Types of datafields
Last updated
Last updated
Datafield | Details |
Text datafields allow you to fill out general text, such as a party’s name and address, the applicable law, etc.When creating conditions, text datafields are useful to differentiate between two or more separate and distinct options. For example: say you want to align applicable law and competent court for three jurisdictions (France, Belgium and the Netherlands). Such a condition could look like this:
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List of texts allow you to list separate and sometimes cumulative strings of text. For example: say you create a clause surrounding contractually obligated insurance coverage by one party. You may choose to incorporate the option to select multiple kinds of coverage (e.g.: product liability, personal injury, property damage, etc.). Choosing one does not rule out the other, so you want to be able to create a list out of them.One useful application for conditions surrounding lists of texts is the occurrence of optional clauses. Using optional clauses allows you to effectively create a type of “menu” from which your users can select the clauses they need. This works by creating list of texts-based conditions in the “enabled?” menu of a clause. For example:
Note that the shape of the condition is different than the traditional text datafield-based condition. This is because this list of texts-based condition essentially asks “Is confidentiality included in the optional clauses list?”, whereas traditional text datafield-based conditions would ask “Is the answer to the question ‘which optional clauses are included’ equal to confidentiality? Obviously, the latter is not desirable, since the whole idea of a list of optional clauses is that more than one answer can be true. | |
Number datafields allow you to fill out general numbers like amount of m², amount of shares, number of weekly working hours for an employee, etc.The primary benefit that number datafields have over text datafields (which can also contain numbers) is that you can use them for mathematical equations. For example, say that you want to automatically calculate the price per m² of leased office space. That calculation could look like this:
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Floating punt numbers are essentially number datafields that also allow you to fill out decimals. They are therefore ideal for more precise numbers such as interest rates and other percentages. | |
True / false datafields allow you to make a distinction between two mutually exclusive options and are therefore exclusively used for conditions. For example: differentiating between an exclusive or a non-exclusive relationship between the parties, indicating whether the seller is a legal or a natural person and any question to which the answer is either “yes” or “no”.These datafields are often used in the “enabled?” tab of a clause, as the application thereof often depends on a yes-or-no-question. For example: a clause detailing the conditions precedent of the agreement could optionally be included if the condition thereto is triggered. This condition could look like this
or perhaps like this:
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Currency datafields are essentially number datafields for sums of money. They act in the exact same way as number datafields would, meaning that you can also use them in mathematical equations, but you can also designate the applicable currency such as EUR, USD, GBP and JPY. | |
Duration datafields allow you to set out fill out a period of time, in particular a number of days, weeks, months, quarters or years. In that respect, they are ideal for things such as the duration of the agreement, notice periods, and terms within which certain actions need to be undertaken by a party.Like (floating point) number and currency datafields, duration datafields allow you to make certain calculations. Say you want to calculate the end date of the agreement based on the commencement date and subsequent duration. That calculation could look like this:
In this example, the “commencement-date” datafield is a date datafield and the “duration” datafield is a duration datafield. The brackets are added to assist Clause9 in maintaining the proper order of operations. | |
Date datafields, as the name suggests, are datafields that allow you to fill out a date. These datafields are handy for easily filling out such things as commencement dates, end dates, signature dates, etc. by allowing users to select the date from a pop-up calendar when they interact with the datafield.Date datafields can also be used in calculations, as shown above. | |
Repeating list datafields are advanced datafields that allow you to repeat all the different kinds of datafields mentioned above so that you can repeat clauses or even documents on the basis of this input. They are ideal for when you want to give users the option to determine not only certain information of parties, products, services, etc. but also the number thereof. Examples include:
When used in conditions, repeating list datafields act as any of the above datafields that they have been linked to. In this way, you can have repeating list text datafields, repeating list number datafields,repeating list duration datafields, etc.Repeating list datafields are subject to a number of extra considerations that do not apply to other datafields (e.g.: they must be interacted with in the datafields tab of the operations panel and can only be included in Q&A by way of a table meaning they won’t show up in the batch create panel). |
It is currently not possible to change the type of datafield once it has been created.
If you need to change the type of datafield afterwards, your best option is to delete the datafield and add a new one with the same name. (Be aware, however, that questions in Q&As will then loose their connection to the deleted datafield. Before deleting the datafield, you may want to check the usage of the datafield by going to Browse Files, clicking on the Other Actions button and choosing the relevant datafield under submenu show datafield usage).
