Today, the heterogeneity of NLP tools in relation to existing methods and the constantly growing availability of models (see Hugging Face<ref xmlns="http://www.tei-c.org/ns/1.0" n="1" target="ftn1" />) confronts various disciplines with major challenges in the daily handling of natural language processing. The spectrum of disciplines, although this is not exhaustive, ranges from biodiversity (e.g. (Lücking et al., 2021; Folk et al., 2024)), medicine (e.g. Poon et al. (2017); Redondo et al. (2019)), linguistics (e.g. Abdurakhmonova et al. (2022); Lücking et al. (2024)), all the way to the digital humanities (e.g. Brooke et al. (2015); Tasovac et al. (2023)). In parallel, the amount of available and usable corpora is also growing regularly in various areas, including, among others, corpora such as the “Collosal Clean Crawled Corpus” (C4 - (Raffel et al., 2020)), parliamentary protocols (e.g. Rauh and Schwalbach (2020); Abrami et al. (2022, 2024)), newspaper corpora (e.g. Süddeutscher Verlag (2014); New York Times (2019)), social media corpora (e.g. Dimitrov et al. (2020); Kratzke (2023)), COW (Schäfer, 2015) as well as Wikipedia (Pasternack and Roth, 2008). These are golden times for all scientific fields, as different models can be applied to the respective corpora; although in the short term this leads to non-trivial challenges in terms of a) analysis time, b) heterogeneity of (corpora) formats, c) processing input and output formats as well as d) analyzeability. These many <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">construction</hi> phases show the need for a reliable working tool that can be used without intensive training, which is available in the form of <hi xmlns="http://www.tei-c.org/ns/1.0" rend="bold">Docker Unified UIMA Interface</hi> (DUUI)<ref xmlns="http://www.tei-c.org/ns/1.0" n="2" target="ftn2" />. <figure xmlns="http://www.tei-c.org/ns/1.0"> <graphic url="Pictures/a5afbbc790eaa32ad5eefd624c469b9b.png" /> <head>A <hi rend="bold italic">Composer</hi> is defined within a Java application, which starts a set of <hi rend="bold">Components</hi> that are each available as Docker images that encapsulate tools implemented in other programming languages (e.g. Python, Java or Rust). The sequential annotation enrichment between the individual <hi rend="bold">Components</hi>, which are executed as Docker images, is done using Lua (Ierusalimschy et al., 2007), which performs the UIMA (de)serialization. At the end of each annotation, the individual documents are serialized, whereby various serializers (e.g. CoNLL, TFC, XMI <hi rend="italic">and various database backends</hi>) are available (Abrami et al., 2024). </head> </figure>DUUI (Leonhardt et al., 2023) is designed as a platform-independent annotation framework for the horizontal and vertical distribution of heterogeneous NLP processes towards microservice-oriented homogenization using web services for a unified processing and reuse of unstructured data. Using microservices such as Docker also allows programming language-different as well as version-different NLP tools such as <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">spaCy</hi> (Honnibal et al., 2020), <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">Heideltime</hi> (Strötgen and Gertz, 2015) or <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">GNFinder</hi> (Mozzherin et al., 2024) to be used in a common aggregated pipeline without causing dependency problems between the individual tools, since each instance (in Docker Swarm also in a cluster mode) is running on its own and can be utilized via a REST web service. Unification and implicit reusability of NLP processing is ensured by using the <hi xmlns="http://www.tei-c.org/ns/1.0" rend="italic">Unstructured Information Management Applications</hi> (UIMA – Ferrucci et al. (2009)) approach as the basis for annotation and serialization on document level. How DUUI can be used as a tool, especially for the digital humanities (c.f. Abrami and Mehler (2024)), will be presented in various hands-on demonstrations, thereby initiating discussions within the community and establishing a forum for exchange on the homogenized usability of heterogeneous annotation tools within one framework. We gratefully acknowledge the financial support provided by the German Research Foundation (DFG) for the project “Critical Online Reasoning in Higher Education” (FOR 5404, project number 462702138) and for the project “Ausbau und Konsolidierung des Fachiformationsdienstes Biodiversitätsforschung<ref xmlns="http://www.tei-c.org/ns/1.0" n="3" target="ftn3" /> (BIOfid)” (DFG: 326061700). <note xmlns="http://www.tei-c.org/ns/1.0" xml:id="ftn1" rend="footnote text" n="1"> https://huggingface.co/ </note><note xmlns="http://www.tei-c.org/ns/1.0" xml:id="ftn2" rend="footnote text" n="2">Available via <ref target="https://github.com/texttechnologylab/DockerUnifiedUIMAInterface">GitHub</ref> under the AGPL license. </note><note xmlns="http://www.tei-c.org/ns/1.0" xml:id="ftn3" rend="footnote text" n="3">Expansion and consolidation of the specialized information service for biodiversity research</note> <hi xmlns="http://www.tei-c.org/ns/1.0" rend="bold">Abdurakhmonova, Nilufar. Z., Alisher S. 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