Elias Kärle

Umutcan Serles, Elias Kärle, Richard Hunkel et al.

Tourism is one of the most critical sectors of the global economy. Due to its heterogeneous and fragmented nature, it provides one of the most suitable use cases for knowledge graphs. In this poster, we introduce the German Tourism Knowledge Graph that integrates tourism-related data from 16 federal states of Germany and various other sources to provide a curated knowledge source for various applications. It is publicly available through GUIs and an API.

Elwin Huaman, Elias Kärle, Dieter Fensel

Knowledge graphs (KGs) have shown to be an important asset of large companies like Google and Microsoft. KGs play an important role in providing structured and semantically rich information, making them available to people and machines, and supplying accurate, correct and reliable knowledge. To do so a critical task is knowledge validation, which measures whether statements from KGs are semantically correct and correspond to the so-called "real" world. In this paper, we provide an overview and review of the state-of-the-art approaches, methods and tools on knowledge validation for KGs, as well as an evaluation of them. As a result, we demonstrate a lack of reproducibility of tools results, give insights, and state our future research direction.

Elwin Huaman, Elias Kärle, Dieter Fensel

In recent years, an increasing amount of knowledge graphs (KGs) have been created as a means to store cross-domain knowledge and billion of facts, which are the basis of costumers' applications like search engines. However, KGs inevitably have inconsistencies such as duplicates that might generate conflicting property values. Duplication detection (DD) aims to identify duplicated entities and resolve their conflicting property values effectively and efficiently. In this paper, we perform a literature review on DD methods and tools, and an evaluation of them. Our main contributions are a performance evaluation of DD tools in KGs, improvement suggestions, and a DD workflow to support future development of DD tools, which are based on desirable features detected through this study.

Umutcan Şimşek, Kevin Angele, Elias Kärle et al.

Schema.org is a widely adopted vocabulary for semantic annotation of content and data. However, its generic nature makes it complicated for data publishers to pick right types and properties for a specific domain and task. In this paper we propose a formal approach, a domain specification process that generates domain specific patterns by applying operators implemented in SHACL to the schema.org vocabulary. These patterns can support knowledge generation and assessment processes for specific domains and tasks. We demonstrated our approach with use cases in tourism domain.

Oleksandra Panasiuk, Omar Holzknecht, Umutcan Şimşek et al.

In this paper, we propose a framework to perform verification and validation of semantically annotated data. The annotations, extracted from websites, are verified against the schema.org vocabulary and Domain Specifications to ensure the syntactic correctness and completeness of the annotations. The Domain Specifications allow checking the compliance of annotations against corresponding domain-specific constraints. The validation mechanism will detect errors and inconsistencies between the content of the analyzed schema.org annotations and the content of the web pages where the annotations were found.

Umutcan Şimşek, Elias Kärle, Dieter Fensel

The creation of Linked Data from raw data sources is, in theory, no rocket science (pun intended). Depending on the nature of the input and the mapping technology in use, it can become a quite tedious task. For our work on mapping real-life touristic data to the schema.org vocabulary we used RML but soon encountered, that the existing Java mapper implementations reached their limits and were not sufficient for our use cases. In this paper we describe a new implementation of an RML mapper. Written with the JavaScript based NodeJS framework it performs quite well for our uses cases where we work with large XML and JSON files. The performance testing and the execution of the RML test cases have shown, that the implementation has great potential to perform heavy mapping tasks in reasonable time, but comes with some limitations regarding JOINs, Named Graphs and inputs other than XML and JSON - which is fine at the moment, due to the nature of the given use cases.

Elias Kärle, Dieter Fensel

Publishing fast changing dynamic data as open data on the web in a scalable manner is not trivial. So far the only approaches describe publishing as much data as possible, which then leads to problems, like server capacity overload, network latency or unwanted knowledge disclosure. With this paper we show ways how to publish dynamic data in a scalable, meaningful manner by applying context-dependent publication heuristics. The outcome shows that the application of the right publication heuristics in the right domain can improve the publication performance significantly. Good knowledge about the domain help choosing the right publication heuristic and hence lead to very good publication results.

Elias Kärle, Umutcan Şimşek, Oleksandra Panasiuk et al.

The introduction of the schema.org vocabulary was a big step towards making websites machine read- and understandable. Due to schema.org's RDF-like nature storing annotations in a graph database is easy and efficient. In this paper the authors show how they gather touristic data in the Austrian region of Tirol and provide this data publicly in a knowledge graph. The definition of subsets of the vocabulary is followed by providing means to map data sources efficiently to schema.org and then store the annotated content into the graph. To showcase the consumption of the touristic data four scenarios are described which use the knowledge graph for real life applications and data analysis.

Umutcan Şimşek, Elias Kärle, Dieter Fensel

The schema.org initiative led by the four major search engines curates a vocabulary for describing web content. The number of semantic annotations on the web are increasing, mostly due to the industrial incentives provided by those search engines. The annotations are not only consumed by search engines, but also by other automated agents like intelligent personal assistants (IPAs). However, only annotating data is not enough for automated agents to reach their full potential. Web APIs should be also annotated for automating service consumption, so the IPAs can complete tasks like booking a hotel room or buying a ticket for an event on the fly. Although there has been a vast amount of effort in the semantic web services field, the approaches did not gain too much adoption outside of academia, mainly due to lack of concrete incentives and steep learning curves. In this paper, we suggest a lightweight, bottom-up approach based on schema.org actions to annotate Web APIs. We analyse schema.org vocabulary in the scope of lightweight semantic web services literature and propose extensions where necessary. We show that schema.org actions could be a suitable vocabulary for Web API description. We demonstrate our work by annotating existing Web APIs of accommodation service providers. Additionally, we briefly demonstrate how these APIs can be used dynamically, for example, by a dialogue system.

Boran Taylan Balcı, Umutcan Şimşek, Elias Kärle et al.

Schema.org is an initiative founded in 2011 by the four-big search engine Bing, Google, Yahoo!, and Yandex. The goal of the initiative is to publish and maintain the schema.org vocabulary, in order to facilitate the publication of structured data on the web which can enable the implementation of automated agents like intelligent personal assistants and chatbots. In this paper, the usage of schema.org in tourism domain between years 2013 and 2016 is analysed. The analysis shows the adoption of schema.org, which indicates how well the tourism sector is prepared for the web that targets automated agents. The results have shown that the adoption of schema.org type and properties is grown over the years. While the US is dominating the annotation numbers, a drastic drop is observed for the proportion of the US in 2016. Poorly rated businesses are encountered more in 2016 results in comparison to previous years.

Oleksandra Panasiuk, Elias Kärle, Umutcan Simsek et al.

Schema.org is an initiative by Bing, Google, Yahoo! and Yandex that publishes a vocabulary for creating structured data markup on web pages. The use of schema.org is necessary to increase the visibility of a website, making the content understandable to different automated agents (e.g. search engines, chatbots or personal assistant systems). The domain specifications are the subsets of types from the schema.org vocabulary, each associated with a set of properties. The challenge is to choose the right classes and properties for an annotation in a given domain. In this paper we address the problem of finding a subset of types and properties for complete and correct annotation of different tourism domains. The approach provides a collection of domain specifications that were built based on domain analysis and vocabulary selection.

Elias Kärle, Dieter Fensel

With a strong motivational background in search engine optimization the amount of structured data on the web is growing rapidly. The main search engine providers are promising great increase in visibility through annotation of the web page's content with the vocabulary of schema.org and thus providing it as structured data. But besides the usage by search engines the data can be used in various other ways, for example for automatic processing of annotated web services or actions. In this work we present an approach to consume and process schema.org annotated data on the web and give an idea how a best practice can look like.

Elias Kärle, Umutcan Şimşek, Dieter Fensel

The application of semantic technologies to content on the web is, in many regards, important and urgent. Search engines, chatbots, intelligent personal assistants and other technologies increasingly rely on content published as semantic structured data. Yet, the process of creating this kind of data is still complicated and widely unknown. The semantify.it platform implements an approach to solve three of the most challenging question regarding the publication of structured semantic data, namely: a) what vocabulary to use, b) how to create annotation files and c) how to publish or integrate annotations within a website without programming. This paper presents the idea and the development of the semantify.it platform. It demonstrates that the creation process of semantically annotated data does not have to be hard, shows use cases and pilot users of the created software and presents where the development of this platform or alike projects lead to in the future.

Umutcan Şimşek, Elias Kärle, Omar Holzknecht et al.

Since its unveiling in 2011, schema.org has become the de facto standard for publishing semantically described structured data on the web, typically in the form of web page annotations. The increasing adoption of schema.org facilitates the growth of the web of data, as well as the development of automated agents that operate on this data. Schema.org is a large heterogeneous vocabulary that covers many domains. This is obviously not a bug, but a feature, since schema.org aims to describe almost everything on the web, and the web is huge. However, the heterogeneity of schema.org may cause a side effect, which is the challenge of picking the right classes and properties for an annotation in a certain domain, as well as keeping the annotation semantically consistent. In this work, we introduce our rule based approach and an implementation of it for validating schema.org annotations from two aspects: (a) the completeness of the annotations in terms of a specified domain, (b) the semantic consistency of the values based on pre-defined rules. We demonstrate our approach in the tourism domain.

Zaenal Akbar, Elias Kärle, Oleksandra Panasiuk et al.

The tourism industry has a significant impact on the world's economy, contributes 10.2% of the world's gross domestic product in 2016. It becomes a very competitive industry, where having a strong online presence is an essential aspect for business success. To achieve this goal, the proper usage of latest Web technologies, particularly schema.org annotations is crucial. In this paper, we present our effort to improve the online visibility of touristic service providers in the region of Tyrol, Austria, by creating and deploying a substantial amount of semantic annotations according to schema.org, a widely used vocabulary for structured data on the Web. We started our work from Tourismusverband (TVB) Mayrhofen-Hippach and all touristic service providers in the Mayrhofen-Hippach region and applied the same approach to other TVBs and regions, as well as other use cases. The rationale for doing this is straightforward. Having schema.org annotations enables search engines to understand the content better, and provide better results for end users, as well as enables various intelligent applications to utilize them. As a direct consequence, the region of Tyrol and its touristic service increase their online visibility and decrease the dependency on intermediaries, i.e. Online Travel Agency (OTA).