PEOPLEEgon W. Stemle

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Egon W. Stemle

Researcher
Institute for Applied Linguistics

T +39 0471 055 129

egon.stemle@eurac.edu

https://orcid.org/0000-0002-7655-5526

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About

I am a Cognitive Scientist: I study skills like perception, thinking, learning, and language by combining the humanistic and analytical methods of the arts and the formal sciences.

My research focus lies in the area where Computational Linguistics and Artificial Intelligence converge. I work on the creation, standardisation, and interoperability of tools for editing, processing, and annotating linguistic
data and enjoy working together with other scientists on their data, but I also collect or help to collect new data from the Web, from computer-mediated communication and social media, and from language learners.

I am an advocate of open science to make research and data available for others to consult or reuse in new research.

My curiosity in research is driven by the question why humans handle incomplete and – more often than not – inconsistent structured concepts just fine, whereas computational processes are often of little avail or fail completely.

External links:

Homepage https://iiegn.eu
CV https://github.com/iiegn/pub/raw/master/CV/CV_en.pdf

Scientific Publications

Conference proceedings article2025

Towards a new Curation Workflow for the CMC Corpora Resource Family

Stemle EW, Nicolas L, König A

Egon W. Stemle, Lionel Nicolas

Projekt: Gemeinsame Infrastruktur für Sprachressourcen und -technologie für Italien bei Eurac Research

This paper aims at raising awareness regarding a recently started and ongoing effort of CLARIN ERIC and the CLARIN Knowledge Centre for CMC and Social Media Corpora (CKCMC) to enhance the visibility and accessibility of the CMC community’s datasets through the CLARIN CMC Corpora Resource Family (CMC-RF), which, as of May 2025, the CKCMC officially adopted, that is, it took over responsibility. We offer some possible scenarios regarding how curation (addition, change and deletion of entries) of the CMC-RF could be approached, with the objective to prepare a productive context for a roundtable at the forthcoming 2025 edition of the CMC-Corpora conference. We intend to use the outcomes of this roundtable to devise a grounded and informed first version of Curation Guidelines for the CMC-RF, together with a community-oriented procedure to update it.

DOI Quelle

DOI: 10.15495/EPub_UBT_00008705

Journal article2024

The Core Metadata Schema for Learner Corpora (LC-meta): collaborative efforts to advance data discoverability, metadata quality and study comparability in L2 research

Paquot M, König A, Stemle EW, Frey JC

Egon W. Stemle, Jennifer-Carmen Frey

Metadata is critical throughout the research process, from study design to corpus selection/compilation, result interpretability and cumulative research. To date, however, learner corpus research has not developed community standards or best practices for metadata collection and sharing. In this article, we present the results of a collaborative project aimed at addressing this issue by developing a standardised metadata schema for learner corpora. We first describe the procedure implemented to design the schema, including the ways in which we continuously involved learner corpus researchers in this initiative. We then introduce the Core Metadata Schema for Learner Corpora (LC-meta, Version 2), which consists in a set of obligatory and optional variables that encapsulate crucial information about L2 data (administrative details, corpus design, text-related variables, learner-related variables, annotations, annotators, or transcribers). Finally, we discuss future developments and emphasise the importance of continued maintenance and further refinement of this schema by the research community.

DOI Quelle

DOI: 10.1075/ijlcr.24010.paq

Conference proceedings article2023

On a digital journey into yesterday’s future: Zeit.shift - preserving Tyrol’s cultural text heritage

Walcher J, Abel A, Andresen J, Brasolin P, Dissertori I, Eberwein E, Franzini G, Gstrein S,

Egon W. Stemle, Andrea Abel, Greta Franzini

Projekt: Zeit.shift – digital in gesterns Zukunft: Bewahrung, Erschließung und Vermittlung des kulturellen Texterbes Gesamttirols

This paper outlines the participatory approach in Zeit.shift and provides insight into strategies and challenges of the exploratory approach to public involvement in this project.

DOI

DOI: 10.22323/1.407.0019

Conference proceedings article2022

Citizen Humanities in Tyrol: A case study on historical newspapers

Franzini G, Stemle EW, Lyding V, Abel A, Andresen J, Pircher K, Gstrein S, Laner B,

Egon W. Stemle, Andrea Abel, Greta Franzini

Projekt: Zeit.shift – digital in gesterns Zukunft: Bewahrung, Erschließung und Vermittlung des kulturellen Texterbes Gesamttirols

This poster outlines a citizen humanities activity developed for a transnational project devoted to the digitisation and promotion of newspapers from the historical region of Tyrol.

DOI Quelle

DOI: 10.6092/unibo/amsacta/6848

Conference proceedings article2022

Collaborating on Language Resource Infrastructures with Non-Research Partners: Practicalities and Challenges

Lyding V, Stemle E, König A

Egon W. Stemle

By now, digital infrastructures for language data and tools have become commonplace in theresearch domain, but their possible benefits are still almost unknown outside of these circles.However, it stands to reason that the data and methods developed there could also be used bynon-research language actors like publishing houses or libraries. This article presents a use casewithin a local language infrastructure project describing our interactions with a newspaper portalthat resulted in modern NLP tools being made available via an API to help improve their onlinesearch. We describe how this use case was implemented, focusing on the problems that came up,specifically those from the interaction between a research and a non-research institution.

DOI Quelle

DOI: 10.3384/ecp1899

Conference proceedings article2022

Zeit.shift: Driving Citizens to Tyrolean Historical Newspapers

Franzini GH, Brasolin P, Lyding V, Stemle EW, Abel A, Andresen J

Egon W. Stemle, Andrea Abel, Greta Franzini

Projekt: Zeit.shift – digital in gesterns Zukunft: Bewahrung, Erschließung und Vermittlung des kulturellen Texterbes Gesamttirols

Zeit.shift is an ongoing digital humanities cooperation between Eurac Research (Bolzano, Italy), the Landesbibliothek Dr. Friedrich Teßmann (Bolzano, Italy) and the Universitäts- und Landesbibliothek Tirol (Innsbruck, Austria) for the digital preservation, enrichment and dissemination of the textual heritage of historical Tyrol. Using digitised German-language historical newspapers as a use-case, Zeit.shift is, among other project goals, developing two participatory tasks –image annotation and text transcription– to increase citizen awareness of, and active engagement with, these collections, while exploring the potential of the tasks themselves as data acquisition tools for research. As of July 2022, results show 25 contributors for the annotation activity with 303 (geo)tagged images and 1,430 unique tags, and 288 played games from 241 unique devices totalling 1,910 words transcribed for the web game.

DOI Quelle

DOI: 10.22323/1.418.0003

Journal article2021

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

König A, Frey JC, Stemle EW

Egon W. Stemle, Jennifer-Carmen Frey

Projekt: Lernerkorpusinfrastruktur

Up until today research in various educational and linguistic domains such as learner corpus research, writing research, or second language acquisition has produced a substantial amount of research data in the form of L1 and L2 learner corpora. However, the multitude of individual solutions combined with domain-inherent obstacles in data sharing have so far hampered comparability, reusability and reproducibility of data and research results. In this article, we present work in creating a digital infrastructure for L1 and L2 learner corpora and populating it with data collected in the past. We embed our infrastructure efforts in the broader field of infrastructures for scientific research, drawing from technical solutions and frameworks from research data management, among which the FAIR guiding principles for data stewardship. We share our experiences from integrating some L1 and L2 learner corpora from concluded projects into the infrastructure while trying to ensure compliance with the FAIR principles and the standards we established for reproducibility, discussing how far research data that has been collected in the past can be made comparable, reusable and reproducible. Our results show that some basic needs for providing comparable and reusable data are covered by existing general infrastructure solutions and can be exploited for domain-specific infrastructures such as the one presented in this article. Other aspects need genuinely domain-driven approaches. The solutions found for the corpora in the presented infrastructure can only be a preliminary attempt, and further community involvement would be needed to provide templates and models acknowledged and promoted by the community. Furthermore, forward-looking data management would be needed starting from the beginning of new corpus creation projects to ensure that all requirements for FAIR data can be met.

DOI Quelle

DOI: 10.3390/info12050199

Journal article2021

Harnessing artificial intelligence technology and social media data to support Cultural Ecosystem Service assessments

Egarter Vigl L, Marsoner T, Giombini V, Simion H, Pecher C, Stemle E, Tasser E, Depellegrin D

Egon W. Stemle, Caroline Pecher, Lukas Egarter Vigl, Erich Tasser, Thomas Marsoner, Heidi Simion

Cultural Ecosystem Services (CESs), such as aesthetic and recreational enjoyment, as well as sense of place and cultural heritage, play an outstanding role in the contribution of landscapes to human well-being.
Scientists, however, still often struggle to understand how landscape characteristics contribute to deliver these intangible benefits, largely because it is hard to navigate how people value nature, and because there is a lack in methods that accommodate both comprehensive and time-efficient evaluations.
Recent advances in technology and the proliferation of new data sources, such as social media data, open promising alternatives to traditional, resource-intensive methods, facilitating the understanding of the multiple relationships between people and nature.
Here, we examine a user-friendly artificial intelligence (AI)-based approach for inferring visual-sensory landscape values from Flickr data, combining computer vision with text mining. We show it is possible to automatically relate photographers' preferences in capturing landscape elements to a set of CESs (aesthetic value, outdoor recreation, cultural heritage, symbolic species) with reasonable accuracy, using the semantic content provided by approximately 640,000 artificially generated tags of photographs taken in the UNESCO world heritage site ‘The Dolomites’ (Italy). We used the geographic information in the data to demonstrate that these preferences can be further linked to different natural and human variables and be used to spatially predict CES patterns.
Over 90% of photograph tags could be linked to four CES categories with reasonable confidence (accuracy ration ∼ 80%). The Dolomites are highly appreciated for its aesthetic value (66% of images classified to that category) and vast cultural heritage (13%), followed by its outdoor recreation opportunities (11%) and symbolic species (10%). CES benefiting hotspots were found in areas with high tourism development and close to residential areas, and could largely be explained by a combination of environmental (e.g. landscape composition) and infrastructural (e.g. accessibility) variables.
We conclude that online available AI technology and social media data can effectively be used to support rapid, flexible and transferrable CES assessments. Our work can provide a reference for innovative adaptive management approaches that can harness emerging technologies to gain insights into human–nature relationships and to sustainably manage our environment.

DOI Quelle

DOI: 10.1002/pan3.10199

Conference proceedings article2020

A Report on the 2020 VUA and TOEFL Metaphor Detection Shared Task

Leong CW, Klebanov BB, Hamill C, Stemle E, Ubale R, Chen X

Egon W. Stemle

Projekt: Computergestützter PoS-Tagger-Aufbau

In this paper, we report on the shared task on metaphor identification on VU Amsterdam Metaphor Corpus and on a subset of the TOEFL Native Language Identification Corpus. The shared task was conducted as apart of the ACL 2020 Workshop on Processing Figurative Language.

DOI Quelle

DOI: 10.18653/v1/P17

Edited book2020

Proceedings of the 12th Web as Corpus Workshop

Barbaresi A, Bildhauer F, Schäfer R, Stemle E

Egon W. Stemle

ISBN: 979-10-95546-68-9

For almost fifteen years, the ACL SIGWAC, and most notably the Web as Corpus (WAC) workshops, have served as a platform for researchers interested in the compilation, processing and use of webderived corpora as well as computer-mediated communication. Past workshops were co-located with major conferences on corpus linguistics and computational linguistics (such as ACL, EACL, Corpus Linguistics, LREC, NAACL, WWW). In corpus linguistics and theoretical linguistics, the World Wide Web has become increasingly popular as a source of linguistic evidence, especially in the face of data sparseness or the lack of variation in traditional corpora of written language. In lexicography, web data have become a major and wellestablished resource with dedicated research data and specialised tools. In other areas of theoretical linguistics, the adoption rate of web corpora has been slower but steady. Furthermore, some completely new areas of linguistic research dealing exclusively with web (or similar) data have emerged, such as the construction and utilisation of corpora based on short messages. Another example is the (manual or automatic) classification of web texts by genre, register, or – more generally speaking – “text type”, as well as topic area. In computational linguistics, web corpora have become an established source of data for the creation of language models, word embeddings, and all types of machine learning. The 12th Web as Corpus workshop (WAC-XII) looks at the past, present, and future of web corpora given the fact that large web corpora are nowadays provided mostly by a few major initiatives and companies, and the diversity of the early years appears to have faded slightly. Also, we acknowledge the fact that alternative sources of data (such as data from Twitter and similar platforms) have emerged, some of them only available to large companies and their affiliates, such as linguistic data from social media and other forms of the deep web. At the same time, gathering interesting and relevant web data (web crawling) is becoming an ever more intricate task as the nature of the data offered on the web changes (for example the death of forums in favour of more closed platforms).

Quelle

Conference proceedings article2020

Technical Solutions for Reproducible Research

König A, Stemle EW, Moreira A, Elbers W

Egon W. Stemle

In recent years, the reproducibility of scientific research has increasingly come into focus, both by ex

ternal stakeholders (e.g. funders) and by the research communities themselves. Corpus linguistics, with its methods for creating, processing and analysing corpora, is an integral part of many other disciplines that work with language data and therefore plays a special role. Moreover, language corpora are often living objects that are regularly improved and revised. At the same time, tools for the automatic processing of human language are also being developed further, which can lead to different results with the same processing steps and the same data. This article argues that modern software technologies, such as version control and containerisation, can mitigate the following problems: Software packaging, installation and execution and, equally important, the tracking of corpus modifications throughout its life-cycle.

All in all, this leads to transparency of changes to raw data and software tools and thereby enhanced reproducibility.

DOI

DOI: 10.3384/ecp2020172

Edited book2019

Building computer-mediated communication corpora for socio-linguistic analysis

Wigham C, Stemle EW

Egon W. Stemle

ISBN: 978-2-84516-859-6

Communication between humans via networked devices has become an everyday part of people's lives across generations, cultures, geographical areas, and social classes. Shaped by the specific social and technical context in which it is produced, synchronous and asynchronous computer-mediated communication (CMC) has become increasingly participatory, interactive, and multimodal. User interactions and user-generated social media content offer a wide range of research opportunities for a growing multidisciplinary research community.

This edited volume combines methodological papers that focus on building and annotating CMC corpora and papers that offer a sociolinguistic analysis of different CMC corpora. The diversity of languages represented in the corpora include Arabic, French, German, Italian, English and Slovenian. In fact, the increasingly multilingual nature of CMC data is a recurring theme throughout the volume, as are the references to the importance of and compliance with standards for CMC corpora development in order to facilitate (the?) re-examination of corpora for reproducibility, and for other areas and objectives of investigation.

All but one paper are extended papers from the 2017 edition of the CMC and Social Media Corpora Conference held in Bolzano, Italy where the community met to discuss themes that related to the interaction between language, CMC, and society.

Journal article2021

Harnessing artificial intelligence technology and social media data to support Cultural Ecosystem Service assessments

Egarter Vigl L, Marsoner T, Giombini V, Simion H, Pecher C, Stemle E, Tasser E, Depellegrin D

Egon W. Stemle, Caroline Pecher, Lukas Egarter Vigl, Erich Tasser, Thomas Marsoner, Heidi Simion

Cultural Ecosystem Services (CESs), such as aesthetic and recreational enjoyment, as well as sense of place and cultural heritage, play an outstanding role in the contribution of landscapes to human well-being.
Scientists, however, still often struggle to understand how landscape characteristics contribute to deliver these intangible benefits, largely because it is hard to navigate how people value nature, and because there is a lack in methods that accommodate both comprehensive and time-efficient evaluations.
Recent advances in technology and the proliferation of new data sources, such as social media data, open promising alternatives to traditional, resource-intensive methods, facilitating the understanding of the multiple relationships between people and nature.
Here, we examine a user-friendly artificial intelligence (AI)-based approach for inferring visual-sensory landscape values from Flickr data, combining computer vision with text mining. We show it is possible to automatically relate photographers' preferences in capturing landscape elements to a set of CESs (aesthetic value, outdoor recreation, cultural heritage, symbolic species) with reasonable accuracy, using the semantic content provided by approximately 640,000 artificially generated tags of photographs taken in the UNESCO world heritage site ‘The Dolomites’ (Italy). We used the geographic information in the data to demonstrate that these preferences can be further linked to different natural and human variables and be used to spatially predict CES patterns.
Over 90% of photograph tags could be linked to four CES categories with reasonable confidence (accuracy ration ∼ 80%). The Dolomites are highly appreciated for its aesthetic value (66% of images classified to that category) and vast cultural heritage (13%), followed by its outdoor recreation opportunities (11%) and symbolic species (10%). CES benefiting hotspots were found in areas with high tourism development and close to residential areas, and could largely be explained by a combination of environmental (e.g. landscape composition) and infrastructural (e.g. accessibility) variables.
We conclude that online available AI technology and social media data can effectively be used to support rapid, flexible and transferrable CES assessments. Our work can provide a reference for innovative adaptive management approaches that can harness emerging technologies to gain insights into human–nature relationships and to sustainably manage our environment.

DOI Quelle

DOI: 10.1002/pan3.10199

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Egon W. Stemle

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Scientific Publications

Towards a new Curation Workflow for the CMC Corpora Resource Family

The Core Metadata Schema for Learner Corpora (LC-meta): collaborative efforts to advance data discoverability, metadata quality and study comparability in L2 research

On a digital journey into yesterday’s future: Zeit.shift - preserving Tyrol’s cultural text heritage

Citizen Humanities in Tyrol: A case study on historical newspapers

Collaborating on Language Resource Infrastructures with Non-Research Partners: Practicalities and Challenges

Zeit.shift: Driving Citizens to Tyrolean Historical Newspapers

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

Harnessing artificial intelligence technology and social media data to support Cultural Ecosystem Service assessments

A Report on the 2020 VUA and TOEFL Metaphor Detection Shared Task

Proceedings of the 12th Web as Corpus Workshop

Technical Solutions for Reproducible Research

Building computer-mediated communication corpora for socio-linguistic analysis

Science Shots Eurac Research Newsletter

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Externe Inhalte

Scientific Publications

Towards a new Curation Workflow for the CMC Corpora Resource Family

The Core Metadata Schema for Learner Corpora (LC-meta): collaborative efforts to advance data discoverability, metadata quality and study comparability in L2 research

On a digital journey into yesterday’s future: Zeit.shift - preserving Tyrol’s cultural text heritage

Citizen Humanities in Tyrol: A case study on historical newspapers

Collaborating on Language Resource Infrastructures with Non-Research Partners: Practicalities and Challenges

Zeit.shift: Driving Citizens to Tyrolean Historical Newspapers

Exploring Reusability and Reproducibility for a Research Infrastructure for L1 and L2 Learner Corpora

Harnessing artificial intelligence technology and social media data to support Cultural Ecosystem Service assessments

A Report on the 2020 VUA and TOEFL Metaphor Detection Shared Task

Proceedings of the 12th Web as Corpus Workshop

Technical Solutions for Reproducible Research

Building computer-mediated communication corpora for socio-linguistic analysis

Technische
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