Morph-KGC is an engine that constructs RDF knowledge graphs from heterogeneous data sources with the R2RML and RML mapping languages. Morph-KGC is built on top of pandas and it leverages mapping partitions to significantly reduce execution times and memory consumption for large data sources.

Morph-KGC is an engine that constructs RDF knowledge graphs from heterogeneous data sources with the R2RML and RML mapping languages. Morph-KGC is built on top of pandas and it leverages mapping partitions to significantly reduce execution times and memory consumption for large data sources. User-friendly mappings with YARRRML.

Morph-KGC is an engine that constructs RDF knowledge graphs from heterogeneous data sources with the R2RML and RML mapping languages. Morph-KGC is feature-rich with support for YARRRML, RML-FNML, RML-star, RML views, Python user-defined functions and more!

Morph-KGC can be used as a library, providing different methods to materialize the RDF or RDF-star knowledge graph. It integrates with RDFLib, Oxigraph and Kafka to easily create and work with knowledge graphs in Python. The methods in the API accept the config as a string or as the path to an INI file. Materialize the knowledge graph to RDFLib.

2025年1月3日 · Morph-KGC is an engine that constructs RDF knowledge graphs from heterogeneous data sources with the R2RML and RML mapping languages. Morph-KGC is built on top of pandas and it leverages mapping partitions to significantly reduce execution times and memory consumption for large data sources.

2024年9月14日 · Morph-KGC 是一个高效的知识图谱构建引擎，能够从异构数据源中生成 RDF 知识图谱。 它支持 R2RML 和 RML 映射语言，并基于 pandas 构建，通过利用 映射分区 技术显著减少了大规模数据源的执行时间和内存消耗。

2024年9月14日 · Morph-KGC 是一个强大的开源引擎，用于从异构数据源构建 RDF（Resource Description Framework）知识图谱。 它支持 R2RML 和 RML 映射语言，能够处理多种数据格式，包括关系数据库、表格文件、层级文件以及内存数据结构。 Morph-KGC 旨在优化大型知识图谱的物化过程，减少执行时间和内存消耗。 2. 项目快速启动. 首先，确保您的环境中已安装 Python。 然后，使用 pip 命令安装 Morph-KGC： 建议使用虚拟环境来安装 Morph-KGC。 创建一个配 …

2024年9月13日 · Morph-KGC是一个强大的引擎,能够从各种异构 数据源 构建RDF和RDF-star知识图谱。 它就像一位精通多国语言的翻译官,能够将不同格式的数据"翻译"成统一的知识图谱语言。

Morph-KGC is an engine that constructs RDF knowledge graphs from heterogeneous data sources with R2RML and RML mapping languages. Morph-KGC is built on top of pandas and it leverages mapping partitions to significantly reduce execution times and memory consumption for large data sources.

Our experimental results show that, compared with state-of-the-art techniques, the use of mapping partitions in Morph-KGC presents the following advantages: (i) it decreases significantly the time required for materialization, (ii) it reduces the maximum peak of memory used, and (iii) it scales to data sizes that other engines are not capable ...