Introduction
The data standards described in this document define an ‘acceptable standard’ of data for each marine assurance entity type. If a data record complies with the conditions and utilises the format defined; it is said to meet the data standard and, as a result, will maximise the utility of the data.
The standards are produced in such a way as to determine “what is the minimum amount of data required to record an entity of each type?”.
For example: “what is the minimum amount of data required to say that the data we are recording represents a vessel?” This is then considered the minimum data volume and quality level required to meet the data standard, with additional fields defined on top of this to provide a unified format in which additional data should be recorded.
The OMarine data standards are defined in two sections as explained below.
Data Standards
The data standards define the data type and format to be recorded for each
entity. This is the set of standards that must be followed when recording marine
assurance data. This includes a data model diagram identifying relationships
that should exist between different marine assurance entities for which a data
standard has been defined- and a complete set of data standards- one for each
marine entity type. Each individual standard includes:
- A definition or description of the entity whose data is to be recorded in
accordance with the standard. - If required; a breakdown of the relationships between sub entities within
each standard. - A breakdown of fields (a piece of data describing a certain element of an
entity) to include within the entity. For every data standard, there are
compulsory and optional fields- this is determined by the ‘Nullability’
information and the ‘Conditions’ within each field definition. Compulsory
fields must be completed for the data record to meet the standard, whereas
optional fields determine how the data should be recorded if it is
available. Other fields (without a format defined within OMarine) can also
be recorded against an entity- the fields defined are determined to be
common across marine data. Each field will be defined using the following
format.
Field ID Field name
Data type List of possible values
A description of what data to record in this field- this includes any useful notes that will aid the recording process.
Conditions applied to this field (for example; limitations placed upon the value).
- If the field is of ‘TABLE’ type, the sub-fields that go within the table will be stated and explained here.
Element ‘Data type’- as included in each field definition- defines the format and type of values that can be recorded against the corresponding field. For each field definition, the ‘data type’ element must take one of the values
described in the table below.
| FLOAT | A floating-point number (one which contains a floating decimal point). |
|---|---|
| INT | A whole number (not a fraction) that can be positive, negative or zero. |
| STRING | A set of alpha-numerical items in a string. The items in the string can be a letter, number, space, piece of punctuation or space. |
| LOOKUP | An item of any type that is contained in a set of potential values (a value dictionary). |
| TABLE | A table containing several elements corresponding to multiple fields. |
| LIST | A set of values (of any type) that are all responses to the same field for a single element within the dataset. |
| DATE | A date representing the calendar date on which an event occurred. |
| DATETIME | A combination of the date and time value representing a given point in time. |
| BOOLEAN | A Boolean value- data that can only take one of two values (True or False). |
Data Dictionaries
A data dictionary contains a set of possible values to describe a certain activity, item or action in the marine assurance industry. These are used when an attribute can only take one of a finite number of values.
In many of the data standards, fields will be of data type ‘LOOKUP ITEM’ and will refer to a dictionary. This indicates that the value recorded in the field must be included in the dictionary- the value that best describes the field attribute for the entity being recorded.
Using the data dictionaries is a preference within the data standards, however; the standards will still be met if fields requiring LOOKUP ITEM data types are instead filled using CHAR values. This ensures that all users of the data standards can record data at a maximum level of accuracy