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Sztuczna inteligencja jest jednym z najważniejszych elementów współczesnego świata. Funkcjonuje już ona w podstawowych dziedzinach życia. Jest także wykorzystywana w różnych dyscyplinach naukowych. Od pewnego czasu zaczyna się również stosować algorytmy sztucznej inteligencji do badania świata kultury. W artykule zostały ukazane najważniejsze metody i narzędzia sztucznej inteligencji stosowane w badaniach różnych zjawisk kultury, a także przykłady takich badań. Badacze kultury wykorzystują sztuczną inteligencję w dwóch obszarach. Pierwszym jest przetwarzanie języka naturalnego, drugim komputerowe badanie obrazów (filmów, zdjęć, grafiki itp.). Sztuczna inteligencja jest częścią uczenia maszynowego. Wykorzystuje ono konwolucyjne sieci neuronowe, duże ilości danych (big data) i superkomputery do analizy i wizualizacji cyfrowych wytworów. Badania kultury za pomocą sztucznej inteligencji są zaliczane do nowego paradygmatu zwanego humanistyką cyfrową.

Poročilo s konference Jezikovne tehnologije in digitalna humanistika (JTDH) 2022, ki je potekala septembra 2022 v prostorih Fakultete za družbene vede Univerze v Ljubljani. Konferenco je priredilo Slovensko društvo za jezikovne tehnologije (SDJT), v soorganizaciji s Centrom za jezikovne vire in tehnologije Univerze v Ljubljani (CJVT), Inštitutom za novejšo zgodovino (INZ) ter raziskovalnima infrastrukturama CLARIN.SI in DARIAH-SI.

Wenige Autoren haben die europäische Lyrik so geprägt wie Francesco Petrarca (1304-1374). Das liegt vor allem an dem poetischen Stil von Petrarcas wichtigstem Text in italienischer Sprache, einer Sammlung von Liebesgedichten mit dem Titel Canzoniere, die über Jahrhunderte zu einem bedeutenden poetischen Modell für die europäische Lyrik wurde. Petrarcas Einfluss auf die europäische Literatur wird in der Forschung oft mit dem Ausdruck „Petrarkismus“ bezeichnet, allerdings ist die genaue Definition des Begriffs nach wie vor umstritten. Ein Grund dafür mag sein, dass nur wenige Untersuchungen zum Petrarkismus ein größeres Textkorpus in den Blick nehmen. Die Analyse eines umfassenden Korpus petrarkistischer Dichtung könnte allerdings nicht nur existierende Definitionen auf breiterer Basis erproben, sondern ferner einen quantitativ fundierten Beitrag zum besseren Verständnis des Petrarkismus leisten. Der vorliegende Beitrag untersucht ausgehend von bestehenden Erklärungsansätzen des Petrarkismus ein Korpus aus 55 italienischen Gedichtsammlungen mittels digitaler stilometrischer, Kookkurrenz- und Netzwerkanalysen.

Reproducible research (Reproducible research is when data can be reanalysed taking the same steps and producing the same or similar result) is being implemented at different speeds in different disciplines, and Archaeology, as a discipline that sits at the intersection of the sciences and humanities, is at the start of this journey. Enabling reproducibility of your work by others is an important step in ensuring research quality. There are currently many barriers to moving towards reproducible research such as upskilling researchers in the practices, software and infrastructure needed to do reproducible research and also the need to address how we can, as a discipline, deal with issues like sensitive data. In this article, we seek to introduce reproducible research in an understandable manner so that archaeological researchers can learn where and how to start with this approach. We describe what reproducible archaeological research can look like and suggest three different computational skill levels of constructing reproducible research workflows (a research workflow is the different parts of a research lifecycle such as data collection, data analysis, data archiving, etc, and making all stages reproducible by using a history tracking system (version control) and transparent documation). Finally, in an extensive appendix, we address common questions about reproducible research to remove the stigma about these issues and suggest ways to overcome them.

Contributor Role Ontologies and Taxonomies (CROTs) provide a standard list of roles to specify individual contributions to research. CROTs most common application has been their inclusion alongside author bylines in scholarly publications. With the recent uptake of CROTs among publishers –particularly the Contributor Role Taxonomy (CRediT)– some have anticipated a positive impact on ethical issues regarding the attribution of credit and responsibilities, but others have voiced concerns about CROTs shortcomings and ways they could be misunderstood or have unintended consequences. Since these discussions have never been consolidated, this review collated and explored published viewpoints about the ethics of CROTs. After searching Ovid Medline, Scopus, Web of Science, and Google Scholar, 30 papers met the inclusion criteria and were analyzed. We identified eight themes and 20 specific issues related to the ethics of CROTs and provided four recommendations for CROT developers, custodians, or others seeking to use CROTs in their workflows, policy and practice: 1) Compile comprehensive instructions that explain how CROTs should be used; 2) Improve the coherence of used terms, 3) Translate roles in languages other than English, 4) Communicate a clear vision about future development plans and be transparent about CROTs’ strengths and weaknesses. We conclude that CROTs are not the panacea for unethical attributions and should be complemented with initiatives that support social and infrastructural transformation of scholarly publications.

This is a revew of the present-day data lanscape prepared as deliverable 5.1. in the framework of the Horizon2020 Project "Computational Literary Studies Infrastracture". This landscape review, for which Work Package 5 is responsible, focuses on intellectual access, i.e. providing guidance for finding and sharing literary data, while Work Package 6 approaches the task from a more technological side, collecting and analyzing literary corpora, available formats, tools, and metadata in order to create an exploratory catalogue / inventory of literary corpora and to provide a transformation matrix/toolbox for solving common issues. Yet we coordinate our efforts – beginning with the compilation of the table of literary collections – therefore one can regard these as two sides of the same coin. The review’s point of departure is the abundance of existing data and their diversity or heterogeneity as regards corpus design and underlying concepts, for example the definitions of text (is it a source, an edition, a data set? see chapter 3), the purpose of a corpus (e.g. general, reference, or monitoring corpora, special purpose corpora; see chapter 4), central considerations or criteria regarding the construction of a corpus (sampling, balancing, representativeness, annotation model(s), data format(s); see likewise chapter 4). How can I go about obtaining data without transgressing ethical or legal boundaries (see chapter 5)? We ask: How can we assist literary scholars in searching for and finding existing data that are relevant to their own research questions? And additionally, what kind of research question is relevant concerning the present-day state of the data landscape and literariness and textuality? The review contains following sections: 1. Introduction: Enhancing Data Findability and Accessibility……………………..……..4 2. Reference Case Studies Highlighting Research Context and Corpus Design (Haiku, Slovak Novel)…………………………………………………………………………..7 3. Research Context: Impact of the Digital Paradigm on Literary Text Collections….…..9 3.1. “Literary” (Return of Essentialism, Poetics, and Classifications)……………………..12 3.2. “Text” (between Bag of Words and Ordered Hierarchy of Content Objects)………..15 3.3. Modelling vs. Exploratory Approaches to Textual Data……………………………….18 3.4. Use Case: Collecting the Haiku………………………………………………………….20 4. Corpus Design: Methods of Selection and Sampling (Use Case: the Slovak Novel)….23 4.1. Typology of Corpora According to Their Purpose……………………………………..25 4.1.1. General-Purpose Collections……………………………………………………….....26 4.1.2. Reference Corpora (Subcorpora of)………………………………………………….28 4.1.3. Digital Critical Editions………………………………………………………………….29 4.1.4. Monitor Corpora…………………………………………………………………………30 4.1.5. Corpora Compiled on the Basis of a Research Question…………………………..31 4.1.6. Opportunistic Corpora………………………………………………………………….31 4.2. Key Considerations for Selection and Sampling (Relative to Different Types of Corpora, e.g. Exploratory or Modelling)…………………………………………...…………32 4.2.1. Corpus Architecture / Composition (Size, Eligibility, Structuring of Texts and Annotations, Entity Typing)……………………………………………………………………34 4.2.2. Completeness…………………………………………………………………………..36 4.2.3. Representativeness…………………….………………………………………………37 4.2.4. Proportion (Balance)……………………………………………………………………38 4.2.5. Frequent Biases………………………………………………………………………...39 4.3. Data Formats………………………………………………………………………………41 4.4. Metadata’s Formats and Structures (Generic vs. Domain-Specific Repositories)….42 4.5. Access to Corpus Data: Retrieval Tools (GUI, APIs, OAI-PMH)…………………….45 5. Legal and Ethical Considerations………………………………………………………….46 6. Outlook……………………………………………………………………………………….51

Within task 5.2 (Hosting and sharing data repositories) of the SSHOC project, repository software is being developed based on Dataverse, for the sharing and publication of research data within the Social Science and Humanities (SSH) domain. Dataverse is open-source research data repository software developed by the Institute for Quantitative Social Science (IQSS), Harvard University. This document describes the work done by task 5.2, for the development of ‘Archive in a Box’ repository software and proof of concept of centralised installation in the cloud. The ‘Archive in a Box’ makes the installation of Dataverse repository software easier for institutes with a lack of technical staff. This document describes the advantages of such a package. Additionally, task 5.2 worked on a proof of concept of a centralised cloud installation of the Dataverse software at the Google cloud infrastructure of CESSDA ERIC. A cloud installation makes it possible to automate the installation and keep the application up and running, for instance by scaling up or down resources when needed. Another advantage of a cloud orchestrator is the ability to start a new component or part of the application, if it should fail for some reason. Furthermore, task 5.2 developed several additional functionalities to the Dataverse software to make the software more compliant to the needs of the SSH communities in Europe. This document describes the results of the accomplished work, and refers to technical details published in GitHub repositories. Already many of the results of task 5.2 are used by the European and Global Dataverse community and some functionalities are integrated in the new versions of the Dataverse master branch of Harvard.

The digital humanities (DH) is an emerging field of teaching and research that invites modern technologies to address traditional humanities questions while simultaneously making space for humanistic critiques of those technologies. A natural relationship exists between DH and the field of information studies (the iField), particularly surrounding their common focus on the interface between humans and computers, as well as subfields such as the organization of information, libraries and archives, data preservation, and information in society. Thus, we propose that iField programs in universities should take an active role in DH education. We are particularly interested in programs that are officially Information Schools (iSchools), members of the international iSchools Organization. Our research began as part of a DH curriculum committee convened by the iSchools Organization. To support iSchool engagement in DH education, we have inventoried and analyzed the degrees and supplemental credentials offered by DH education programs throughout the world. Our study deployed multiple data collection methods, which included conducting both ad hoc and comprehensive website surveys, querying an online DH catalog, and inviting members of the iSchools Organization to participate in an online questionnaire. This work has revealed several common patterns for the current structure of DH programs, including the various types of degrees or supplemental credentials offered. We observe that iSchools have a significant opportunity to become more engaged in DH education and we suggest several possible approaches based on our research.