The In-Use track at ESWC provides a forum for the community to share the challenges and successes of using semantic technologies in real world settings. We are interested in the following types of papers:
- In-use application papers describe end-user applications that use semantic technologies to solve a problem for a community of end users. Examples of in-use applications papers include applications that use semantic technologies such as knowledge graphs, linked data, ontologies, neuro-symbolic techniques, knowledge graph embeddings, to implement a solution for a problem. The implemented solution must be deployed to a community of end users.
- In-use technology papers describe adaptations and enhancements of semantic technologies for use in real-world applications. Examples of in-use technology papers include discussions of adaptations and enhancements for scalability, run-time efficiency, ease of deployment, interoperability with other technologies (e.g., natural language processing) or other enterprise systems (e.g., relational databases). The technologies discussed in the papers must be used by a community of developers to implement applications that would be worthy of presentation in in-use application papers.
- in-use knowledge graph papers describe experiences integrating the large public knowledge graphs such as Wikidata and DBpedia into deployed applications. These papers should describe the parts of the public knowledge graphs used, the benefits of doing so and the challenges encountered such as data quality, completeness, timeliness, other data used to complement the public knowledge graph and technical approaches to host, update and deploy the knowledge graph.
In-use application papers should include:
- A description of the community of users and the problem being addressed.
- A discussion of the challenges that must be overcome to implement a solution to the problem. When possible, include a discussion of alternative solutions that do not use semantic technologies and their limitations.
- A description of the application from an end-user perspective, conveying the main tasks that users perform, the expected inputs and outputs of the application.
- A detailed description of the semantic technologies used to solve the problem and how these techniques are used to implement an effective solution.
- A discussion of the challenges faced when applying the semantic technologies and how they were overcome.
- A discussion of the deployment of the application, including information about the organizations using the application, the number of users and the deployment characteristics (e.g., number and size of machines), response times, etc.
- A discussion of lessons learned, including, when possible, quantitative metrics to measure the benefits and effectiveness of the semantic technologies, and qualitative metrics and examples to illustrate the contribution of the semantic technologies.
In-use technology papers should include:
- A description of the semantic technology (e.g., knowledge graph, query language).
- A statement of the performance, scalability, efficiency and other requirements for deployment in a practical setting in an organization.
- A discussion of the challenges faced when using the available implementations of the desired semantic technologies, including, if possible, quantitative metrics that illustrate the magnitude of the challenges.
- A detailed description of the enhancements, adaptations, simplifications, etc. to existing baseline implementations, or new re-implementations to meet deployment requirements.
- An evaluation of the new technology showing quantitative metrics to understand the magnitude of the improvements and to compare with baseline technologies.
In-use knowledge graph papers should include:
- A discussion of the public knowledge graph used, the domain of interest, and the rationale and benefits of incorporating the public knowledge graph.
- A discussion of the challenges faced in incorporating the public knowledge graph, including considerations such as subsetting the public knowledge graph, data quality, completeness and timeliness of the data, vandalism mitigation.
- A discussion of other data sources used to complement the public knowledge graph to build a satisfactory knowledge graph for the desired domain. Include a discussion of the techniques used to augment the public knowledge graph.
- A description of how the domain knowledge graph is used, including a discussion of the technologies used to deploy the knowledge graph, types of queries it supports and the language or system used to query it, analytics of interest, etc.
- When possible, include quantitative metrics about the knowledge graph, including statistics on the classes, properties and instances, query loads, response times and all metrics used to assess the performance and usefulness of the domain knowledge graph.
- A discussion of lessons learned and recommendations for the providers of the public knowledge graphs to facilitate incorporation of these knowledge graphs into the possibly private knowledge graphs used within an organization.
We understand that now all in-use papers fall neatly in the two categories above, and we also encourage submissions that address the following topics:
- Description and analysis of concrete problems and user requirements for applying semantic technologies in a specific domain
- Analysis and evaluation of usability and uptake of semantic technologies
- Scalability analysis and large scale deployment in real world scenarios
- Assessment of costs and benefits of implementing, deploying, using, and managing semantic technologies
- Analysis of risks and opportunities of using semantic technologies in organizations with respect to their businesses and customers
- Experience with large scale deployments of semantic technologies
Submissions to the In-Use track should report on the use of applications and technologies in real world settings.
Papers presenting a research prototype where the main objective is to support the validation of a research hypothesis or answering a research question are more appropriate to the research track.
Emerging applications that are not yet deployed, as well as vision papers describing future applications should be submitted to the Poster & Demo track.
Authors who want to present an interesting industry application but who do not want to submit a full paper should submit to the industry track. Also, authors who want to present a success story of the deployment & establishment of applications using semantic technologies in a real world environment addressing main benefits for their organization, key success factors or challenges encountered for the integration in an industrial setting should submit to the industry track.
The Semantic Web In-Use papers will be evaluated on their relevance to the track, rigor in the methodology and analysis used to reach conclusions, originality, readability, and usefulness to developers, researchers, and practitioners. Review criteria include:
- Novelty and significance of the problem addressed
- Value of the use case in demonstrating benefits/challenges of semantic technologies
- Adoption by domain practitioners and general members of the public
- Impact of the solution, especially in supporting the adoption of semantic technologies
- Applicability of the lessons learnt to other use cases
- Clarity and quality of the description
Important dates and submission guidelines are specified here.
Authors will have the opportunity to submit a rebuttal to the reviews to clarify questions posed by program committee members.
- Pedro Szekley
- Pavan Kapanipathi
- IBM Research AI, USA
The text from this CfP is based on the call for In-Use Papers for ESWC 2020, by Anna Lisa Gentile and Peter Haase, which was already based on previous calls: In-Use Papers for ISWC 2017 by Philippe Cudré-Mauroux and Juan Sequeda and the call for In-Use Papers for ESWC 2018 by Anna Tordai and Laura Hollink, and the call for In-Use Papers for ESWC 2019 by Vanessa Lopez and Armin Haller.