This R package was created to provide a set of tools for those working in Statistical Disclosure Control The functions will help the user keep track of tables created from a single dataset and create risk profiles for each table with regards to the disclosure vector of table differencing. The tool is designed to be used from within an R project, where the data logged is kept across sessions in the .RDATA file.

User Functions

init_project()

    Function: Creates the initial tibbles that will contain the metadata.
    Param: No Input
    Output: Two tibbles: tables_metadata and dataset_metadata

create_dataset_meta(filename,filepath)

    Function: Creates CSV file containing Dataset Metadata
    Param: filename,string - the dataset filename
    Param: filepath,string, - dataset path (default: `./datasets/')
    Output: A single CSV file with the same name as filename but with `meta' appended.

add_newdataset(filenames,filepath)

    Function: Adds datasets metadata to datasets_metadata tibble
    Param: filenames,vector - a vector containing the metadata filenames as strings
    Param: filepath,string - (default: ./datasets/)
    Output: Modifies datasets_metadata

remove_dataset(datasets)

    Function: Removes a dataset from datasets_metadata
    Param: datasets,vector - a vector containing dataset names as strings
    Output: Modifies datasets_metadata

add_newtable(filenames,filepath)

    Function: Adds table metadata to tables_metadata tibble
    Param: filenames,vector - a vector containing the metadata filenames as strings
    Param: filepath,string - (default: ./tables_metadata/)
    Output: Modifies tables_metadata

remove_table(tables)

    Function: Removes a table from tables_metadata
    Param: tables,vector - a vector containing table names as strings
    Output: Modifies tables_metadata

report_tablesRisk()

    Function: Produces a full report on tables vs variables and breakdowns risk
    Param: include, vector - modifies network to display only those variables in include
    Param: exclude, vector - modifies network to not display those variables in exclude
    Param: colours, vector - modifies default colour scheme (`black',`black',`black',`red',`red')
    Output: Prints to Console and creates network visualisation

report_table(table)

    Function: Produces same console report as report_tablesRisk() but has a reduced network based on table
    Param: table, string - table name
    Output: Prints to Console and creates network visualisation

report_na(metadata)

    Function: Reports if there are any NA values in the metadata
    Param: metadata, tibble - target metadata to report on
    Output: Prints report to console

report_variablesrisk()

    Function: Produces a report categorising the variables in use by their risk level
    Param: None
    Output: Prints report to console

report_full(outfile)

    Function: Produces a full study report file based on an Rmarkdown template
    Param: outfile, string - name of the output file
    Output: HTML file

Internal Functions

reset_matrix(metadata,node_column,filler

    Function: Creates a square matrix for building network object
    Param: metadata,tibble - the target metadata
    Param: node_column,integer - which column in metadata should be used as the row/column labels
    Param: filler,string or integer - value which will fill the matrix.
    Output: Returns matrix object

adjmatrix_complete(metadata,edge_column,node_column,include,exclude,colours)

    Function: Create Adjacency Matrix
    Param: metadata,tibble - the target metadata
    Param: edge_column,integer - which column in metadata should be used as the network edge information
    Param: node_column,integer - which column in metadata should be used as the row/column labels
    Param: include,vector - list of values to include from the edge_column
    Param: exclude,vector - list of values to exclude from the edge_column
    Param: colours,vector - list of 5 colours as strings representing Risk level of variable
    Output: Returns a list of two matrices, an adjacency matrix for creating a network and an equivalent matrix for labelling the edges.

adjmatrix_singletable_impact(M,table)

    Function: Create Adjacency Matrix with edges only connecting to table
    Param: table,string - the table to target
    Output: Adjacency Matrix

labelled_graph(M_edges,M_labels)

    Function: Draws a labelled network
    Param: M_edges,matrix - the adjacency matrix for the network
    Param: M_labels,matrix - the equivalent matrix with edge labels
    Output: Draws Network