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These spreadsheets map the SSH Training Discovery Tool (TDT) metadata to Schema.org. The TDT metadata was updated in March 2022 and linked to Schema.org to improve the findability of its contents. The mapping is divided in two spreadsheets: one for the TDT items (e.g. individual courses), and one for TDT sources (e.g. a provider of courses).

Data that belongs to the manuscript "Detecting dairy cows' lying behavior using noisy 3D ultra-wide band positioning data" by Adriaens, Ouweltjes, Pastell, Ellen, Kamphuis.

This Dataverse manual aims to provide a practical, user-friendly, and concise guide intended for typical end users of Dataverse. The manual includes instructions for the essential functions of Dataverse such as creating, managing and sharing Dataverse collections and datasets; a technical setup guide; legal questions, including usage agreements; as well as references to additional resources such as technical setup guides. Please refer to the table of contents below for a full overview of the topics covered. This manual is not intended to cover advanced functions such as those for administrators or developers, but throughout the manual, references to further reading that do cover more advanced topics will be provided.

The dataset contains the processed and analysed research data from the research project 'Policy-making of early nature conservation. The Netherlands and the United Kingdom compared, 1930-1960', funded by the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No 832350.The dataset contains the Data Management Plan, the researcher's notes on literature and archival sources, and export files for his full literature reference system (also including notes, summaries etc.). For further details about contents and hints for usage, please see the readme.txt file.

This dataset contains the supporting data for the following article:Zhang, C., Jepson, K.M., Lohfink, G. & Arvaniti, A. (2021). Comparing acoustic analyses of speech data collected remotely. The Journal of the Acoustical Society of America, 149 (6), 3910-3916. doi: https://doi.org/10.1121/10.0005132Face-to-face speech data collection has been next to impossible globally as a result of the COVID-19 restrictions. To address this problem, simultaneous recordings of three repetitions of the cardinal vowels were made using a Zoom H6 Handy Recorder with an external microphone (henceforth, H6) and compared with two alternatives accessible to potential participants at home: the Zoom meeting application (henceforth, Zoom) and two lossless mobile phone applications (Awesome Voice Recorder, and Recorder; henceforth, Phone). F0 was tracked accurately by all of the devices; however, for formant analysis (F1, F2, F3), Phone performed better than Zoom, i.e., more similarly to H6, although the data extraction method (VoiceSauce, Praat) also resulted in differences. In addition, Zoom recordings exhibited unexpected drops in intensity. The results suggest that lossless format phone recordings present a viable option for at least some phonetic studies.This dataset contains two data files:- "data_Praat.csv" contains data extracted using Praat- "data_VoiceSauce.csv" contains data extracted using VoiceSauceThe full information of participants, materials, recording procedures, and measurements are recorded in the above-mentioned article.

This dataset contains the supporting data for the presentation at the 179th Meeting of the Acoustical Society of America:Zhang, C., Jepson, K.M., Lohfink, G. & Arvaniti, A. (2020). Speech data collection at a distance: Comparing the reliability of acoustic cues across homemade recordings. The Journal of the Acoustical Society of America, 148 (4). doi: 10.1121/1.5147535It is also related to the following article:Zhang, C., Jepson, K.M., Lohfink, G. & Arvaniti, A. (2021). Comparing acoustic analyses of speech data collected remotely. The Journal of the Acoustical Society of America, 149 (6), 3910-3916. doi: 10.1121/10.0005132Speech production data collection has been significantly impacted by COVID-19 restrictions. Sound-treated recording spaces and high-quality recording devices are inaccessible, and face-to-face interactions are limited. We investigated alternative recording methods that produce data suitable for phonetic analysis, and are accessible to people in their homes. We examined simultaneous recordings of pure tones at seven frequencies (50 Hz, every 100 Hz between 100 Hz and 600 Hz), and three repetitions of the primary cardinal vowels elicited from five trained speakers. Recordings were made using the ZOOM meeting application and non-lossy format smartphone applications (Awesome Voice Recorder, Recorder), comparing these with Zoom H6N reference recordings. F0, F1-4, and duration based on manual segmentation were measured.

The aim of this report is to present to its stakeholders (researchers, policy makers, cultural heritage institutions, research infrastructures, archives) a series of recommendations and guidelines about which policies to apply during and after their research or infrastructure work. “During their research work”, because policies on data and repositories guide the data creator to produce high quality data; “after their research work”, because policies on access and reuse help make the data more accessible and reusable. The research communities are: Archaeology, History, Language related studies and social sciences.

This report addresses the ARIADNE project objectives and the framework of the impact evaluation, summarises the overall results, and gives recommendations for ARIADNE and other stakeholders with a focus on potential further advances.

Publishing research data as open data is not yet common practice for researchers in the arts and humanities, and lags behind other scientific fields, such as the natural sciences. Moreover, even when humanities researchers publish their data in repositories and archives, these data are often hard to find and use by other researchers in the field. This report gives an overview of the various aspects that are connected to open access publishing of research data in the humanities. After the introduction, where we give definitions of key concepts, we describe the research data life cycle. We present an overview of the different stakeholders involved and we look into advantages and obstacles for researchers to share research data. Furthermore, a description of the European data repositories is given, followed by certification standards of trusted digital data repositories. The possibility of data citation is important for sharing open data and is also described in this report. We also discuss the standards and use of metadata in the humanities. Finally, we discuss best practice example of open access research data system in the humanities: the French open research data ecosystem. With this report we provide information and guidance on open access publishing of humanities research data for researchers. It will also serve as input for the design and implementation of an open humanities data platform in DARIAH.