Collaborative annotation and semantic enrichment of 3D media

Rossenova, Lozana; Schubert, Zoe; Vock, Richard; Sohmen, Lucia; Günther, Lukas; Duchesne, Paul N.; Blümel, Ina

doi:10.1145/3529372.3533289

Cited by 6 publications

(6 citation statements)

References 6 publications

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“…In the Big Active Data project [19], notifications delivered to users can be enriched with other existing data to provide actionable notifications that are individualized per user. Other proposed solutions like [20], focuses on the annotation of data within a collaborative knowledge graph environment, so that metadata is incorporated to data items and annotations remain searchable, and data interconnections are not lost.…”

Section: B Data Semantic Enrichmentmentioning

confidence: 99%

Data Enrichment Toolchain: A Data Linking and Enrichment Platform for Heterogeneous Data

Sánchez,

Lanza,

Santana

et al. 2023

IEEE Access

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Proliferation of data sources associated to Internet of Things (IoT) deployment as well as those bound to Open Data Portals (e.g. European Data Portal, Municipalities Open Data Portals, etc.) and Social Media platforms is creating an abundance of information that is called to bring benefits for both the private and public sectors, through the development of added-value services, increasing administrations' transparency and availability or fostering efficiency of public services. However, pieces of information without a context are significantly less valuable. Raw data lacks semantics and it is highly heterogeneous from one data-source to another. This poses a challenge to make it useful. To turn all this data into valuable information it is necessary to enable its combination so that meaningful context can be created. Moreover, it is fundamental to define the mechanisms enabling the adoption and orchestration of advanced (typically AIenabled) data processing techniques to be applied over the harmonized datasets and data-streams. This paper presents the Data Enrichment Toolchain (DET) that provides the necessary harmonization and enrichment to datasets and data-streams coming from heterogeneous sources. The value of the enriched data lies on the one hand in the transfer of the data into a semantically grounded knowledge graph and, on the other hand, in the creation of new data through linking, aggregating and reasoning on the data. In both cases, the benefit of employing linked-data modelling and semantics comes from the extension of the metadata that is associated to every piece of information. Furthermore, the experimental evaluation of the DET implementation that we have carried out is also presented in the paper.

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Section: B Data Semantic Enrichmentmentioning

confidence: 99%

Data Enrichment Toolchain: A Data Linking and Enrichment Platform for Heterogeneous Data

Sánchez,

Lanza,

Santana

et al. 2023

IEEE Access

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“…The NFDI4Culture [76] provides various tools, such as the FOSS infrastructure [77], for annotating 3D models with Wikidata entries. Baureka.online [78] provides a portal to store and share research data, particularly for historical architectural research.…”

Section: Data Infrastructuresmentioning

confidence: 99%

Advancements in 3D Heritage Data Aggregation and Enrichment in Europe: Implications for Designing the Jena Experimental Repository for the DFG 3D Viewer

Münster

2023

Applied Sciences

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Since the 2010s, various national and pan-European public infrastructures have been emerging around aggregation, viewing, and 3D heritage model collection. The purpose of this article is to focus on the current state and ecosystem for 3D models in Europe through (a) a review of published studies on users, objects, and demands (b) and an overview of the ecosystem for 3D heritage data. As part of the German distributed infrastructure, the DFG 3D Viewer Jena experimental repository serves as a testbed for technology prototyping and testing. Based on the findings of the European ecosystem, we used this repository to test a prototypic approach to (c) acquiring 3D data from multiple sources, (d) enriching data quality, and (e) enabling indexing, searching, and viewing functionalities.

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“…For example, MaRDI and BERD4NFDI are using Wikibase instances as central portals for all research data generated by their respective consortia participants [4,5]. In the context of NFDI4Culture, TIB's Open Science Lab deploys Wikibase instances to structure data about digitized cultural objects entered and edited via a 3D-Viewer and Annotation tool [3]. NFDI4Memory have recently also partnered with an existing major Wikibase project, Fact-Grid, run by the Gotha Research Centre and hosted at the University of Erfurt, which provides a central repository for data about historical persons and events [12].…”

Section: Service Proposalmentioning

confidence: 99%

“…The identical approach to interfacing with data, modelling and querying data between Wikidata and Wikibase provides native federation capabilities across these services, which NFDI consortia that use Wikibase are taking advantage of [3,4,12]. Developing the Wikibase tool suite further in the context of a pilot KGI for NFDI will streamline deployment and customization, and improve interoperability at scale.…”

Section: Service Proposalmentioning

confidence: 99%

“…KGs also play an essential role within Germany as a vehicle to connect research data and researchrelated entities and make those accessible -examples include the GESIS Knowledge Graph Infrastructure, TIB Open Research Knowledge Graph, and GND.network. Furthermore, the Wikidata knowledge graph, maintained by Wikimedia Germany, contains a large number of research-related entities and is widely used in scientific knowledge management in addition to being an important advocacy tool for open data [3]. Extending domain-specific ontology-supported KGs with the multidisciplinary, crowdsourced knowledge in Wikidata KG would enable significant applications.…”

Section: Introductionmentioning

confidence: 99%

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The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI

Rossenova,

Schubotz,

Shigapov

2023

Proc Conf Res Data Infrastr

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The Strategic Research and Innovation Agenda (SRIA) of the European Commission identifies Knowledge Graphs (KGs) as one of the most important technologies for building an interoperability framework and enabling data exchange among users across countries, sectors, and disciplines [1]. KG is a graph-structured knowledge base containing a terminology (vocabulary or ontology) and data entities interrelated via the terminology [2]. KGs are based on semantic web technologies (RDF, SPARQL, etc.) and often used for agile data integration. KGs also play an essential role within Germany as a vehicle to connect research data and research-related entities and make those accessible – examples include the GESIS Knowledge Graph Infrastructure, TIB Open Research Knowledge Graph, and GND.network. Furthermore, the Wikidata knowledge graph, maintained by Wikimedia Germany, contains a large number of research-related entities and is widely used in scientific knowledge management in addition to being an important advocacy tool for open data [3]. Extending domain-specific ontology-supported KGs with the multidisciplinary, crowdsourced knowledge in Wikidata KG would enable significant applications. The linking between expert knowledge systems and world knowledge empowers lay persons to benefit from high-quality research data and ultimately contributes to increasing confidence in scientific research in society.

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Collaborative annotation and semantic enrichment of 3D media

Cited by 6 publications

References 6 publications

Data Enrichment Toolchain: A Data Linking and Enrichment Platform for Heterogeneous Data

Data Enrichment Toolchain: A Data Linking and Enrichment Platform for Heterogeneous Data

Advancements in 3D Heritage Data Aggregation and Enrichment in Europe: Implications for Designing the Jena Experimental Repository for the DFG 3D Viewer

The Case for a Common, Reusable Knowledge Graph Infrastructure for NFDI

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