1.4.3.201

2020-08-28

• AWS Marketplace compatibility

• The Lens can now accept new Custom Functions via an endpoint

1.3.3.153

2020-05-15

• SFLENS-126: Fix Docker image security vulnerabilities as seen in ECR

• SFLENS-118: Fixed persistent Kafka logging

1.2.2.137

2020-03-17

• SFLENS-104: Enhancements have been made to CSV transformation in order to more elegantly handle CSV files containing errors.

• SFLENS-107: It is now possible to choose which provenance activities are generated for your transformed data.

• SFLENS-112: Dead Letter Queue messages are now much richer, and include additional information in JSON format, to more easily facilitate consumption by an external process.

• SFLENS-113: Update the POM to use our latest custom RMLMapper which prevents erroneous IRI encoding

1.1.0.102

2020/03/03

• SFLENS-102: Added support for the following new mapping functions:

  • retrieveValueFromDelimitedListTests

  • extractCharactersFromStartTest

  • extractCharactersFromEndTest

• SFLENS-106: Fixed a problem which could cause large CSV files to be iterated over incorrectly.

1.0.0.93

2020/02/03

This is the first official release of the Structured File Lens.

It is a highly configurable pipeline component, which will transform structured content into a Knowledge Graph compatible output.

• Highly configurable transformation from structured content, to RDF.

• Supplied as a Docker Container, available from DockerHub.

• Supports the following input file formats:

  • XML

  • JSON

  • CSV

• Supports the following output file formats:

  • NQuads

  • JSON-LD

• Capable of iteratively transforming input files of any file size.

• May be triggered via Message bus, or directly via RESTful endpoint.

• Input / Output files may be accessed from on-premise, or cloud locations.

• Provenance as standard.