There are several ways for you to analyse and share your own data with Aleph. How best to do it is dependent on the type of data you are attempting to add and how frequently you would like to update it.
Personal datasets are contained workspaces within Aleph where you can upload, edit, and organize data related to an investigation or topic of interest.
The most common type of data to import into Aleph is files, such as PDFs, E-Mail, or Word documents. Uploading them will make it easy to search them even if their text is hidden in images, and you can share them with your colleagues.
1. Create a personal dataset using the user interface.
2. Then upload your documents using the upload function inside that dataset.
You can share this personal dataset with colleagues who have accounts on the site and groups of users, but it cannot be made public.
If you plan to regularly import data from a public source, such as a government web site, you may want to create a web crawler that automatically executes, collects data and submits them to Aleph.
When importing a list of companies, people or similar data objects, it is helpful to convert your raw data into structured entities that Aleph can use to classify those entities for searching, cross-referencing, and many other operations.
1. Follow the "Importing documents and files" steps above to import your .csv, .xls, or .xlsx data file to a personal dataset.
2. Once the data file has finished uploading, browse to one of the tables you have uploaded. Click the "Generate Entities" tab to open the mapping editor.
3. Select the types of entities you would like to create from your data
4. Define any relationships - such as ownership or family relations - that exist between the entities.
5. Select columns from your data to use as unique keys for each entity.
Keys are usually ID numbers, email addresses, telephone numbers, or other properties of your data which are guaranteed to be unique. The more columns you are able to select as keys, the better, to ensure that Aleph correctly generates an entity for each unique entry in your data.
6. Assign data columns to properties of the entity types you have selected.
7. Add any fixed values to the entities. If, for instance, your data is a company registry from Moldova, it would be useful to set the "Country" property to "Moldova", so that all company entities that are generated will automatically have their country set as Moldova.
8. Verify and submit your mapping