This is a glossary of terms used in the SEAD Shape Shifter User Guide
Jump straight to a given term:
Columns
Columns define the individual data fields within a table. Each column holds one specific attribute (for example, a site name, a date, or a measurement value), and every row in the table provides a value for that attribute. Columns also determine the data type and meaning of the information stored, which allows Shape Shifter to validate, filter, and map data correctly during transformations.
Data Sources
This refers to the specific datasets that are being mapped to SEAD, and to SEAD itself. To use SEAD Shape Shifter the data source needs to be uploaded
dispatch
This is the final step, once all mapping and data transformations are done. Do this only when you are 100% happy with the result from Execute, ideally that you have also checked your work with one of the SEAD database team
Entities
In a database, such as SEAD, entities are the main types of things that your data describes. Each entity represents a real‑world concept—such as a site, sample, analysis, taxon, measurement—and has its own set of properties (fields) that describe it.
Execute:
run all of the defined processes ann export the result. If you export to a spreadsheet use the one whose name isn’t pandas, as it will be a prettier result. It is ok to execute often to check your work and be certain that it is doing what you think it is doing
Graph
The SEAD Shape Shifter Graph is a graphical illustration of the mapped connections between two Data Sources
Mapping
The act of determining and recording which types of data in one Data Sources are equivalent to which types of data in another.
Metadata
This is the data about the data. It includes information such as the name of the dataset, the owner(s)/author(s) of the dataset, the categories of information (tables) and the specific types (columns) of information in the dataset.
Materalize
Takes the rules that you established in the Basic tab and runs them, and then freezes the result for the current table. If you weren’t ready for this step. After it has been matteralized it becomes a “fixed” form. You can manually add information here, for example, if the location already exists in SEAD, you can type in the SEAD_id for that location. Note: if you unmateralize the entity, such manually entered changes will be lost
Project
A SEAD Shape Shifter project is where you define your dataset and map your data to the SEAD Database. There are a variety of interface windows for all stages of the process including defining the data sources and entities, doing the mapping and checking the results either visually (as a graph) or through validation tests.
SEAD
The Strategic Environmental Archaeology Database (SEAD) is a national research infrastructure for environmental archaeology data developed and managed at the Environmental Archaeology Lab (MAL) in collaboration with Humlab at Umeå University, Sweden. SEAD is part of an international network of research infrastructures for environmental archaeology and Quaternary paleoecology, enabling collaboration and data sharing among researchers worldwide. Its mission is to provide online tools to support research in environmental archaeology and to promote online access of relevant datasets. The system grants the online storage, extraction, analysis, and visualisation of data on past climates, environments, and human impacts
SEAD Shape Shifter
SEAD Shape Shifter is a tool for transforming and normalising data in preparation for inclusion in SEAD, and for Mapping new Data Sources to SEAD’s database structure. This User Guide is dedicated to explaining this tool.
Tables
Tables combine categories of data within a Data Source (such as location information) and are comprised of a set of Columns containing the various data fields for that category of data.
Validation
Validation is the process of checking that incoming data is complete, correctly formatted, and consistent with the rules and structures of the SEAD database. It ensures that values match expected data types, required fields are present, and references between tables are valid, so that transformed datasets can be safely imported into SEAD without errors.
YAML
A YAML configuration is a small text file that tells Shape Shifter how to interpret and transform your data, using a very readable, plain‑text format to record the information necessary to understand your data set, such as “This column contains dates”, “This column is the sample ID”, and “When you see this value, map it to this SEAD field”. These files require correct syntax to function. Shape Shifter creates these files, with the correct syntax, automatically from the data entered in the various project dialogue boxes. Any edits to the YAML configuration from the YALM window will also be reflected in the corresponding project dialogue boxes.