Import Excel

Take a lender’s list or an object list from Excel into Moliri. The import writes into fields that already exist. It does not create fields. Files in .xlsx and .xls format are accepted. Open a CSV file in Excel first and save it as .xlsx.

Prepare the spreadsheet. One header row with column names, below it one row per object. Dimensions are best already given in the unit of the target field (see below).
Open the import. Sidebar, Data In- & Export tab, section Import, Excel. Choose the file.
Check the range. Moliri detects the sheet, the column range and the header row and shows the result under Detected:. If there are title rows above the table, or several tables on one sheet, correct the details and click Re-read.
Map the columns. Moliri maps the columns itself, based on the headings. Each column carries a mark: sure (exact name match or chosen by you), check (fuzzy suggestion), open (no target field, not imported). Take a look at the columns marked check and open.

For this, Moliri reads the content of the columns. Below a column without a target field you may then see Suggested by content: Datierung (dating); Apply sets the field. If the content does not fit the chosen field, such as 88 cm in a number field, the column warns you with an example. More on this under Content of the columns .

If field search is switched on in your profile, Moliri also reads the meaning of the column headers. Below an English column such as Object description you then see, for example, Suggested by the column header: Objektbeschreibung.
Choose mode and options. Under Mode and options:

Mode Effect

New objects Each row creates a new object
Fill in Fills gaps in existing objects. Existing values stay
Overwrite Replaces existing values. Empty cells are ignored

With Fill in and Overwrite you also choose how a row finds its object: a spreadsheet column that corresponds to a field in the object, usually the inventory number. This column carries the mark match key. If Moliri recognises a column with inventory numbers, it offers Use as mapping column for it.
Read the preview and the footer. To the right of each column, the preview shows what becomes of the cells. Values that cannot be assigned to any entry carry the mark to resolve. If rows break the conditions of the fields, such as a missing required value or an inventory number that already exists, this is shown above the preview. Before you start, the footer tells you how many columns are mapped, how many objects will be created or matched, how many cells are still to be resolved and how many rows break conditions.
Import. The button states the number of values. The import keeps running in the background, even if you close the window. Afterwards Moliri checks the new and changed objects against the field conditions. If one breaks them, the window stays open with the report; everything has been written all the same.
Resolve parked values. If the import parked values, the closing message offers Resolve (n). This opens Resolve references .

Mode	Effect
New objects	Each row creates a new object
Fill in	Fills gaps in existing objects. Existing values stay
Overwrite	Replaces existing values. Empty cells are ignored

What happens to unclear values

Moliri writes nothing unclear into a field with a fixed set of values. Instead the import parks the value, and the field stays empty until someone has decided.

Target field	Written directly	Parked
Authority record, address, geolocation, file	An identifier held by exactly one record (such as a GND number)	Names and everything else
Switch	yes, no, x, TRUE, 1, 0 and similar	Anything that cannot be read unambiguously, including a single dash
Select list, selection tree	Values from the field’s list of values	Values not on that list, unless the field allows its own values
JSON	Valid JSON, also after a small repair; text under a chosen label or in chosen keys; text that the field’s cleanup turns into JSON	Other text
Link (authority data, addresses, files, objects)	Values with exactly one target	Values with no target or several

The rest goes in as it stands in the cell. Dates are brought into Moliri’s date format. How JSON fields and links are filled in detail is described in the reference under JSON targets and Links .

Columns into parts of a JSON field

A JSON field such as Production has several parts per entry, for example place and date. If these are in separate columns of the spreadsheet, choose under Keys at each column which part it fills. The columns of one field together make one entry per row. If the columns are already called Production place and Production date, both are preset. A part that is the same for every row is entered at the first column under Fixed. If the field allows several entries, Append decides whether the entry is added next to the existing ones or replaces them.

For a multilingual title, choose the Label instead, for example de. If the setup has stored an import label for the field, it is already selected.

Dimensions and units

A number is taken over without conversion. If the height is given in metres in the spreadsheet but the field works in centimetres, 1.2 ends up in the object as 1.2 cm. Convert the column in Excel beforehand, or after the import with bulk edit (Multiply by 100).

Options

Option	Effect
Log original values	When a value changes, the old value is appended to the field’s comment. Default: on
Pin objects	The affected objects are pinned after the import. Default: on
New objects	Rows that cannot be matched to an object create a new object (with Fill in and Overwrite)
Empty cells	Empty cells are imported too and can clear existing values (only with Overwrite)
Merge	New values are appended to existing ones (text fields only)
Import images	Images from the Excel file are assigned to the object of their row. If an image field is mapped to the column, they are placed there, for example as the title image
Import colors	Cell colours become the colour marking of the field
Import comments	Cell comments are appended to the field’s comment

With the first two options, an import into an established collection stays easy to check: the affected objects are pinned at the top afterwards (pinned only shows exactly these), and every changed field has what stood there before in its comment.

Reshaping columns

Not every list fits as it arrives. The column mapping offers three tools for this:

Tool	What for
Function per column	Reshape a cell before the import, for example take the GND number from a neighbouring column. The effect shows in the preview straight away
duplicate	Map the same column a second time to import it into another field
Several columns into one field	First name and surname become one value. Order and joining are adjustable

Saved functions are kept in the Import functions library, which is maintained in the setup area.

For common cases Moliri brings its own functions and suggests them below the column, for example Import function: Split dimensions into Höhe, Breite for a column containing 56x74cm, or Dating → from/to for um 1910 (around 1910) and 18. Jh. (18th century). A click on Apply sets the function and creates the copies of the column for the number fields. Which functions there are and what they read is listed in the reference .

After the import

Switch to pinned only.
In the table , add the imported fields as columns.
Group by each imported field. Typos and outliers stand out that way.
Resolve parked values under Resolve references .

If the import broke conditions, the report leads to each affected object. After you click an object, it stays available under Import report (n) on the Data In- & Export tab until the next import. The same objects are found later on the Check tab under Field conditions.

The whole import is listed in the history under Batch operations and can be undone there as a whole.