Semantic Publishing Challenge – Assessing the Quality of Scientific Output by Information Extraction and Interlinking

Iorio, Angelo Di; Lange, Christoph; Dimou, Anastasia; Vahdati, Sahar

doi:10.1007/978-3-319-25518-7_6

Cited by 15 publications

(11 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We get a similar picture if we look at the Semantic Publishing Challenge held at the Semantic Web conferences ESWC from 2014 until 2017 [20,30,49]. There were three tasks defined for each of these three challenges, but none of them actually deals with publishing.…”

Section: Semantic Publishingmentioning

confidence: 95%

“…The topic of semantic publishing has received considerable attention during the last few years, most prominently in events that carry the term in their names, specifically the workshop series on Semantic Publishing (SePublica) 1 and the Semantic Publishing Challenges at ESWC conferences [20,30,49]. However, as we argue below, the presented approaches mostly interpret the term semantic publishing in a non-intuitive way.…”

Section: T Kuhn and M Dumontier / Genuine Semantic Publishingmentioning

confidence: 99%

See 1 more Smart Citation

Genuine semantic publishing

Kuhn

Dumontier

2017

View full text Add to dashboard Cite

Editor: Silvio Peroni (https://orcid.org/0000-0003-0530-4305) Solicited reviews: Sarven Capadisli (https://orcid.org/0000-0002-0880-9125); Francesco Osborne (https://orcid.org/0000-0001-6557-3131); Jodi Schneider (https://orcid.org/0000-0002-5098-5667) Closer inspection, however, reveals that these approaches are mostly not about publishing semantic representations, as the name seems to suggest. Rather, they take the processes and outcomes of the current narrative-based publishing system for granted and only work with already published papers. This includes approaches involving semantic annotations, semantic interlinking, semantic integration, and semantic discovery, but with the semantics coming into play only after the publication of the original article. While these are interesting and important approaches, they fall short of providing a vision to transcend the current publishing paradigm. We argue here for taking the term semantic publishing literally and work towards a vision of genuine semantic publishing, where computational tools and algorithms can help us with dealing with the wealth of human knowledge by letting researchers capture their research results with formal semantics from the start, as integral components of their publications. We argue that these semantic components should furthermore cover at least the main claims of the work, that they should originate from the authors themselves, and that they should be fine-grained and light-weight for optimized re-usability and minimized publication overhead. This paper is in fact not just advocating our concept, but is itself a genuine semantic publication, thereby demonstrating and illustrating our points.

show abstract

Section: Semantic Publishingmentioning

confidence: 95%

Section: T Kuhn and M Dumontier / Genuine Semantic Publishingmentioning

confidence: 99%

Genuine semantic publishing

Kuhn

Dumontier

2017

View full text Add to dashboard Cite

show abstract

“…More detailed reports for each edition have been published separately by , Di Iorio et al (2015) and Dimou et al (2016).…”

Section: Semantic Publishing Challenge: 2014-2016mentioning

confidence: 99%

“…Semantic publishing is defined as ''the enhancement of scholarly publications by the use of modern Web standards to improve interactivity, openness and usability, including the use of ontologies to encode rich semantics in the form of machine-readable RDF metadata'' by Shotton (2009). The 2014 Semantic Publishing Challenge, was themed ''Assessing the Quality of Scientific Output'' ) (2014 SemPub Challenge, http: //2014.eswc-conferences.org/semantic-publishing-challenge.html), in 2015 we mentioned the techniques more explicitly by appending ''... by Information Extraction and Interlinking'' (Di Iorio et al, 2015) (2015 SemPub Challenge, http://2015.eswc-conferences. org/important-dates/call-SemPub), and in 2016 we generalized to ''... in its Ecosystem'' to emphasize the multiple dimensions of scientific quality and the potential impact of producing Linked Data about it SemPub Challenge, http: //2016.eswc-conferences.org/assessing-quality-scientific-output-its-ecosystem).…”

Section: Introductionmentioning

confidence: 99%

Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing Challenge

Dimou

Vahdati

Iorio

et al. 2017

PeerJ Computer Science

Self Cite

View full text Add to dashboard Cite

While most challenges organized so far in the Semantic Web domain are focused on comparing tools with respect to different criteria such as their features and competencies, or exploiting semantically enriched data, the Semantic Web Evaluation Challenges series, co-located with the ESWC Semantic Web Conference, aims to compare them based on their output, namely the produced dataset. The Semantic Publishing Challenge is one of these challenges. Its goal is to involve participants in extracting data from heterogeneous sources on scholarly publications, and producing Linked Data that can be exploited by the community itself. This paper reviews lessons learned from both (i) the overall organization of the Semantic Publishing Challenge, regarding the definition of the tasks, building the input dataset and forming the evaluation, and (ii) the results produced by the participants, regarding the proposed approaches, the used tools, the preferred vocabularies and the results produced in the three editions of 2014, 2015 and 2016. We compared these lessons to other Semantic Web Evaluation Challenges. In this paper, we (i) distill best practices for organizing such challenges that could be applied to similar events, and (ii) report observations on Linked Data publishing derived from the submitted solutions. We conclude that higher quality may be achieved when Linked Data is produced as a result of a challenge, because the competition becomes an incentive, while solutions become better with respect to Linked Data publishing best practices when they are evaluated against the rules of the challenge.

show abstract

“…In this paper, we present a general-purpose Linked Data publishing workflow, adjusted to scholarly data publishing, which can be used by different data owners. The proposed workflow is applied in the case of the iLastic 8 Linked Data set generation and publishing for the iMinds 9 research institute's scholarly (meta)data. The workflow is complemented by an easily adjustable and extensible user interface which allows users to explore the underlying Linked Data.…”

Section: Introductionmentioning

confidence: 99%

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

Dimou

Haesendonck

Vanbrabant

et al. 2018

Semantics, Analytics, Visualization

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Semantic Publishing Challenge – Assessing the Quality of Scientific Output by Information Extraction and Interlinking

Cited by 15 publications

References 13 publications

Genuine semantic publishing

Genuine semantic publishing

Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing Challenge

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

Contact Info

Product

Resources

About