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OPEN SCIENCE, VERSION 3.0: Breaking down barriers for equitable and efficient research communication
(2022)
The recognition of pharmacological substances, compounds and proteins is an essential preliminary work for the recognition of relations between chemicals and other biomedically relevant units. In this paper, we describe an approach to Task 1 of the PharmaCoNER Challenge, which involves the recognition of mentions of chemicals and drugs in Spanish medical texts. We train a state-of-the-art BiLSTM-CRF sequence tagger with stacked Pooled Contextualized Embeddings, word and sub-word embeddings using the open-source framework FLAIR. We present a new corpus composed of articles and papers from Spanish health science journals, termed the Spanish Health Corpus, and use it to train domain-specific embeddings which we incorporate in our model training. We achieve a result of 89.76% F1-score using pre-trained embeddings and are able to improve these results to 90.52% F1-score using specialized embeddings.
Despite the great importance of the Latin language in the past, there are relatively few resources available today to develop modern NLP tools for this language. Therefore, the EvaLatin Shared Task for Lemmatization and Part-of-Speech (POS) tagging was published in the LT4HALA workshop. In our work, we dealt with the second EvaLatin task, that is, POS tagging. Since most of the available Latin word embeddings were trained on either few or inaccurate data, we trained several embeddings on better data in the first step. Based on these embeddings, we trained several state-of-the-art taggers and used them as input for an ensemble classifier called LSTMVoter. We were able to achieve the best results for both the cross-genre and the cross-time task (90.64% and 87.00%) without using additional annotated data (closed modality). In the meantime, we further improved the system and achieved even better results (96.91% on classical, 90.87% on cross-genre and 87.35% on cross-time).
The annotation of texts and other material in the field of digital humanities and Natural Language Processing (NLP) is a common task of research projects. At the same time, the annotation of corpora is certainly the most time- and cost-intensive component in research projects and often requires a high level of expertise according to the research interest. However, for the annotation of texts, a wide range of tools is available, both for automatic and manual annotation. Since the automatic pre-processing methods are not error-free and there is an increasing demand for the generation of training data, also with regard to machine learning, suitable annotation tools are required. This paper defines criteria of flexibility and efficiency of complex annotations for the assessment of existing annotation tools. To extend this list of tools, the paper describes TextAnnotator, a browser-based, multi-annotation system, which has been developed to perform platform-independent multimodal annotations and annotate complex textual structures. The paper illustrates the current state of development of TextAnnotator and demonstrates its ability to evaluate annotation quality (inter-annotator agreement) at runtime. In addition, it will be shown how annotations of different users can be performed simultaneously and collaboratively on the same document from different platforms using UIMA as the basis for annotation.
The Specialized Information Service Biodiversity Research (BIOfid) has been launched to mobilize valuable biological data from printed literature hidden in German libraries for over the past 250 years. In this project, we annotate German texts converted by OCR from historical scientific literature on the biodiversity of plants, birds, moths and butterflies. Our work enables the automatic extraction of biological information previously buried in the mass of papers and volumes. For this purpose, we generated training data for the tasks of Named Entity Recognition (NER) and Taxa Recognition (TR) in biological documents. We use this data to train a number of leading machine learning tools and create a gold standard for TR in biodiversity literature. More specifically, we perform a practical analysis of our newly generated BIOfid dataset through various downstream-task evaluations and establish a new state of the art for TR with 80.23% F-score. In this sense, our paper lays the foundations for future work in the field of information extraction in biology texts.
Challenges of FAIR phase 0
(2018)
After two-year's shutdown, the GSI accelerators plus the latest addition of storage ring CRYRING, will be back into operation in 2018 as the FAIR phase 0 with the goal to fulfill the needs of scientific community and the FAIR accelerators and detector development. Even though GSI has been well known for its operation of a variety of ion beams ranging from proton up to uranium for multi research areas such as nuclear physics, astrophysics, biophysics, material science, the upcoming beam time faces a number of challenges in re-commissioning its existing circular accelerators with brand new control system and upgrade of beam instrumentations, as well as in rising failures of dated components and systems. The cycling synchrotron SIS18 has been undergoing a set of upgrade measures for fulfilling future FAIR operation, among which many measures will also be commissioned during the upcoming beam time. This paper presents the highlights of the challenges such as re-establishing the high intensity heavy ion operation as well as parallel operation mode for serving multi users. The status of preparation including commissioning results will also be reported.
GSI High Energy Beam Transfer lines (HEST) link the SIS18 synchrotron with two storage rings (Experimental Storage Ring and Cryring) and six experimental caves. The recent upgrades to HEST beam instrumentation enables precise measurements of beam properties along the lines and allow for faster and more precise beams setup on targets. Preliminary results of some of the measurements performed during runs in 2018 and 2019 are presented here. The focus is on response matrix measurements and quadrupole scans performed on HADES beam line. The errors and future improvements are discussed.