ILastic: Linked Data Generation Workflow and User Interface for iMinds Scholarly Data

Abstract

Enriching scholarly data with metadata enhances the publications' meaning. Unfortunately, different publishers of overlapping or complementary scholarly data neglect general-purpose solutions for metadata and instead use their own ad-hoc solutions. This leads to duplicate efforts and entails non-negligible implementation and maintenance costs. In this paper, we propose a reusable Linked Data publishing workflow that can be easily adjusted by different data owners to (i) generate and publish Linked Data, and (ii) align scholarly data repositories with enrichments over the publications' content. As a proof-of-concept, the proposed workflow was applied to the iMinds research institute data warehouse, which was aligned with publications' content derived from Ghent University's digital repository. Moreover, we developed a user interface to help lay users with the exploration of the iLastic Linked Data set. Our proposed approach relies on a general-purpose workflow. This way, we manage to reduce the development and maintenance costs and increase the quality of the resulting Linked Data.

EABlock

“…Entity Alignment (EA) is an important solution to overcome interoperability issues while creating a knowledge graph from heterogeneous data sources. Dimou et al [9], Michel et al [18], and Vidal et al [21] propose EA as a pre-processing step, prior to the semantic enrichment and integration of data. In this case, pre-processing performs the task of EA on the whole provided data sources, independent of their involvement in the goal KG.…”

“…Experiments are grouped into six categories, each category utilizing a different 𝐷𝐸, i.e., all the experiments in one category have the same 𝐷𝐸. To avoid any bias caused by the techniques applied in the development of the state-of-the-art engines, we repeat the same experiments by two different available engines 7 https://labs.tib.eu/sdm/biofalcon/ including RocketRML 8 and SDM-RDFizer 9 . Accordingly, the experiments in one category differs in a. the applied RML-compliant engine and b. whether EABlock is used as part of the pipeline or not.…”

Single‐Cell Immunoblotting based on a Photoclick Hydrogel Enables High‐Throughput Screening and Accurate Profiling of Exogenous Gene Expression

“…Cell segmentation was performed using the software Ilastic. [46] CellProfiler [47] was used to quantify the fluorescence intensity in single cells.…”

EABlock: A Declarative Entity Alignment Block for Knowledge Graph Creation Pipelines

“…Entity Alignment (EA) is an important solution to overcome interoperability issues while creating a knowledge graph from heterogeneous data sources. Dimou et al [8], Michel et al [16], and Vidal et al [19] propose EA as a pre-processing step, prior to the semantic enrichment and integration of data. In this case, pre-processing performs the task of EA on the whole provided data sources, independent of their involvement in the goal KG.…”

“…EABlock is developed in Python3, open-source, and available under the Apache License 2.0 8 . 7 https://labs.tib.eu/sdm/falconmedical/falcon2/ 8 To keep the anonymity of the paper, EABlock will be publicly available as a tool at the Zenodo platform, GitHub, and Dockerhub after the review procedure.…”