Processes constitute the core of the toolkit. Processes are “connecting” or “working” on data . Processes are e.g. adding, altering, or deleting data.
Create is the process of creating or keep adding data to existing data sets. This can be files that are added, or data that is added to a database, spreadsheet or similar. Data can be created by tools, sensors, manual entry of data etc.
Deleting data is the process of removing entire or substantial parts of a data set.
Copy will create another separate instance of your data as an identical copy.
When you discard data, you do not delete the entire content (e.g. files or records) but you remove/omit part of the information within the data. An example is when you remove a column or some rows from an Excel spreadsheet.
Converting data concerns the process changing files from one file format to another. The process is often applied when either software or systems have the need for specific file formats, or to apply some kind of compression to data.
Merge is the process of bringing together two different data sets into one by merging them, often by a common key. E.g. when joining statistical data from multiple sources to create a new joint data set.
Import can be compared to the copy process, except that the import process is meant to be applied when you get data from external sources. This can be e.g. data sets that are downloaded from various sources of data, handed over by external parties etc.
Edit / alter can be used for actions where you make changes to data, e.g. overwriting or altering a value in a spreadsheet, make changes to an image.
Moving is data is about moving files from one location to another. This can be done across systems, e.g. from a laptop to a USB pen, or to another location within the same system.
Processing is the action of applying e.g. algorithms or similar to data, e.g. looking for patterns in images, analyzing gene sequences, text analysis etc.
Export is used when you extract information from one data set to another, often omitting information, change file formats etc. in the same process. E.g. various software allow you to export your data in various formats and apply filters.
Synchronization of data keeps two data sets alike. It can be compared to an automatic copy procedure.
Upload is an action where you use a web browser, ftp client, or similar to copy a file to a remote system.
When you query a data source, you access data using some kind of application programming interface (API) to a given data source. E.g. you can make structured requests for e.g. Wikipedia through the Wikidata service.
When you pseudonymize data, you substitute one or more values with non-identifiable keys. However, contrary to anonymization you store the mapping between keys and original values away from the data themselves. Pseudonymization makes it possible to reverse the process, if you hold both the mapping table and the pseudonymized data set.
When you anonymize data, you remove or change enough information in a data set to ensure that no single – or a combination – of values can be used to identify a person. This is useful when you need to share data, but do not have consent for sharing the identity.