redirect to:
 
 ``:ComputeBaseUrl?datasetPersistentId``
 
-If a user is computing on multiple datasets, the compute button will redirect to:
+If a user is computing on multiple datasets, the compute tool option will redirect to:
 
 ``:ComputeBaseUrl/multiparty?datasetPersistentId&anotherDatasetPersistentId&anotherDatasetPersistentId&...``
 
-If a user is computing on a single file, depending on the configuration of your installation, the compute button will either redirect to:
+If a user is computing on a single file, depending on the configuration of your installation, the compute tool option will either redirect to:
 
 ``:ComputeBaseUrl?datasetPersistentId=yourObject``
 

doc/sphinx-guides/source/user/find-use-data.rst

@@ -102,9 +102,9 @@ If you want to download all files in a dataset, you can click the Access Dataset
 
 If you'd like to download a single file or some subset of the dataset's files, you can use the Files tab. To download more than one file at a time, select the files you would like to download and then click the Download button above the files. The dataset's files will download in .zip format and will preserve any folder structure that the dataset owner had set up.
 
-You may also download a file from its file page by clicking the Download button in the upper right corner of the page, or by :ref:`url_download` under the Metadata tab on the lower half of the page.
+You may also download a file from the Access File button on its file page or by :ref:`url_download` under the Metadata tab.
 
-Tabular data files offer additional options: You can explore using any data exploration or visualization :doc:`/admin/external-tools` (if they have been enabled) by clicking the Explore button, or choose from a number of tabular-data-specific download options available as a dropdown under the Download button.
+Tabular data files offer additional options: You can explore using any data exploration or visualization :doc:`/admin/external-tools` (if they have been enabled), or choose from a number of tabular-data-specific download options available.
 
 Tabular Data
 ^^^^^^^^^^^^
@@ -144,7 +144,7 @@ rsync is typically used for synchronizing files and directories between two diff
 
 rsync-enabled Dataverse installations offer a new file download process that differs from traditional browser-based downloading. Instead of multiple files, each dataset uploaded via rsync contains a single "Dataverse Package". When you download this package you will receive a folder that contains all files from the dataset, arranged in the exact folder structure in which they were originally uploaded.
 
-In a dataset containing a Dataverse Package, the information to download and/or access is in two places. You can find it on the **dataset page** under the **Files** tab, and on the **file page** under the **Data Access** tab. If the data is locally available to you (on a shared drive, for example) you will find the folder path to access the data locally. To download, use one of the rsync commands provided. There may be multiple commands, each corresponding to a different mirror that hosts the Dataverse Package. Go outside your browser and open a terminal (AKA command line) window on your computer. Use the terminal to run the command that corresponds with the mirror of your choice. It’s usually best to choose the mirror that is geographically closest to you. Running this command will initiate the download process.
+In a dataset containing a Dataverse Package, the information to download and/or access is in outlined the **Data Access** listed under the Access File button. If the data is locally available to you (on a shared drive, for example) you will find the folder path to access the data locally. To download, use one of the rsync commands provided. There may be multiple commands, each corresponding to a different mirror that hosts the Dataverse Package. Go outside your browser and open a terminal (AKA command line) window on your computer. Use the terminal to run the command that corresponds with the mirror of your choice. It’s usually best to choose the mirror that is geographically closest to you. Running this command will initiate the download process.
 
 After you've downloaded the Dataverse Package, you may want to double-check that your download went perfectly. Under **Verify Data**, you'll find a command that you can run in your terminal that will initiate a checksum to ensure that the data you downloaded matches the data in Dataverse precisely. This way, you can ensure the integrity of the data you're working with. 
 

doc/sphinx-guides/source/user/tabulardataingest/csv tsv.rst → doc/sphinx-guides/source/user/tabulardataingest/csv-tsv.rst

@@ -4,7 +4,7 @@ CSV/TSV
 .. contents:: |toctitle|
 	:local:
 
-Ingest of Comma-Separated Values and Tab-Separated Values files as tabular data. 
+Ingest of Comma-Separated Values and Tab-Separated Values files as tabular data
 --------------------------------------------------------------------------------
 
 Dataverse will make an attempt to turn CSV and TSV files uploaded by the user into tabular data, using the `Apache CSV parser <https://commons.apache.org/proper/commons-csv/>`_. 
@@ -37,7 +37,6 @@ are recognized as a **single** row with **5** comma-separated values (cells):
 
 (where ``\n`` is a new line character)
 
-
 Limitations
 ------------
 
@@ -48,7 +47,6 @@ Recognized data types and formatting
 
 The application will attempt to recognize numeric, string, and date/time values in the individual columns.
 
-
 For dates, the ``yyyy-MM-dd`` format is recognized. 
 
 For date-time values, the following 2 formats are recognized: 
@@ -73,9 +71,6 @@ In character strings, an empty value (a comma followed by another comma, or the
 
 Any non-Latin characters are allowed in character string values, **as long as the encoding is UTF8**. 
 
-
-**Note:** When the ingest recognizes a CSV or TSV column as a numeric vector, or as a date/time value, this information is reflected and saved in the database as the *data variable metadata*. To inspect that metadata, click on the *Download* button next to a tabular data file, and select *Variable Metadata*. This will export the variable records in the DDI XML format. (Alternatively, this metadata fragment can be downloaded via the Data Access API; for example: ``http://localhost:8080/api/access/datafile/<FILEID>/metadata/ddi``). 
+**Note:** When the ingest recognizes a CSV or TSV column as a numeric vector, or as a date/time value, this information is reflected and saved in the database as the *data variable metadata*. To inspect that metadata, select *Variable Metadata* listed as a download option for the tabular file. This will export the variable records in the DDI XML format. (Alternatively, this metadata fragment can be downloaded via the Data Access API; for example: ``http://localhost:8080/api/access/datafile/<FILEID>/metadata/ddi``). 
 
 The most immediate implication is in the calculation of the UNF signatures for the data vectors, as different normalization rules are applied to numeric, character, and date/time values. (see the :doc:`/developers/unf/index` section for more information). If it is important to you that the UNF checksums of your data are accurately calculated, check that the numeric and date/time columns in your file were recognized as such (as ``type=numeric`` and ``type=character, category=date(time)``, respectively). If, for example, a column that was supposed to be numeric is recognized as a vector of character values (strings), double-check that the formatting of the values is consistent. Remember, a single improperly-formatted value in the column will turn it into a vector of character strings, and result in a different UNF. Fix any formatting errors you find, delete the file from the dataset, and try to ingest it again.
-
-

doc/sphinx-guides/source/user/tabulardataingest/index.rst

@@ -16,4 +16,4 @@ Contents:
    stata
    rdata
    excel
-   csv tsv
+   csv-tsv