Attributes are the “words” in the SampleNavigator database. The same attribute can be part of multiple attribute-sets, like the same word can be used in multiple sentences. With attributes you define the terminology.
At SampleNavigator we use “attributes” and “attribute-sets”.
This is the same concept as tables and fields. Below a comparison to equivalent terminology
When you change the name of an attribute, it is changed everywhere on every attribute and every attribute-set
“Attribute-sets” are a combination of “attributes” that can be attached to documents, to researches, to samples, sample holders, documents and storage. For instance the “attribute-set” “patient data” can contain the “attributes”; “patient number”, “date of birth”, “gender” etc.
You don’t have to define all the attributes first, the user-interface helps you to create new ones on the fly.
Within an attribute-set, you can move the single attributes up and down, to give them the right logical sequence
Like a field in a table, an attribute is of a certain data-type. A data type restricts the possible values. For instance in a DateTime-type you can only store a date and time. You cannot store the value “male” in DateTime-type. In a lookup-type you can only store a limited lists of values. And in a numeric-type only numeric values can be stored.
But there is one important difference. In SampleNavigator it is possible to compare different samples with the same attribute.
You can assign the same attribute to different attribute-sets. It is essential when you want to compare data between different researches. You are sure that the same attribute, with the same list of possible values, is used in different researches.
So, in this case you always have the same structure of data. (date-format for example.) This modern approach is of course far better – from a scientific viewpoint – than an attribute-set per type of research.
With SampleNavigator you cannot only standardize the way you store the samples, but you can also standardize the data that is used.
The use of the same attribute also improves the performance in searches.
There are no practical limitations to the number of attributes, attribute-sets or number of attributes in set, if you want to use one million different attributes in 200.000 tables, you can do it.
However, our advice is to restrict yourself to those attributes that are really useful.
The following data-types can be assigned to an attribute:
- Integer (f.i.107)
- Float (f.i. 107.12)
- Character (f.i. ‘A107’’
- Text (Clear text)
- Date (date-stamp, also possible in combination with time-stamp)
- Time (time-stamp)
- File (a photo or movie)
- URL to the internet or a local file)
- Lookup (create your own pull down menu)
Upon entering data, the systems checks whether the data is entered in the correct pre-defined format. For instance, only insert a “time value” in a time field and only “numeric values” in an integer field.
You can upload a file to the database if the data type is a file. New files are automatically stored in a new record. A new file with the same name becomes a new version of the old file, the old file is not overwritten.
Often you want to restrict the values of the fields. This is done with the “lookup source”. The “lookup source” is just another attribute-set. In this attribute-set you define the values you allow. Those values are used for all researches that contain this “lookup source”, and also for all researches that use this attribute-set.
You can define every lookup value, there is no practical restriction.
One of the nice features of the system is that you can define lookup values in multiple languages, for instance French and English.
Not everything is just a list of values. Often classification systems are hierarchical, SampleNavigator supports this.
Where can you use attributes
You can assign attribute-sets to:
- Documents: for instance attribute-sets for “patient data” or “order data”, kind of “illnesses”.
- Sample Holders: for instance about to define it is a box, a plate or a liquid holder
- Samples: for instance the results of measurements.
- Storage Types: for instance the brand of a freezer, location, temperature range, measured temperature