@article{GeyMKW25,

title = {find.software: Foundations for Interdisciplinary Discovery of (Research) Software},

volume = {11},

issn = {2367-7163},

url = {https://riojournal.com/article/179253/},

doi = {10.3897/rio.11.e179253},

shorttitle = {find.software},

abstract = {Across essentially all fields of research, many aspects of the respective research processes – whether experimental, theoretical, empirical or outright computational – are closely related to software. Yet the process of finding software that is directly suitable or at least a good starting point for a given research task is cumbersome.

This project aims to develop a community-driven system that provides potential users of research software with a diversity of pathways towards actually finding software that closely matches their research needs if such software exists. Conversely, it will provide software developers with mechanisms to make their software findable for research-related tasks and it will highlight mismatches between software supply and demand for specific tasks.

To this end, we will document how various stakeholders of the research landscape have been searching for – or stumbling upon – research software so far, identify variables associated with successful search outcomes and build workflows that assist in describing software and associated concepts in a standardised fashion. These descriptions will then be aligned across various sources of relevant information and integrated into Wikidata, the knowledge graph that anyone can edit and that already contains considerable breadth and depth of information related to research, software and their interactions.

While keeping an eye on similar approaches to software discovery that might work in parts of the research ecosystem, existing Wikidata content and workflows will be reviewed and built upon. Additional documentation, tooling and workflows will be developed to enrich, expand, curate, query and explore this content, both for specific use cases and with ongoing engagement of the communities involved in research software, open data or collaborative curation. Within its three years, the project seeks to establish a dedicated community overseeing a well-documented and smoothly running infrastructure for software discovery and to devise a plan for how this can be sustained for the longer term.},

pages = {e179253},

journaltitle = {Research Ideas and Outcomes},

shortjournal = {{RIO}},

author = {Gey, Ronny and Mietchen, Daniel and Karras, Oliver and Wittenborg, Tim and Schubotz, Moritz and Bumberger, Jan},

urldate = {2026-02-06},

date = {2025-12-03},

keywords = {!ms\_author},

}

@article{LinkeRSS25,

title = {{PID} Panel @ {CORDI}},

rights = {Creative Commons Attribution 4.0 International},

url = {https://zenodo.org/doi/10.5281/zenodo.17817057},

doi = {10.5281/ZENODO.17817057},

abstract = {A panel about the state of the art of {PID} infrastructure and the future thereof featuring the below linked {CORDI} contributions.

Said Fathalla, Mustafa Soylu, Volker Hofmann and Stefan Sandfeld {PIDA}: Reliably Addressing the Challenges of Persistent Semantic Artifact Referencing, https://doi.org/10.5281/zenodo.16735980

Emanuel Söding, Andrea Poersch, Dorothee Kottmeier, Stanislav Malinovschii and Sören Lorenz Establishing Workflows to Engage Stakeholder Groups in {PID} Metadata Maintenance, https://doi.org/10.5281/zenodo.16736056

Preston Rodrigues, David Linke and Thomas Bönisch, Persistent Identifier ({PID}) - A journey of making data machine-actionablehttps://doi.org/10.5281/zenodo.16735899

Moritz Schubotz, Sven Bingert and Tim Conrad Persistent Identifiers and Knowledge Graphs - Investigating synergies between the {NFDI} basic services {PID}4NFDI and {KGI}4NFDI, https://doi.org/10.5281/zenodo.16736129

Janete Saldanha Bach, Peter Mutschke, Yudong Zhang, {ErdalBaran}, Knut Wenzig and Noemi Betancort Cabrera Advancing data findability and re-use by {PIDs} at lower granularity level, https://doi.org/10.5281/zenodo.16736152

Each contribtion was presented in a slot of 5 minutes (bold = pesenter). The panel closed with a 15 min Q+A session on {PID}-related question from the audience.},

author = {Linke, David and Rodrigues, Preston and Schubotz, Moritz and Söding, Emanuel and Saldanha Bach Estevao, Janete and Fathalla, Said},

urldate = {2026-02-06},

date = {2025-08-27},

keywords = {!ms\_author},

}

@article{SchubotzSA25,

title = {Electronic Laboratory Notebook: An Adaptable Solution},

volume = {13},

issn = {2049-9647},

url = {http://openresearchsoftware.metajnl.com/articles/10.5334/jors.391/},

doi = {10.5334/jors.391},

shorttitle = {Electronic Laboratory Notebook},

pages = {11},

journaltitle = {Journal of Open Research Software},

author = {Schubotz, Simon and Schubotz, Moritz and Auernhammer, Günter K.},

urldate = {2026-02-06},

date = {2025-08-05},

langid = {english},

keywords = {!ms\_author},

}

@article{RossenovaLFK25,

title = {How are {NFDI} consortia using Knowledge Graphs?: An overview of common functions and challenges by the Working Group "Knowledge Graphs"},

rights = {Creative Commons Attribution 4.0 International},

url = {https://zenodo.org/doi/10.5281/zenodo.16736078},

doi = {10.5281/ZENODO.16736078},

shorttitle = {How are {NFDI} consortia using Knowledge Graphs?},

abstract = {The {NFDI} Working Group "Knowledge Graphs" ({WG} {KGs}) operates within the cross-cutting Section Metadata to coordinate and facilitate exchange on best practices, use cases, and challenges in the creation and use of knowledge graphs ({KGs}) across different disciplines. In this poster, we follow up on previously published findings, such as the dataset of {KGs} and related metadata developed and used by different consortia [1]. Besides the successful proposal and initiation of a basic service for a {KG} infrastructure ({KGI}4NFDI) [2], members of the {WG} have continued to meet regularly to discuss the ways the basic service can best meet the requirements of individual disciplines, and the {NFDI} as a whole. Furthermore, the {WG} discusses concerns beyond the scope of the basic service, such as efforts within individual consortia focused on disciplinary tasks, or ongoing developments within related basic services, such as {TS}4NFDI [3] or {PID}4NFDI [4]. Based on agile requirements gathering, feedback, and practical exchange, the {WG} has coordinated the collection of functional use cases and ongoing challenges different consortia face, with the aim to identify commonalities and/or distinctions that can inform the development of current and future basic services. The core premise of {KGs} is to represent (meta)data and their relations in a machine-understandable format, which improves semantic interoperability and data integration by adopting standard ontologies and Linked Data principles (e.g., {RDF}, {OWL}). This drives the functional use cases observed in {NFDI} consortia. Following a literature review, the following core {KG} functionalities were categorised by members of the {WG}: a) Data integration; b) Data {FAIRification}; c) Metadata cataloguing; d) Data verification, enrichment and extension; e) Machine actionability and {AI}-readiness [5–9]. These core categories were specified further through an open call among the consortia represented in the {WG} {KG}. The call collected an extended dataset of use case examples from their {KG} projects, grouped according to functionality categories, and linked to the previously published {KG} overview dataset [10]. Examples include {KGs} established by individual consortia functioning as data and metadata catalogues for discipline-specific repositories and research data portals, while using dedicated semantic ontologies as in the case of {NFDI}4Culture, {NFDI}-{MatWerk}, {NFDI}4DataScience, {MaRDI}, and {NFDI}4Objects, among others. A more specific example of data integration is the capacity of the Semantic Kompakkt {KG} ({NFDI}4Culture) and the {NFDI}4Bioimage {KG} to semantically express the annotation of 3D models and Bioimaging file formats, respectively. Alongside the use cases that illustrate why different consortia adopt specific {KG} functionalities, common challenges were also identified and documented. These challenges include harmonizing diverse ontologies within or across consortia, ensuring data verification and quality, optimizing {AI}-ready tools to support {KG} (and data) (re)usage, as well as socio-technical challenges, such as data privacy, or managing access restrictions. By collecting concrete use case examples and identifying specific challenges, the {WG} {KGs} supports its mission to encourage broader adoption of {KGs} across the {NFDI}. This effort also contributes to building a "one-stop-shop" catalog of {KG} example implementations that the {NFDI} community can turn to when starting {KG}-driven projects.},

author = {Rossenova, Lozana and Limani, Fidan and Fortmann-Grote, Carsten and Kaplan, Angelika and Thiery, Florian and Latif, Atif and Shigapov, Renat and Zapilko, Benjamin and Schubotz, Moritz and Fliegl, Heike and Tietz, Tabea},

editora = {Sure-Vetter, York and Groth, Paul},

editoratype = {collaborator},

urldate = {2026-02-06},

date = {2025-08-04},

keywords = {!ms\_author, {FAIR} data, Knowledge Graphs, {NFDI}, data integration, semantic interoperability},

}

@article{SauerweinRSS25,

title = {{KGI}4NFDI - Knowledge Graph Infrastructure for the German National Research Data Infrastructure (Proposal for the Integration phase of a Basic Service in Base4NFDI)},

rights = {Creative Commons Attribution 4.0 International},

url = {https://zenodo.org/doi/10.5281/zenodo.15088675},

doi = {10.5281/ZENODO.15088675},

abstract = {The {KGI}4NFDI (Knowledge Graph Infrastructure for the German National Research Data Infrastructure) aims to support the creation, discovery, connection, and use of {KGs} within the {NFDI} ecosystem, {EOSC}, and beyond. This Basic Service builds upon the achievements of the Initialisation Phase and addresses the increasing demand for {KG} deployment, a central {KG} Hub, interoperability, and community engagement. In this context, an incubator program will enable projects to generate and maintain {KGs} supported by {KGI}4NFDI, facilitating decentralised {KG} instances based on standards and tried-and-tested approaches. Furthermore, Registry and Hub services are refined to provide a more user-friendly interface for querying across different {KGs} with improved semantic interoperability. Consultancy services will be expanded to actively engage the {NFDI} community in the creation and use of {KGs} through various initiatives, including workshops, webinars, and dedicated events. Our approach is expected to contribute significantly to the vision of “One {NFDI}” by promoting the standardisation practices that enhance data integration capabilities. We also align with prevalent international initiatives such as the European Open Science Cloud ({EOSC}), creating a sustainable {KG} infrastructure. Feedback from the Initialisation phase offered valuable insights from the {NFDI} community, some aligning with the Initialisation phase's scope and others thoughtfully incorporated into the proposal for the Integration phase.},

author = {Sauerwein, Till and Rossenova, Lozana and Shigapov, Renat and Schubotz, Moritz and Limani, Fidan and Zapilko, Benjamin and Elhossary, Muhammad and Mietchen, Daniel and Förstner, Konrad U.},

urldate = {2026-02-06},

date = {2025-01-23},

keywords = {!ms\_author},

}

@article{AgricolaHSS25,

title = {Fraudulent Publishing in the Mathematical Sciences},

volume = {72},

issn = {1088-9477, 0002-9920},

url = {https://www.ams.org/journals/notices/202509/noti3217/noti3217.html?type=.html},

doi = {10.1090/noti3217},

number = {9},

journaltitle = {Notices of the American Mathematical Society},

shortjournal = {Notices Amer. Math. Soc.},

author = {Agricola, Ilka and Heller, Lynn and Schilders, Wil and Schubotz, Moritz and Taylor, Peter and Vega, Luis},

urldate = {2026-02-06},

date = {2025-10},

langid = {english},

keywords = {!ms\_author},

}

@misc{NeumannLSF25,

title = {Optimizing Small Transformer-Based Language Models for Multi-Label Sentiment Analysis in Short Texts},

rights = {Creative Commons Attribution 4.0 International},

url = {https://arxiv.org/abs/2509.04982},

doi = {10.48550/ARXIV.2509.04982},

abstract = {Sentiment classification in short text datasets faces significant challenges such as class imbalance, limited training samples, and the inherent subjectivity of sentiment labels -- issues that are further intensified by the limited context in short texts. These factors make it difficult to resolve ambiguity and exacerbate data sparsity, hindering effective learning. In this paper, we evaluate the effectiveness of small Transformer-based models (i.e., {BERT} and {RoBERTa}, with fewer than 1 billion parameters) for multi-label sentiment classification, with a particular focus on short-text settings. Specifically, we evaluated three key factors influencing model performance: (1) continued domain-specific pre-training, (2) data augmentation using automatically generated examples, specifically generative data augmentation, and (3) architectural variations of the classification head. Our experiment results show that data augmentation improves classification performance, while continued pre-training on augmented datasets can introduce noise rather than boost accuracy. Furthermore, we confirm that modifications to the classification head yield only marginal benefits. These findings provide practical guidance for optimizing {BERT}-based models in resource-constrained settings and refining strategies for sentiment classification in short-text datasets.},

publisher = {{arXiv}},

author = {Neumann, Julius and Lange, Robert and Susanti, Yuni and Färber, Michael},

urldate = {2026-02-06},

date = {2025},

keywords = {!ms\_author, Computation and Language (cs.{CL}), {FOS}: Computer and information sciences, Information Retrieval (cs.{IR}), Machine Learning (cs.{LG})},

}

@article{MietchenS25,

title = {Analyzing the reproducibility of research-related Jupyter notebooks at scale},

issn = {1617-5468},

url = {https://dl.gi.de/handle/20.500.12116/45813},

doi = {10.18420/SE2025-07},

abstract = {We address computational reproducibility of publication-associated Jupyter notebooks at 3 levels: (i) using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks associated with publications indexed in the biomedical literature repository {PubMed} Central. We identified such notebooks by mining the article’s full text, trying to locate them on {GitHub}, and attempting to rerun them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. (ii) This study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on {PubMed} Central over the course of 2 years, during which the corpus of Jupyter notebooks from articles indexed in {PubMed} Central has grown in a highly dynamic fashion. (iii) We imported the corpus into a knowledge graph with a public {SPARQL} endpoint that allows for fine-grained exploration of notebooks individually or in aggregation (e.g. by topic, by journal or by error type). In this talk, we zoom in on common problems and practices, highlight trends, and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.},

author = {Mietchen, Daniel and Samuel, Sheeba},

urldate = {2026-02-06},

date = {2025},

langid = {english},

keywords = {!ms\_author, Computational reproducibility, {FAIR} data, {GitHub}, Jupyter notebooks, Knowledge Graph, {PubMed} Central, Python, {SPARQL}},

}

@inproceedings{DebBPE24,

location = {Hong Kong China},

title = {An Overview of {zbMATH} Open Digital Library},

isbn = {979-8-4007-1093-3},

url = {https://dl.acm.org/doi/10.1145/3677389.3702597},

doi = {10.1145/3677389.3702597},

eventtitle = {{JCDL} '24: 24th {ACM}/{IEEE} Joint Conference on Digital Libraries},

pages = {1--5},

booktitle = {Proceedings of the 24th {ACM}/{IEEE} Joint Conference on Digital Libraries},

publisher = {{ACM}},

author = {Deb, Madhurima and Beckenbach, Isabel and Petrera, Matteo and Ehsani, Dariush and Fuhrmann, Marcel and Hao, Yun and Teschke, Olaf and Schubotz, Moritz},

urldate = {2026-02-06},

date = {2024-12-16},

langid = {english},

keywords = {!ms\_author},

}

@article{RossenovaSS23,

title = {The Case for a Common, Reusable Knowledge Graph Infrastructure for {NFDI}},

volume = {1},

issn = {2941-296X},

url = {https://www.tib-op.org/ojs/index.php/CoRDI/article/view/266},

doi = {10.52825/cordi.v1i.266},

abstract = {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.},

journaltitle = {Proceedings of the Conference on Research Data Infrastructure},

shortjournal = {Proc Conf Res Data Infrastr},

author = {Rossenova, Lozana and Schubotz, Moritz and Shigapov, Renat},

urldate = {2023-10-20},

date = {2023-09-07},

keywords = {!ms\_author},

}

@inproceedings{ScharpfSSG23,

title = {{PhysWikiQuiz} - An {AI}-Aided Collaborative Physics Exam Question Generation and Test System for Teachers and Students},

booktitle = {Interactive Events at the 24th International Conference on Artificial Intelligence in Education ({AIED}) 2023},

author = {Scharpf, Philipp and Schubotz, Moritz and Spitz, Andreas and Greiner-Petter, Andre and Gipp, Bela},

date = {2023-07},

note = {Place: Tokyo, Japan and virtual (synchronous hybrid)

tex.topic: mathir},

keywords = {!ms\_author, no-doi},

topic = {mathir},

}

@inproceedings{SatputeGSM23,

title = {{TEIMMA}: The First Content Reuse Annotator for Text, Images, and Math},

doi = {10.1109/JCDL57899.2023.00056},

booktitle = {2023 {ACM}/{IEEE} Joint Conference on Digital Libraries ({JCDL})},

author = {Satpute, Ankit and Greiner-Petter, Andre and Schubotz, Moritz and Meuschke, Norman and Aizawa, Akiko and Teschke, Olaf and Gipp, Bela},

date = {2023-06},

note = {Place: Santa Fe, New Mexico, {USA}

tex.topic: pd

{QID}: Q122926591},

keywords = {!ms\_author},

topic = {pd},

}

@article{GreinerPetterSBS23,

title = {Do the Math: Making Mathematics in Wikipedia Computable},

volume = {45},

issn = {0162-8828, 2160-9292, 1939-3539},

url = {https://ieeexplore.ieee.org/document/9847017/},

doi = {10.1109/TPAMI.2022.3195261},

shorttitle = {Do the Math},

abstract = {Wikipedia combines the power of {AI} solutions and human reviewers to safeguard article quality. Quality control objectives include detecting malicious edits, fixing typos, and spotting inconsistent formatting. However, no automated quality control mechanisms currently exist for mathematical formulae. Spell checkers are widely used to highlight textual errors, yet no equivalent tool exists to detect algebraically incorrect formulae. Our paper addresses this shortcoming by making mathematical formulae computable.

We present a method that (1) gathers the semantic information surrounding the context of each mathematical formulae, (2) provides access to the information in a graph-structured dependency hierarchy, and (3) performs automatic plausibility checks on equations. We evaluate the performance of our approach on 6,337 mathematical expressions contained in 104 Wikipedia articles on the topic of orthogonal polynomials and special functions. Our system, {LaCASt}, verified 358 out of 1,516 equations as error-free. {LaCASt} successfully translated 27\% of the mathematical expressions and outperformed existing translation approaches by 16\%. Additionally, {LaCASt} achieved an F1 score of .495 for annotating mathematical expressions with relevant textual descriptions, which is a significant step towards advancing searchability, readability, and accessibility of mathematical formulae in Wikipedia.

A prototype of {LaCASt} and the semantically enhanced Wikipedia articles are available at: https://tpami.wmflabs.org.},

pages = {1--12},

number = {4},

journaltitle = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence},

shortjournal = {{IEEE} Trans. Pattern Anal. Mach. Intell.},

author = {Greiner-Petter, Andre and Schubotz, Moritz and Breitinger, Corinna and Scharpf, Philipp and Aizawa, Akiko and Gipp, Bela},

urldate = {2022-10-03},

date = {2023-04},

note = {tex.keywords: top

{QID}: Q115649438},

keywords = {!ms\_author},

keywords = {top},

}

@report{GippGSM23,

title = {Final Report for the {DFG}-Project Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation- and Assistance-Systems},

rights = {Creative Commons Attribution 4.0 International, Open Access},

doi = {10.5281/ZENODO.7924634},

abstract = {This project investigated new approaches and technologies to enhance the accessibility of mathematical content and its semantic information for a broad range of information retrieval applications. To achieve this goal, the project addressed three main research challenges: (1) syntactic analysis of mathematical expressions, (2) semantic enrichment of mathematical expressions, and (3) evaluation using quality metrics and demonstrators. To make our research useful for the research community, we published tools that enable researchers to process mathematical expressions more effectively and efficiently. The project has made significant research contributions to various Mathematical Information Retrieval ({MathIR}) tasks and systems, including plagiarism detection and recommendation systems, search engines, the first mathematical type assistance system, math question answering and tutoring systems, automatic plausibility checks for mathematical expressions on Wikipedia, automatic computability of mathematical content via Computer Algebra Systems ({CAS}), and others. Although our project focused on {MathIR} tasks, its impact on other natural language research was significant, leading to a more extensive range of demonstrators than originally expected. Many of these demonstrators introduced novel applications, such as the tutoring system {PhysWikiQuiz} or {LaCASt}, which automatically verifies the correctness of math formulae on Wikipedia or the Digital Library of Mathematical Functions ({DLMF}) via commercial {CAS}. During the project, we published 29 peer-reviewed articles in international venues, including prestigious conferences like the Joint Conference on Digital Libraries ({JCDL}) and The Web Conference ({WWW}) ({CORE} rank A*), as well as journals such as {IEEE} Transactions on Pattern Analysis and Machine Intelligence ({TPAMI}) ({IF}: 24.314) and Scientometrics ({IF}: 3.801). Our Wikipedia demonstrator was also featured in public media. Furthermore, we actively presented our contributions, especially demonstrators, to the research community in multiple workshops. This project has strengthened our international collaborations, particularly with colleagues at the National Institute of Standards and Technology ({NIST}) in the {US} and the National Institute of Informatics ({NII}) in Japan. Several subprojects were partially developed in course projects and theses at the Universities of Konstanz, Wuppertal, and Göttingen, exposing junior researchers to cutting-edge technologies and sensitizing students and researchers to the outstanding issues in {MathIR} technologies. We firmly believe that this project will have a lasting effect on following {MathIR} technologies. Several of the subprojects initiated as part of this grant are ongoing and motivating follow-up {DFG} projects, such as Analyzing Mathematics to Detect Disguised Academic Plagiarism (project no. 437179652).},

institution = {University of Goettingen},

author = {Gipp, Bela and Greiner-Petter, André and Schubotz, Moritz and Meuschke, Norman},

urldate = {2023-05-15},

date = {2023-03-27},

langid = {english},

keywords = {!ms\_author, no-doi},

}

@article{HeckSRS23,

title = {Bootstrapping the Open Science culture: The fellowship approach},

volume = {9},

issn = {2367-7163},

url = {https://riojournal.com/article/103675/},

doi = {10.3897/rio.9.e103675},

shorttitle = {Bootstrapping the Open Science culture},

pages = {e103675},

journaltitle = {Research Ideas and Outcomes},

shortjournal = {{RIO}},

author = {Heck, Tamara and Steinhardt, Isabel and Rahal, Rima-Maria and Schubotz, Moritz and Scholl, Dominik and Behrens, Sarah},

urldate = {2023-10-03},

date = {2023-03-21},

note = {{QID}: Q117236770},

keywords = {!ms\_author},

}

@report{GippGSM23a,

title = {Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation- and Assistance-Systems},

type = {Final Report for {DFG}-funded Project},

author = {Gipp, Bela and Greiner-Petter, André and Schubotz, Moritz and Meuschke, Norman},

date = {2023-03},

keywords = {!ms\_author, no-doi},

}

@article{IhleTSM23,

title = {Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature Review},

issn = {0360-0300, 1557-7341},

url = {https://dl.acm.org/doi/10.1145/3578581},

doi = {10.1145/3578581},

abstract = {Centralized networks inevitably exhibit single points of failure that malicious actors regularly target. Decentralized networks are more resilient if numerous participants contribute to the network’s functionality. Most decentralized networks employ incentive mechanisms to coordinate the participation and cooperation of peers and thereby ensure the functionality and security of the network. This article systematically reviews incentive mechanisms for decentralized networks and networked systems by covering 165 prior literature reviews and 178 primary research papers published between 1993 and October 2022. Of the considered sources, we analyze eleven literature reviews and 105 primary research papers in detail by categorizing and comparing the distinctive properties of the presented incentive mechanisms. The reviewed incentive mechanisms establish fairness and reward participation and cooperative behavior. We review work that substitutes central authority through independent and subjective mechanisms run in isolation at each participating peer and work that applies multiparty computation. We use monetary, reputation, and service rewards as categories to differentiate the implementations and evaluate each incentive mechanism’s data management, attack resistance, and contribution model. Further, we highlight research gaps and deficiencies in reproducibility and comparability. Finally, we summarize our assessments and provide recommendations to apply incentive mechanisms to decentralized networks that share computational resources.},

pages = {3578581},

journaltitle = {{ACM} Computing Surveys},

shortjournal = {{ACM} Comput. Surv.},

author = {Ihle, Cornelius and Trautwein, Dennis and Schubotz, Moritz and Meuschke, Norman and Gipp, Bela},

urldate = {2023-04-25},

date = {2023-01-24},

langid = {english},

note = {{QID}: Q122926585},

keywords = {!ms\_author},

}

@article{ScharpfSCB23,

title = {Discovery and Recognition of Formula Concepts using Machine Learning},

volume = {128},

issn = {0138-9130, 1588-2861},

url = {https://link.springer.com/10.1007/s11192-023-04667-9},

doi = {10.1007/s11192-023-04667-9},

abstract = {Abstract

Citation-based Information Retrieval ({IR}) methods for scientific documents have proven effective for {IR} applications, such as Plagiarism Detection or Literature Recommender Systems in academic disciplines that use many references. In science, technology, engineering, and mathematics, researchers often employ mathematical concepts through formula notation to refer to prior knowledge. Our long-term goal is to generalize citation-based {IR} methods and apply this generalized method to both classical references and mathematical concepts. In this paper, we suggest how mathematical formulas could be cited and define a Formula Concept Retrieval task with two subtasks: Formula Concept Discovery ({FCD}) and Formula Concept Recognition ({FCR}). While {FCD} aims at the definition and exploration of a ‘Formula Concept’ that names bundled equivalent representations of a formula, {FCR} is designed to match a given formula to a prior assigned unique mathematical concept identifier. We present machine learning-based approaches to address the {FCD} and {FCR} tasks. We then evaluate these approaches on a standardized test collection ({NTCIR} {arXiv} dataset). Our {FCD} approach yields a precision of 68\% for retrieving equivalent representations of frequent formulas and a recall of 72\% for extracting the formula name from the surrounding text. {FCD} and {FCR} enable the citation of formulas within mathematical documents and facilitate semantic search and question answering, as well as document similarity assessments for plagiarism detection or recommender systems.},

pages = {4971--5025},

number = {9},

journaltitle = {Scientometrics},

shortjournal = {Scientometrics},

author = {Scharpf, Philipp and Schubotz, Moritz and Cohl, Howard S. and Breitinger, Corinna and Gipp, Bela},

urldate = {2024-03-13},

date = {2023-09},

langid = {english},

note = {{QID}: Q122926584

tex.ids= Scharpf2023

tex.topic: mathir},

keywords = {!ms\_author},

topic = {mathir},

}

@inproceedings{PetersenSGG23,

location = {Toronto, Canada},

title = {Neural Machine Translation for Mathematical Formulae},

url = {https://aclanthology.org/2023.acl-long.645},

doi = {10.18653/v1/2023.acl-long.645},

pages = {11534--11550},

booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), {ACL} 2023, Toronto, Canada, July 9-14, 2023},

publisher = {Association for Computational Linguistics},

author = {Petersen, Felix and Schubotz, Moritz and Greiner-Petter, André and Gipp, Bela},

editor = {Rogers, Anna and Boyd-Graber, Jordan L. and Okazaki, Naoaki},

date = {2023},

langid = {english},

note = {{QID}: Q122926589

tex.ids= {PetersenSGG}23

tex.bibsource: dblp computer science bibliography, https://dblp.org

tex.biburl: https://dblp.org/rec/conf/acl/{PetersenSGG}23.bib

tex.timestamp: Thu, 10 Aug 2023 12:35:43 +0200},

keywords = {!ms\_author},

bibsource = {dblp computer science bibliography, https://dblp.org},

biburl = {https://dblp.org/rec/conf/acl/PetersenSGG23.bib},

timestamp = {Thu, 10 Aug 2023 12:35:43 +0200},

}

@article{AzzouzThuderozST22,

title = {Sustaining the {swMATH} project: Integration into {zbMATH} Open interface and Open Data perspectives},

issn = {2747-7894, 2747-7908},

url = {https://euromathsoc.org/magazine/articles/118},

doi = {10.4171/mag/118},

shorttitle = {Sustaining the {swMATH} project},

pages = {62--64},

number = {126},

journaltitle = {European Mathematical Society Magazine},

shortjournal = {Eur. Math. Soc. Mag.},

author = {Azzouz-Thuderoz, Maxence and Schubotz, Moritz and Teschke, Olaf},

urldate = {2023-07-27},

date = {2022-12-14},

note = {{QID}: Q122926735},

keywords = {!ms\_author},

}

@inproceedings{TrautweinRTC22,

location = {Amsterdam, Netherlands},

title = {Design and Evaluation of {IPFS}: A Storage Layer for the Decentralized Web},

doi = {10.1145/3544216.3544232},

booktitle = {{ACM} {SIGCOMM} 2022 Conference ({SIGCOMM} '22)},

publisher = {{ACM}},

author = {Trautwein, Dennis and Raman, Aravindh and Tyson, Gareth and Castro, Ignacio and Scott, Will and Schubotz, Moritz and Gipp, Bela and Psaras, Yiannis},

date = {2022-08},

note = {tex.topic: blockchain

{QID}: Q122926731},

keywords = {!ms\_author},

topic = {blockchain},

}

@inproceedings{IhleDSG22,

location = {Bologna, Italy},

title = {Towards Portable Identities in the Matrix Protocol},

doi = {10.1109/ICDCSW56584.2022.00025},

booktitle = {2022 {IEEE} 42nd International Conference on Distributed Computing Systems Workshops ({ICDCSW})},

publisher = {{IEEE}},

author = {Ihle, Cornelius and Deifuss, Fabian and Schubotz, Moritz and Gipp, Bela},

date = {2022-07},

note = {tex.topic: misc

{QID}: Q122926736},

keywords = {!ms\_author},

topic = {misc},

}

@inproceedings{ScharpfSG22,

location = {Cologne Germany},

title = {Mining mathematical documents for question answering via unsupervised formula labeling},

isbn = {978-1-4503-9345-4},

url = {https://dl.acm.org/doi/10.1145/3529372.3530925},

doi = {10.1145/3529372.3530925},

eventtitle = {{JCDL} '22: The {ACM}/{IEEE} Joint Conference on Digital Libraries in 2022},

pages = {1--11},

booktitle = {Proceedings of the 22nd {ACM}/{IEEE} Joint Conference on Digital Libraries},

publisher = {{ACM}},

author = {Scharpf, Philipp and Schubotz, Moritz and Gipp, Bela},

urldate = {2022-10-24},

date = {2022-06-20},

langid = {english},

note = {tex.keywords: top

{QID}: Q122926704},

keywords = {!ms\_author},

keywords = {top},

}

@inproceedings{GreinerPetterCYS22,

location = {Munich, Germany},

title = {Comparative Verification of the Digital Library of Mathematical Functions and Computer Algebra Systems},

url = {https://arxiv.org/abs/2201.09488},

doi = {10.1007/978-3-030-99524-9_5},

series = {Lecture Notes in Computer Science},

abstract = {Digital mathematical libraries assemble the knowledge of years of mathematical research. Numerous disciplines (e.g., physics, engineering, pure and applied mathematics) rely heavily on compendia gathered findings. Likewise, modern research applications rely more and more on computational solutions, which are often calculated and verified by computer algebra systems. Hence, the correctness, accuracy, and reliability of both digital mathematical libraries and computer algebra systems is a crucial attribute for modern research.

In this paper, we present a novel approach to verify a digital mathematical library and two computer algebra systems with one another by converting mathematical expressions from one system to the other. We use our previously developed conversion tool (referred to as {LaCASt}) to translate formulae from the {NIST} Digital Library of Mathematical Functions to the computer algebra systems Maple and Mathematica. The contributions of our presented work are as follows: (1) we present the most comprehensive verification of computer algebra systems and digital mathematical libraries with one another; (2) we significantly enhance the performance of the underlying translator in terms of coverage and accuracy; and (3) we provide open access to translations for Maple and Mathematica of the formulae in the {NIST} Digital Library of Mathematical Functions.},

eventtitle = {{TACAS}},

pages = {87--105},

booktitle = {Tools and Algorithms for the Construction and Analysis of Systems - 28th International Conference, ({TACAS})},

publisher = {Springer},

author = {Greiner-Petter, André and Cohl, Howard S. and Youssef, Abdou and Schubotz, Moritz and Trost, Avi and Dey, Rajen and Aizawa, Akiko and Gipp, Bela},

date = {2022-04},

note = {tex.keywords: top

{QID}: Q122926706},

keywords = {!ms\_author},

keywords = {top},

}

@article{SchubotzSGA22,

title = {Caching and Reproducibility: Making Data Science Experiments Faster and {FAIRer}},

volume = {7},

url = {https://www.frontiersin.org/article/10.3389/frma.2022.861944},

doi = {10.3389/frma.2022.861944},

journaltitle = {Frontiers in Research Metrics and Analytics},

author = {Schubotz, Moritz and Satpute, Ankit and Greiner-Petter, Andre and Aizawa, Akiko and Gipp, Bela},

date = {2022},

note = {tex.topic: misc

{QID}: Q112683183},

keywords = {!ms\_author},

topic = {misc},

}

@inproceedings{ScharpfSSG22,

location = {Virtual Event China},

title = {Collaborative and {AI}-aided Exam Question Generation using Wikidata in Education},

volume = {3262},

url = {http://ceur-ws.org/Vol-3262/paper13.pdf},

series = {{CEUR} Workshop Proceedings},

eventtitle = {Wikidata Workshop @ {ISWC}},

booktitle = {Proceedings of the 3rd Wikidata Workshop 2022 co-located with the 21st International Semantic Web Conference ({ISWC})},

publisher = {{CEUR}-{WS}.org},

author = {Scharpf, Philipp and Schubotz, Moritz and Spitz, Andreas and Greiner-Petter, André and Gipp, Bela},

date = {2022},

keywords = {!ms\_author, no-doi, ⛔ No {DOI} found},

}

@inproceedings{StegmuellerBMR21,

location = {Illinois, {USA}},

title = {Detecting Cross-Language Plagiarism using Open Knowledge Graphs},

doi = {10.6084/m9.figshare.17212340.v3},

booktitle = {2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents ({EEKE}2021) at the {ACM}/{IEEE} Joint Conference on Digital Libraries 2021 ({JCDL}2021), Online},

publisher = {{ACM}},

author = {Stegmueller, Johannes and Bauer-Marquart, Fabian and Meuschke, Norman and Ruas, Terry and Schubotz, Moritz and Gipp, Bela},

date = {2021-09},

note = {tex.topic: pd

{QID}: Q122926738},

keywords = {!ms\_author},

topic = {pd},

}

@inproceedings{BeckSSM21a,

title = {Strategies to Record, Annotate and Visualize and Parallel Structures in {XML} Documents},

booktitle = {Proceedings of the {ACM}/{IEEE} Joint Conference on Digital Libraries ({JCDL})},

author = {Beck, Marco and Schubotz, Moritz and Stange, Vincent and Meuschke, Norman and Gipp, Bela},

date = {2021-09},

note = {tex.topic: misc},

keywords = {!ms\_author, !nm\_author, no-doi},

topic = {misc},

}

@article{SchubotzT21,

title = {{zbMATH} Open: Towards standardized machine interfaces to expose bibliographic metadata},

issn = {2747-7894, 2747-7908},

url = {https://ems.press/doi/10.4171/mag/12},

doi = {10.4171/mag/12},

shorttitle = {{zbMATH} Open},

pages = {50--53},

number = {119},

journaltitle = {European Mathematical Society Magazine},

shortjournal = {Eur. Math. Soc. Mag.},

author = {Schubotz, Moritz and Teschke, Olaf},

urldate = {2023-10-03},

date = {2021-06-14},

note = {{QID}: Q122746482},

keywords = {!ms\_author},

}

@inproceedings{TrautweinSG21,

location = {Espoo and Helsinki, Finland},

title = {Introducing Peer Copy - A Fully Decentralized Peer-to-Peer File Transfer Tool},

doi = {10.23919/IFIPNetworking52078.2021.9472842},

booktitle = {2021 {IFIP} Networking Conference ({IFIP} Networking)},

publisher = {{IEEE}},

author = {Trautwein, Dennis and Schubotz, Moritz and Gipp, Bela},

date = {2021-06},

note = {tex.topic: blockchain

tex.core: A;Core Rank A;http://portal.core.edu.au/conf-ranks/806/

{QID}: Q122926733},

keywords = {!dt, !ms\_author, decentralized\_open\_science},

topic = {blockchain},

core = {A;Core Rank A;http://portal.core.edu.au/conf-ranks/806/},

}

@inproceedings{ScharpfSG21,

location = {Ljubljana Slovenia},

title = {Fast Linking of Mathematical Wikidata Entities in Wikipedia Articles Using Annotation Recommendation},

isbn = {978-1-4503-8313-4},

url = {https://doi.org/10.1145/3442442.3452348},

doi = {10.1145/3442442.3452348},

eventtitle = {{WWW} '21: The Web Conference 2021},

pages = {602--609},

booktitle = {Companion of The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021},

publisher = {{ACM} / {IW}3C2},

author = {Scharpf, Philipp and Schubotz, Moritz and Gipp, Bela},

editor = {Leskovec, Jure and Grobelnik, Marko and Najork, Marc and Tang, Jie and Zia, Leila},

date = {2021-04-19},

langid = {english},

note = {tex.ids= {ScharpfSG}21b

{QID}: Q122926724},

keywords = {!ms\_author, {SchubotzCV}},

}

@misc{SchubotzTT21,

title = {{zbMATH} is open: a practical guide to open an information service},

url = {https://doi.org/10.5281/zenodo.4646668},

doi = {10.5281/zenodo.4646668},

publisher = {Zenodo},

author = {Schubotz, Moritz and Trautwein, Dennis and Teschke, Olaf},

date = {2021-03},

keywords = {!ms\_author, no-doi},

}

@article{CohlTS21,

title = {Connecting Islands: Bridging {zbMATH} and {DLMF} with Scholix, a blueprint for connecting expert knowledge systems},

issn = {2747-7894, 2747-7908},

url = {https://ems.press/doi/10.4171/mag/35},

doi = {10.4171/mag/35},

shorttitle = {Connecting Islands},

pages = {66--67},

number = {120},

journaltitle = {European Mathematical Society Magazine},

shortjournal = {Eur. Math. Soc. Mag.},

author = {Cohl, Howard S. and Teschke, Olaf and Schubotz, Moritz},

urldate = {2023-04-15},

date = {2021-07},

note = {{QID}: Q122926730},

keywords = {!ms\_author},

}

@incollection{DeifussISG21,

location = {Glückstadt},

title = {procd: A privacy-preserving robust implementation to discover contacts in social networks},

volume = {74},

url = {https://epub.uni-regensburg.de/44954/},

doi = {10.5283/EPUB.44954},

series = {Schriften zur informationswissenschaft},

abstract = {Current instant messengers store the users? phone book contacts typically unencrypted or hashed on a central server. In case of a server?s corruption, all contacts are either directly available in plaintext or can be unmasked using a simple dictionary attack. To solve this problem, we present procd [p?o?st], a python implementation for privacy preserving contact discovery. procd is a trustless solution that requires neither plaintext numbers nor hashes of single phone numbers to retrieve contacts. Instead, we transfer hashed combinations of multiple phone numbers, which increases the effort for dictionary attacks to an unfeasible level using today?s hardware.},

pages = {363--368},

booktitle = {Information between data and knowledge},

publisher = {Proceedings of the 16th International Symposium of Information Science ({ISI} 2021)},

author = {Deifuß, Fabian and Ihle, Cornelius and Schubotz, Moritz and Gipp, Bela},

date = {2021},

note = {tex.preprint: https://www.gipp.com/wp-content/papercite-data/pdf/deifuss2021.pdf},

keywords = {!ci, !ci\_author, !ms\_author, decentralized\_open\_science, no-doi, private contact discovery, private information retrieval, private set intersection, secure multiparty computation},

preprint = {https://www.gipp.com/wp-content/papercite-data/pdf/deifuss2021.pdf},

}

@inproceedings{vonTottlebenISG21,

location = {New York, {NY}, {USA}},

title = {Academic Storage Cluster},

doi = {10.1109/jcdl52503.2021.00034},

abstract = {Decentralized storage is still rarely used in an academic and educational environment, although it offers better availability than conventional systems. It still happens that data is not available at a certain time due to heavy load or maintenance on the university servers. In such cases, a decentralized solution can help keep the data available and distribute the load among several peers. In our experiment, we created a cluster of containers in Docker to evaluate a private {IPFS} cluster for an academic data store focusing on availability, {GET}/{PUT} performance, and storage needs. As sample data, we used {PDF} files to analyze the data transport in our peer-to-peer network with Wireshark. We found that a bandwidth of at least 100 kbps is required for {IPFS} to function but recommend at least 1000 kbps for smooth operation. Also, the hard disk and memory size should be adapted to the data. Other limiting factors such as {CPU} processing power and delay in the internet connection did not affect the operation of the {IPFS} cluster.},

booktitle = {Proceedings of the {ACM}/{IEEE} joint conference on digital libraries in 2021},

publisher = {Association for Computing Machinery},

author = {von Tottleben, Alexander and Ihle, Cornelius and Schubotz, Moritz and Gipp, Bela},

date = {2021},

note = {{QID}: Q122926700},

keywords = {!ci, !ci\_author, !ms\_author, decentralized\_open\_science},

}

@inproceedings{TrautweinSG21a,

title = {Leveraging Node Heterogeneity to Improve Content Discovery and Content Retrieval in Peer-To-Peer Networks},

isbn = {978-1-4503-9133-7},

doi = {10.1145/3488658.3493781},

booktitle = {{CoNEXT} Student Workshop 2021 ({CoNEXT}-{SW}'21), December 7, 2021, Virtual Event, Germany},

author = {Trautwein, Dennis and Schubotz, Moritz and Gipp, Bela},

date = {2021},

note = {tex.topic: blockchain

{QID}: Q122926740},

keywords = {!ms\_author},

topic = {blockchain},

}

@inproceedings{ScharpfSG21a,

title = {Mathematics in Wikidata},

volume = {2982},

url = {http://ceur-ws.org/Vol-2982/paper-1.pdf},

series = {{CEUR} Workshop Proceedings},

eventtitle = {Wikidata Workshop (Wikidata 2021)},

booktitle = {Proceedings of the 2nd Wikidata Workshop (Wikidata 2021) co-located with the 20th International Semantic Web Conference \{({ISWC}\} 2021)},

publisher = {{CEUR}-{WS}.org},

author = {Scharpf, Philipp and Schubotz, Moritz and Gipp, Bela},

date = {2021},

keywords = {!ms\_author, no-doi, ⛔ No {DOI} found},

}

@inproceedings{PetreraTBE21,

title = {{zbMATH} Open: {API} Solutions and Research Challenges},

volume = {2976},

url = {http://ceur-ws.org/Vol-2976/paper-1.pdf},

series = {{CEUR} Workshop Proceedings},

pages = {4--13},

booktitle = {Proceedings of the Workshop on Digital Infrastructures for Scholarly Content Objects ({DISCO} 2021) co-located with {ACM}/{IEEE} Joint Conference on Digital Libraries 2021 ({JCDL} 2021), Online (due to the global pandemic), September 30, 2021},

publisher = {{CEUR}-{WS}.org},

author = {Petrera, Matteo and Trautwein, Dennis and Beckenbach, Isabel and Ehsani, Dariush and Müller, Fabian and Teschke, Olaf and Gipp, Bela and Schubotz, Moritz},

editor = {Balke, Wolf-Tilo and de Waard, Anita and Fu, Yuanxi and Hua, Bolin and Schneider, Jodi and Song, Ningyuan and Wang, Xiaoguang},

date = {2021},

note = {tex.topic: mathir},

keywords = {!ms\_author, no-doi, ⛔ No {DOI} found},

topic = {mathir},

}

@incollection{HamborgMSS21,

title = {{NewsDeps}: Visualizing the Origin of Information in News Articles},

isbn = {978-3-658-32957-0},

doi = {10.1007/978-3-658-32957-0},

booktitle = {Wahrheit und Fake im postfaktisch-digitalen Zeitalter},

publisher = {Springer Vieweg},

author = {Hamborg, Felix and Meschenmoser, Philipp and Schubotz, Moritz and Scharpf, Philipp and Gipp, Bela},

editor = {Klimczak, Peter and Zoglauer, Thomas},

date = {2021},

note = {tex.topic: newsanalysis},

keywords = {!ms\_author, no-doi},

topic = {newsanalysis},

}

@inproceedings{ArndtIRS21,

location = {Cham},

title = {10 Years Later: The Mathematics Subject Classification and Linked Open Data},

isbn = {978-3-030-81097-9},

abstract = {Ten years ago, the Mathematics Subject Classification {MSC} 2010 was released, and a corresponding machine-readable Linked Open Data collection was published using the Simple Knowledge Organization System ({SKOS}). Now, the new {MSC} 2020 is out.},

pages = {153--158},

booktitle = {Intelligent Computer Mathematics},

publisher = {Springer International Publishing},

author = {Arndt, Susanne and Ion, Patrick and Runnwerth, Mila and Schubotz, Moritz and Teschke, Olaf},

editor = {Kamareddine, Fairouz and Sacerdoti Coen, Claudio},

date = {2021},

keywords = {!ms\_author, no-doi},

}

@inproceedings{SchubotzGMT20,

location = {Wuhan, China},

title = {Mathematical Formulae in Wikimedia Projects 2020},

doi = {10.1145/3383583.3398557},

booktitle = {Proceedings of the {ACM}/{IEEE} Joint Conference on Digital Libraries ({JCDL})},

publisher = {{IEEE}},

author = {Schubotz, Moritz and Greiner-Petter, Andre and Meuschke, Norman and Teschke, Olaf and Gipp, Bela},

date = {2020-08},

note = {tex.topic: wiki

{QID}: Q122926734},

keywords = {!ms\_author, !nm\_author},

topic = {wiki},

}

@inproceedings{OstendorffRSR20,

location = {Virtual Event China},

title = {Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles},

isbn = {978-1-4503-7585-6},

url = {https://dl.acm.org/doi/10.1145/3383583.3398525},

doi = {10.1145/3383583.3398525},

pages = {127--136},

booktitle = {Proceedings of the {ACM}/{IEEE} Joint Conference on Digital Libraries in 2020},

publisher = {{ACM}},

author = {Ostendorff, Malte and Ruas, Terry and Schubotz, Moritz and Rehm, Georg and Gipp, Bela},

urldate = {2021-10-20},

date = {2020-08},

langid = {english},

note = {tex.ids= {OstendorffRSG}20

tex.oldkey: Ostendorff2020

tex.topic: wiki

{QID}: Q105592627},

keywords = {!bg, !bg\_author, !bg\_preprint, !ms, !ms\_author, !ms\_preprint, jabref\_imp2},

oldkey = {Ostendorff2020},

topic = {wiki},

}

@inproceedings{ScharpfSYH20,

location = {Virtual Event China},

title = {Classification and Clustering of {arXiv} Documents, Sections, and Abstracts Comparing Encodings of Natural and Mathematical Language},

rights = {All rights reserved},

isbn = {978-1-4503-7585-6},

url = {https://dl.acm.org/doi/10.1145/3383583.3398529},

doi = {10.1145/3383583.3398529},

eventtitle = {{JCDL} '20: The {ACM}/{IEEE} Joint Conference on Digital Libraries in 2020},

pages = {137--146},

booktitle = {Proceedings of the {ACM}/{IEEE} Joint Conference on Digital Libraries in 2020},

publisher = {{ACM}},

author = {Scharpf, Philipp and Schubotz, Moritz and Youssef, Abdou and Hamborg, Felix and Meuschke, Norman and Gipp, Bela},

date = {2020-06},

langid = {english},

note = {tex.ids= {ScharpfSYH}20a

tex.keywords: top

tex.oldkey: Scharpf2020

tex.topic: mathir

{QID}: Q122926716},

keywords = {!bg, !bg\_author, !fh, !fh\_author, !ms, !ms\_author, !nm, !nm\_author, \#nosource, classification, document classification, jabref\_imp1\_clean},

keywords = {top},

oldkey = {Scharpf2020},

topic = {mathir},

}

@article{GreinerPetterYRM20,

title = {Math-Word Embedding in Math Search and Semantic Extraction},

volume = {125},

issn = {0138-9130, 1588-2861},

url = {https://link.springer.com/10.1007/s11192-020-03502-9},

doi = {10.1007/s11192-020-03502-9},

abstract = {Word embedding, which represents individual words with semantically fixed-length vectors, has made it possible to successfully apply deep learning to natural language processing tasks such as semantic role-modeling, question answering, and machine translation. As math text consists of natural text, as well as math expressions that similarly exhibit linear correlation and contextual characteristics, word embedding techniques can also be applied to math documents. However, while mathematics is a precise and accurate science, it is usually expressed through imprecise and less accurate descriptions, contributing to the relative dearth of machine learning applications for information retrieval in this domain. Generally, mathematical documents communicate their knowledge with an ambiguous, context-dependent, and non-formal language. Given recent advances in word embedding, it is worthwhile to explore their use and effectiveness in math information retrieval tasks, such as math language processing and semantic knowledge extraction. In this paper, we explore math embedding by testing it on several different scenarios, namely, (1) math-term similarity, (2) analogy, (3) numerical concept-modeling based on the centroid of the keywords that characterize a concept, (4) math search using query expansions, and (5) semantic extraction, i.e., extracting descriptive phrases for math expressions. Due to the lack of benchmarks, our investigations were performed using the {arXiv} collection of {STEM} documents and carefully selected illustrations on the Digital Library of Mathematical Functions ({DLMF}: {NIST} digital library of mathematical functions. Release 1.0.20 of 2018-09-1, 2018). Our results show that math embedding holds much promise for similarity, analogy, and search tasks. However, we also observed the need for more robust math embedding approaches. Moreover, we explore and discuss fundamental issues that we believe thwart the progress in mathematical information retrieval in the direction of machine learning.},

pages = {3017--3046},

number = {3},

journaltitle = {Scientometrics},

shortjournal = {Scientometrics},

author = {Greiner-Petter, André and Youssef, Abdou and Ruas, Terry and Miller, Bruce R. and Schubotz, Moritz and Aizawa, Akiko and Gipp, Bela},

urldate = {2021-06-30},

date = {2020-06},

langid = {english},

note = {tex.ids= {GreinerPetterYRM}20

{QID}: Q122926719},

keywords = {!ag\_author, !bg\_author, !ms\_author, !tr\_author, math search, mathematical information retrieval, nlp, nlp\_embeddings},

}

@inproceedings{SchwarzkopfFPS20,

location = {Berlin, Germany},

title = {Empowering next generation open scholarship with an open science fellows program},

rights = {Creative Commons Attribution 4.0 International, Open Access},

url = {https://zenodo.org/record/3776755},

doi = {10.5281/ZENODO.3776755},

abstract = {This poster will present the main actions, the management framework and outcomes{\textless}br{\textgreater} of a scholarship program for next generation researchers, that works towards{\textless}br{\textgreater} changing the knowledge creation process so as to create natively free/open{\textless}br{\textgreater} knowledge. Over the past three years, we have developed and constantly improved{\textless}br{\textgreater} our mechanisms of capacity and community building. We hope that by demonstrating{\textless}br{\textgreater} success stories we encourage other parties to use this scholarship program as a{\textless}br{\textgreater} blueprint for other institutional, national or international activities. We will also address{\textless}br{\textgreater} the challenges of sustainable set up and stabilization, as well as creating a knowledge{\textless}br{\textgreater} hub for capacity building. The main approach of this program is to mentor researchers by acknowledged{\textless}br{\textgreater} experts in Open Science over a period of eight months. Since 2016, the program{\textless}br{\textgreater} supported over 50 junior researchers in learning how to open up their research{\textless}br{\textgreater} projects, and how to best combine requirements of traditional scholarly routines{\textless}br{\textgreater} (such as publishing in high impact journals) with those encouraged by open science{\textless}br{\textgreater} principles (e.g., sharing research data, dissemination). The fellows also act as{\textless}br{\textgreater} ambassadors for Open Science and free knowledge in their research communities{\textless}br{\textgreater} (e.g. via personal contacts, within institutional training formats, or talks at academic{\textless}br{\textgreater} societies). In addition to a financial grant, the fellows receive holistic support: they build a{\textless}br{\textgreater} network of peers, engage with one another, and receive mentoring by experts in{\textless}br{\textgreater} Open Science. They also get the chance to present their projects in non-academic{\textless}br{\textgreater} environments. While they work on their Open Science projects, they also participate{\textless}br{\textgreater} in a series of hands-on workshops (e.g. book sprints), to improve their ‘open’ skills and{\textless}br{\textgreater} abilities. The evaluation of our program indicates that our model seems to be effective for{\textless}br{\textgreater} making impact and that it has helped the fellows advancing their research: So far, we{\textless}br{\textgreater} have supported 50 researchers from various academic disciplines and the vast{\textless}br{\textgreater} majority stated that they could increase their knowledge about open science{\textless}br{\textgreater} significantly by participating in the program. Moreover, the scholarship tackles a crucial aspect of academic careers: The{\textless}br{\textgreater} competitive nature of the scientific reward and funding system often hinders broad{\textless}br{\textgreater} application of open science principles. The program’s combination of financial{\textless}br{\textgreater} support, strong community support and mentoring convincingly shows that the right{\textless}br{\textgreater} framework conditions make open science a success.},

eventtitle = {Open Science Conference},

publisher = {Zenodo},

author = {Schwarzkopf, Christopher and Fecher, Benedikt and Peters, Isabella and Schubotz, Moritz},

urldate = {2023-04-15},

date = {2020-04-30},

langid = {english},

note = {{QID}: Q122926732},

keywords = {!ms\_author},

}

@inproceedings{GreinerPetterSMB20,

location = {Taipei, Taiwan},

title = {Discovering Mathematical Objects of Interest — A Study of Mathematical Notations},

isbn = {978-1-4503-7023-3},

url = {https://arxiv.org/abs/2002.02712},

doi = {10.1145/3366423.3380218},

abstract = {Mathematical notation, i.e., the writing system used to communicate concepts in mathematics, encodes valuable information for a variety of information search and retrieval systems. Yet, mathematical notations remain mostly unutilized by today's systems. In this paper, we present the first in-depth study on the distributions of mathematical notation in two large scientific corpora: the open access {arXiv} (2.5B mathematical objects) and the mathematical reviewing service for pure and applied mathematics {zbMATH} (61M mathematical objects). Our study lays a foundation for future research projects on mathematical information retrieval for large scientific corpora. Further, we demonstrate the relevance of our results to a variety of use-cases. For example, to assist semantic extraction systems, to improve scientific search engines, and to facilitate specialized math recommendation systems.

The contributions of our presented research are as follows: (1) we present the first distributional analysis of mathematical formulae on {arXiv} and {zbMATH}; (2) we retrieve relevant mathematical objects for given textual search queries (e.g., linking \$P\_\{n\}{\textasciicircum}\{({\textbackslash}alpha, {\textbackslash}beta)\}{\textbackslash}!{\textbackslash}left(x{\textbackslash}right)\$ with `Jacobi polynomial'); (3) we extend {zbMATH}'s search engine by providing relevant mathematical formulae; and (4) we exemplify the applicability of the results by presenting auto-completion for math inputs as the first contribution to math recommendation systems. To expedite future research projects, we have made available our source code and data.},

eventtitle = {{WWW} '20},

pages = {1445--1456},

booktitle = {Proceedings of the Web Conference 2020 ({WWW}'20), April 20–24, 2020, Taipei, Taiwan},

publisher = {{ACM}},

author = {Greiner-Petter, André and Schubotz, Moritz and Müller, Fabian and Breitinger, Corinna and Cohl, Howard S. and Aizawa, Akiko and Gipp, Bela},

date = {2020-04},

langid = {english},

note = {tex.ids= {GreinerPetterSMB}20a

tex.core: 0;Core Rank A*;http://portal.core.edu.au/conf-ranks/1548/

tex.keywords: top

tex.oldkey: {GreinerPetter}2020

tex.preprint: https://ag-gipp.github.io/bib/preprints/greinerpetter2020.pdf

tex.topic: mathir

{QID}: Q122926714},

keywords = {!bg, !bg\_author, !bg\_preprint, !cb, !cb\_author, !ms, !ms\_author, !ms\_cv, !ms\_preprint, {DFG}1259-1, jabref\_imp2, old\_tex\_field\_preprint},

core = {0;Core Rank A*;http://portal.core.edu.au/conf-ranks/1548/},

keywords = {top},

oldkey = {GreinerPetter2020},

preprint = {https://ag-gipp.github.io/bib/preprints/greinerpetter2020.pdf},

topic = {mathir},

}

@inproceedings{IhleSMG20,

location = {New York, {NY}, {USA}},

title = {A first step towards content protecting plagiarism detection},

isbn = {978-1-4503-7585-6},

url = {https://doi.org/10.1145/3383583.3398620},

doi = {10.1145/3383583.3398620},

series = {{JCDL} '20},

abstract = {Plagiarism detection systems are essential tools for safeguarding academic and educational integrity. However, today's systems require disclosing the full content of the input documents and the document collection to which the input documents are compared. Moreover, the systems are centralized and under the control of individual, typically commercial providers. This situation raises procedural and legal concerns regarding the confidentiality of sensitive data, which can limit or prohibit the use of plagiarism detection services. To eliminate these weaknesses of current systems, we seek to devise a plagiarism detection approach that does not require a centralized provider nor exposing any content as cleartext. This paper presents the initial results of our research. Specifically, we employ Private Set Intersection to devise a content-protecting variant of the citation-based similarity measure Bibliographic Coupling implemented in our plagiarism detection system {HyPlag}. Our evaluation shows that the content-protecting method achieves the same detection effectiveness as the original method while making common attacks to disclose the protected content practically infeasible. Our future work will extend this successful proof-of-concept by devising plagiarism detection methods that can analyze the entire content of documents without disclosing it as cleartext.},

pages = {341--344},

booktitle = {Proceedings of the {ACM}/{IEEE} joint conference on digital libraries in 2020},

publisher = {Association for Computing Machinery},

author = {Ihle, Cornelius and Schubotz, Moritz and Meuschke, Norman and Gipp, Bela},

date = {2020},

note = {tex.ids: {IhleSMG}20a

tex.oldkey: Ihle2020

tex.topic: pd

tex.core: A*;Core Rank A*;http://portal.core.edu.au/conf-ranks/2085/

tex.preprint: https://www.gipp.com/wp-content/papercite-data/pdf/ihle2020.pdf

{QID}: Q122926697},

keywords = {!bg, !bg\_author, !ci, !ci\_author, !ms, !ms\_author, !nm, !nm\_author, \#nosource, decentralized\_open\_science, jabref\_imp1\_clean, plagiarism detection, private computation, similarity detection},

ids = {IhleSMG20a},

oldkey = {Ihle2020},

topic = {pd},

core = {A*;Core Rank A*;http://portal.core.edu.au/conf-ranks/2085/},

preprint = {https://www.gipp.com/wp-content/papercite-data/pdf/ihle2020.pdf},

}

@inproceedings{GreinerPetterSAG20,

location = {Braunschweig, Germany},

title = {Making Presentation Math Computable: Proposing a Context Sensitive Approach for Translating {LaTeX} to Computer Algebra Systems},

volume = {12097},

isbn = {978-3-030-52199-8},

url = {https://link.springer.com/content/pdf/10.1007%2F978-3-030-52200-1_33.pdf},

doi = {10.1007/978-3-030-52200-1_33},

series = {Lecture Notes in Computer Science},

shorttitle = {Making Presentation Math Computable},

abstract = {Scientists increasingly rely on computer algebra systems and digital mathematical libraries to compute, validate, or experiment with mathematical formulae.

However, the focus in digital mathematical libraries and scientific documents often lies more on an accurate presentation of the formulae rather than providing uniform access to the semantic information.

But, presentational math formats do not provide exclusive access to the underlying semantic meanings.

One has to derive the semantic information from the context.

As a consequence, the workflow of experimenting and publishing in the Sciences often includes time-consuming, error-prone manual conversions between presentational and computational math formats.

As a contribution to improve this workflow, we propose a context-sensitive approach that extracts semantic information from a given context, embeds the information into the given input, and converts the semantically enhanced expressions to computer algebra systems.},

eventtitle = {{ICMS}},

pages = {335--341},

booktitle = {International Congress of Mathematical Software ({ICMS})},

publisher = {Springer},

author = {Greiner-Petter, André and Schubotz, Moritz and Aizawa, Akiko and Gipp, Bela},

editor = {Bigatti, Anna Maria and Carette, Jacques and Davenport, James H. and Joswig, Michael and de Wolff, Timo},

urldate = {2021-07-30},

date = {2020},

langid = {english},

note = {{QID}: Q122926705},

keywords = {!ms\_author},

}

@inproceedings{ScharpfSGO20,

location = {Thessaloniki, Greece},

title = {{ARQMath} Lab: An Incubator for Semantic Formula Search in {zbMATH} Open?},

volume = {2696},

url = {http://ceur-ws.org/Vol-2696/paper_200.pdf},

abstract = {The {zbMATH} database contains more than 4 million bibliographic entries. We aim to provide easy access to these entries. Therefore, we maintain dif-ferent index structures including a formula index. To optimize the findability of the entries in our database, we constantly investigate new approaches to satisfy the information needs of our users. We believe that the findings from the {ARQMath} evaluation will generate new insights into which index struc-tures are most suitable to satisfy mathematical information needs. Search en-gines, recommender systems, plagiarism checking software, and many other added-value services acting on databases such as the {arXiv} and {zbMATH} need to combine natural and formula language. One initial approach to ad-dress this challenge is to enrich the mostly unstructured document data via Entity Linking. The {ARQMath} Task at {CLEF} 2020 aims to tackle the problem of linking newly posted questions from Math Stack Exchange ({MSE}) to exist-ing ones that were already answered by the community. To deeply under-stand {MSE} information needs, answer-, and formula types, we performed manual runs for tasks 1 and 2. Furthermore, we explored several formula re-trieval methods for task 2, such as fuzzy string search, k-nearest neighbors, and our recently introduced approach to retrieve Mathematical Objects of In-terest ({MOI}) with textual search queries. The task results show that neither our automated methods nor our manual runs archived good scores in the competition. However, the perceived quality of the hits returned by the {MOI} search particularly motivates us to conduct further research about {MOI}.},

eventtitle = {{CLEF}},

booktitle = {Working Notes of ({CLEF}) 2020 - Conference and Labs of the Evaluation Forum},

publisher = {{CEUR}-{WS}.org},

author = {Scharpf, Philipp and Schubotz, Moritz and Greiner-Petter, André and Ostendorff, Malte and Teschke, Olaf and Gipp, Bela},

date = {2020},

keywords = {!ms\_author, no-doi, ⛔ No {DOI} found},

}

@inproceedings{WortnerSBL19,

location = {Urbana-Champaign, {IL}, {USA}},

title = {Securing the Integrity of Time Series Data in Open Science Projects Using Blockchain-Based Trusted Timestamping},

booktitle = {Proceedings of the Workshop on Web Archiving and Digital Libraries ({WADL}) co-located with the Annual International {ACM}/{IEEE} Joint Conference on Digital Libraries ({JCDL})},

author = {Wortner, Patrick and Schubotz, Moritz and Breitinger, Corinna and Leible, Stephan and Gipp, Bela},

date = {2019-06},

note = {tex.oldkey: Wortner2019

tex.preprint: https://www.gipp.com/wp-content/papercite-data/pdf/wortner2019.pdf

tex.topic: blockchain},

keywords = {!bg, !bg\_author, !bg\_preprint, !ms, !ms\_author, !ms\_cv, !ms\_preprint, decentralized\_open\_science, jabref\_imp2, no-doi, old\_tex\_field\_preprint},

oldkey = {Wortner2019},

preprint = {https://www.gipp.com/wp-content/papercite-data/pdf/wortner2019.pdf},

topic = {blockchain},

}

@inproceedings{MeuschkeSSK19,

location = {Urbana-Champaign, Illinois, {USA}},

title = {Improving Academic Plagiarism Detection for {STEM} Documents by Analyzing Mathematical Content and Citations},

rights = {Creative Commons Attribution 4.0 International License ({CC}-{BY})},

isbn = {978-1-7281-1547-4},

url = {https://ieeexplore.ieee.org/document/8791126/},

doi = {10.1109/jcdl.2019.00026},

abstract = {Identifying academic plagiarism is a pressing task for educational and research institutions, publishers, and funding agencies. Current plagiarism detection systems reliably find instances of copied and moderately reworded text. However, reliably detecting concealed plagiarism, such as strong paraphrases, translations, and the reuse of nontextual content and ideas is an open research problem. In this paper, we extend our prior research on analyzing mathematical content and academic citations. Both are promising approaches for improving the detection ofconcealed academic plagiarism primarily in Science, Technology, Engineering and Mathematics ({STEM}). We make the following contributions: i) We present a two-stage detec- tion process that combines similarity assessments of mathematical content, academic citations, and text. ii) We introduce new similar- ity measures that consider the order of mathematical features and outperform the measures in our prior research. iii) We compare the effectiveness of the math-based, citation-based, and text-based detection approaches using confirmed cases of academic plagia- rism. iv) We demonstrate that the combined analysis of math-based and citation-based content features allows identifying potentially suspicious cases in a collection of 102K {STEM} documents. Overall, we show that analyzing the similarity of mathematical content and academic citations is a striking supplement for conventional text- based detection approaches for academic literature in the {STEM} disciplines. The data and code of our study are openly available at https://purl.org/{hybridPD}},

eventtitle = {2019 {ACM}/{IEEE} Joint Conference on Digital Libraries ({JCDL})},

pages = {120--129},

booktitle = {2019 {ACM}/{IEEE} Joint Conference on Digital Libraries ({JCDL})},

publisher = {{IEEE}},

author = {Meuschke, Norman and Stange, Vincent and Schubotz, Moritz and Kramer, Michael and Gipp, Bela},

date = {2019-06},

note = {tex.ids= {MeuschkeSSK}19a

tex.core: 0;Core Rank A*;http://portal.core.edu.au/conf-ranks/2085/

tex.keywords: top

tex.oldkey: Meuschke2019

tex.preprint: https://www.gipp.com/wp-content/papercite-data/pdf/meuschke2019.pdf

tex.topic: pd

{QID}: Q122926720},

keywords = {!bg, !bg\_author, !bg\_preprint, !ms, !ms\_author, !ms\_cv, !ms\_preprint, !nm, !nm\_author, !nm\_preprint, 21InfWissHb, {DFG}1259-1, jabref\_imp1\_clean, old\_tex\_field\_preprint, pd\_litrev19, plagiarism detection},

core = {0;Core Rank A*;http://portal.core.edu.au/conf-ranks/2085/},

keywords = {top},

oldkey = {Meuschke2019},

preprint = {https://www.gipp.com/wp-content/papercite-data/pdf/meuschke2019.pdf},

topic = {pd},

}

@article{GreinerPetterSCG19,

title = {Semantic Preserving Bijective Mappings for Expressions involving Special Functions between Computer Algebra Systems and Document Preparation Systems},

volume = {71},

issn = {2050-3806},

url = {https://arxiv.org/abs/1906.11485},

doi = {10.1108/AJIM-08-2018-0185},

abstract = {Modern mathematicians and scientists of math-related disciplines often use Document Preparation Systems ({DPS}) to write and Computer Algebra Systems ({CAS}) to calculate mathematical expressions. Usually, they translate the expressions manually between {DPS} and {CAS}. This process is time-consuming and error-prone. The purpose of this paper is to automate this translation. This paper uses Maple and Mathematica as the {CAS}, and {LaTeX} as the {DPS}.

Bruce Miller at the National Institute of Standards and Technology ({NIST}) developed a collection of special {LaTeX} macros that create links from mathematical symbols to their definitions in the {NIST} Digital Library of Mathematical Functions ({DLMF}). The authors are using these macros to perform rule-based translations between the formulae in the {DLMF} and {CAS}. Moreover, the authors develop software to ease the creation of new rules and to discover inconsistencies.

The authors created 396 mappings and translated 58.8 percent of {DLMF} formulae (2,405 expressions) successfully between Maple and {DLMF}. For a significant percentage, the special function definitions in Maple and the {DLMF} were different. An atomic symbol in one system maps to a composite expression in the other system. The translator was also successfully used for automatic verification of mathematical online compendia and {CAS}. The evaluation techniques discovered two errors in the {DLMF} and one defect in Maple.

This paper introduces the first translation tool for special functions between {LaTeX} and {CAS}. The approach improves error-prone manual translations and can be used to verify mathematical online compendia and {CAS}.},

pages = {415--439},

number = {3},

journaltitle = {Aslib Journal of Information Management},

shortjournal = {{AJIM}},

author = {Greiner-Petter, André and Schubotz, Moritz and Cohl, Howard S. and Gipp, Bela},

urldate = {2021-09-06},

date = {2019-05-20},

langid = {english},

note = {tex.ids= {GreinerPetterSCG}19

tex.biburl: https://www.emeraldinsight.com/action/{showCitFormats}?doi=10.1108\%2FAJIM-08-2018-0185

tex.oldkey: {GreinerPetter}2019

tex.preprint: https://ag-gipp.github.io/bib/preprints/greinerpetter2019.pdf

tex.topic: mathir

{QID}: Q122926728},

keywords = {!bg, !bg\_author, !bg\_preprint, !ms, !ms\_author, !ms\_cv, !ms\_preprint, {DFG}1259-1, jabref\_imp2, old\_tex\_field\_preprint},

biburl = {https://www.emeraldinsight.com/action/showCitFormats?doi=10.1108%2FAJIM-08-2018-0185},

oldkey = {GreinerPetter2019},

preprint = {https://ag-gipp.github.io/bib/preprints/greinerpetter2019.pdf},

topic = {mathir},

}

@article{LeibleSSG19,

title = {A Review on Blockchain Technology and Blockchain Projects Fostering Open Science},

volume = {2},

issn = {2624-7852},

url = {https://www.frontiersin.org/article/10.3389/fbloc.2019.00016},

doi = {10.3389/fbloc.2019.00016},

abstract = {Many sectors, like finance, medicine, manufacturing, and education, use blockchain applications to profit from the unique bundle of characteristics of this technology. Blockchain technology ({BT}) promises benefits in trustability, collaboration, organization, identification, credibility, and transparency. In this paper, we conduct an analysis in which we show how open science can benefit from this technology and its properties. For this, we determined the requirements of an open science ecosystem and compared them with the characteristics of {BT} to prove that the technology suits as an infrastructure. We also review literature and promising blockchain-based projects for open science to describe the current research situation. To this end, we examine the projects in particular for their relevance and contribution to open science and categorize them afterwards according to their primary purpose. Several of them already provide functionalities that can have a positive impact on current research workflows. So, {BT} offers promising possibilities for its use in science, but why is it then not used on a large-scale in that area? To answer this question, we point out various shortcomings, challenges, unanswered questions, and research potentials that we found in the literature and identified during our analysis. These topics shall serve as starting points for future research to foster the {BT} for open science and beyond, especially in the long-term.},

pages = {16},

journaltitle = {Frontiers in Blockchain},

author = {Leible, Stephan and Schlager, Steffen and Schubotz, Moritz and Gipp, Bela},

date = {2019},

note = {tex.biburl: https://www.frontiersin.org/articles/10.3389/fbloc.2019.00016/{bibTex}

tex.oldkey: Leible2019

tex.preprint: https://www.gipp.com/wp-content/papercite-data/pdf/leible2019.pdf

tex.topic: blockchain

{QID}: Q81747275},

keywords = {!bg, !bg\_author, !bg\_preprint, !ms, !ms\_author, !ms\_preprint, jabref\_imp2},

biburl = {https://www.frontiersin.org/articles/10.3389/fbloc.2019.00016/bibTex},

oldkey = {Leible2019},

preprint = {https://www.gipp.com/wp-content/papercite-data/pdf/leible2019.pdf},

topic = {blockchain},

}

@article{SchubotzT19,

title = {Four Decades of {TeX} at {zbMATH}.},

volume = {112},

issn = {1027-488X},

url = {http://www.ems-ph.org/journals/show_pdf.php?issn=1027-488x&vol=6&iss=112&rank=15},

doi = {10.4171/news/112/15},

pages = {50--52},

journaltitle = {European Mathematical Society Newsletter},

author = {Schubotz, Moritz and Teschke, Olaf},

date = {2019},

note = {tex.biburl: https://zbmath.org/bibtex/07065264.bib

tex.oldkey: Schubotz2019b

tex.publisher: European Mathematical Society ({EMS}) Publishing House, Zurich

{QID}: Q122926696},

keywords = {!ms, !ms\_author, !ms\_cv, \#nosource, jabref\_imp2, old\_tex\_field\_preprint},

biburl = {https://zbmath.org/bibtex/07065264.bib},

oldkey = {Schubotz2019b},