dataesr/scientific-paragraphs-categorization huggingface dataset:
Relative Abundance Graphs Taxonomic relative abundance graphs were prepared, dividing microbiome populations into their respective taxonomic levels (phylum, genus, species). Data were analyzed using Student's t-test for statistical significance and reported as follows: p ≤ 0. 05 (*), ≤0. 01 (**), and ≤0. 001 (***). Figures were produced using the Qiime2View 2018. 8 website. Raw data are available under the Sequence Read Archive BioProject PRJNA647447 (SRR12276169 to SRR12276257).
3  , and Fig. C3  with different X-axes) and longitude-latitude cross-sections of chemical species mole fractions (Fig. 4  ). For the longitude-latitude cross-sections, we sampled our model data at a pressure level of the photosphere (i. e. where the value of the normalized contribution function is equal to 1, see Appendix C ) in spectral bands 6  closest to the centre of the Spitzer /IRAC channels 3. 6, 4. 5, 5. 8, and 8. 0 μm that coincide with the peaks in the absorption cross-section of CH 4 , CO, H 2 O, and CH 4 , respectively, and a band closest to 10. 5 μm coinciding with the peak in NH 3 absorption crosssection. We selected a single spectral band for each Spitzer /IRAC channel instead of a range of bands as did  Drummond et al. ( 2018c )  to simplify the cases of 'convoluted' photospheres (Dobbs-Dixon & Cowan 2017 ), for which the contribution function has multiple peaks when a range of absorption coefficients from several spectral bands contributes to the total absorption.
AC K N OW L E D G E M E N T S The authors thank the anonymous referee for a thorough re vie w of our paper. We also thank  Maria E. Steinrueck  and  Heather A. Knutson  for providing the observed HD 189733b phase curve data published in Knutson et al. ( 2012 ), and  Denis Sergeev  for help with the data visualization. This research has made use of the  NASA Exoplanet Archive , which is operated by the  California Institute of Technology , under contract with the  National Aeronautics and Space Administration  under the  Exoplanet Exploration Program. Financial support. This research was partly supported by a  Science and Technology Facilities Council  consolidated grant  ST/R000395/1a , a  UKRI Future Leaders Fellowship   MR/T040866/1 , and the  Leverhulme Trust  through a research project grant  RPG-2020-82.
JM acknowledges the support of a  Met Office Academic Partnership secondment. Hardware. This research was performed using the DiRAC Data Intensive service at Leicester, operated by the  University of Leicester IT Services , which forms part of the  STFC DiRAC HPC Facility  ( www. dirac. ac. uk). The equipment was funded by  BEIS  capital funding via STFC capital grants  ST/K000373/1  and  ST/R002363/1  and  STFC DiRAC Operations  grant  ST/R001014/1. DiRAC is part of the  National e-Infrastructure. Software. Material produced using Met Office Software. The scripts to process and visualize the Met Office UNIFIED MODEL data are available on GitHub at ht tps://github. com/mzamyatina/sign atures of wind driven chemistry on hot jupiters ; these scripts are dependent on the following PYTHON libraries: AEOLUS (Sergeev & Zamyatina 2022 ),  IRIS  ( MetOffice 2022  ), IPYTHON (Perez & Granger 2007 ), JUPYTER (Kluyver et al.
The Places dataset is still in-process and being added to on a regular basis. It is comprised of complete data management documentation and ethics documentation in English and French, concept notes in English and French, and participant data files that include. csv metadata sheets,. wav audio recordings of interviews,. jpeg photographs of the place of the interview and open ELAN. eaf transcriptions. The participant interview data relies on a narrative inquiry methodology and is collected in one-on-one interviews with researchers on the theme of anglophone expatriation and adaptation to French socio-physical space. These interviews are informal and interactive, aiming for a sharing of experience, since the researchers are, themselves, anglophone expatriates. The aim of this accompanying article is to provide information on the dataset through a concomitant reflection on the research context in France and the affordances of the increasingly powerful TGIR Huma-Num digital humanities infrastructure, as well as the tensions that are prevalent in the Franco-European space between the demands of Open Science and the restrictions of the European General Data Protection Regulations.
(1) INTRODUCTION Places is an interview-based narrative research project lead by Hillary Bays and William Kelleher from the LISAA research unit at Gustave Eiffel and the LIDILE research unit at Rennes 2, respectively. Places data is opened on the Nakala data repository that is overseen by the Digital Humanities Very Large Research Infrastructure (Sciences Humaines Numériques Très Grande Infrastructure de Recherche -TGIR Huma-Num)  (CNRS, 2022). The project and data collection are ongoing. The Nakala data set includes full data management documentation, full ethics documentation in English and French, concept notes in English and French and participant data files that include. csv metadata sheets,. wav audio recordings of interviews,. jpeg photographs of the place of the interview and open ELAN  (MPI, 2021).
eaf transcriptions. The Places project seeks to better understand processes of place-making, primarily in response to the dramatic shifts in socialisation, language, and cultural adequation undergone by those in situations of expatriation in France. These shifts suppose, additionally, a reflection on events such as the COVID pandemic, new configurations of work, and the merging of the offline and the online. Places participants are anglophone expatriates in France. Expatriates, generally, are critically aware of their surrounds because of their need to adapt to new circumstances. Places is compiling an open dataset of narratives. In these narratives, material urban fabric becomes the interface for biographic work on displacement -whether linguistic, personal, or professional. Whereas the social context for Places is an interrogation of public space, the wider research context is the gathering force of the move towards Open Science, and the adoption of that move in France, and Franco-European space.
Nakala is a dataset managing and hosting repository that is specifically built for scientific data. It offers assignation of a Digital Object Identifier (DOI 15 ), hierarchisation (using 'collections'), description, metadata and a selection of Creative Commons sharing licences. TGIR Huma-Num is a central partner in a series of research initiatives and systems, all of which promote Open Science. The Common Language Resources and Technology Infrastructure (CLARIN 16 ) is one example that is very important. CLARIN is a European label that hosts and curates larger corpuses generated by research consortiums. TGIR Huma-Num also supports smaller data-sharing platforms. Ortolang 17 and COCOON 18 are examples of the latter. Ortolang is a corpus repository for linguistics that hosts phonetic annotations, multimedia files, and multimodal or text-based datasets.
TGIR Huma-Num promotes Open Science in other ways, for instance through the free availability of a host of textometric and other analytic tools, like TXM. 19   French universities are very active partners in open research that is conceived of as pluri-site and localisable. Open Science charters (see Université Rennes 2 a, 2021) or initiatives such as Keys for Open Science (Clés pour la Science Ouverte -SOcle 20 ) (Université Rennes 2 b, 2022), for example, serve as references for training and information. Infrastructures such as TGIR Huma-Num, similarly have contacts that can be reached directly by telephone or email, thanks to the Human Sciences Foundation (Fondation Maison des Scienes de l'Homme -MSH 21 ). The Nakala repository that has been adopted as the Places data hosting service is a very good example of Open Science in France.
It is dialogable with other TGIR Huma-Num applications and is a fun and accessible platform, as attested to by its furry-eared logo given in Extract 1: Project organisation is affected by the RGPD, since a deadline must be set for destruction of those documents (such as consent forms, or primary documentation) that identify or implicate participants and both sensitive and confidential information must be removed: • Sensitive data includes racial or ethnic references, political opinions, religious and philosophical convictions, trade union affiliation, genetic and biometric data, health data, sexual data, penal record, identification document data and numbers. • Confidential data includes names and addresses of persons directly related to the participant, proper names such as residential street addresses, telephone numbers, work names and addresses and specific identifying times and events.
To paraphrase its documentation (TGIR Huma-Num, 2022), there are three basic settings for uploaded data: i) uploaded, unpublished, and private, ii) published and public, iii) published and embargoed. Options i) and iii) are not open, option ii) is completely open. It is therefore hard to find a middle term that is suitable for qualitative data. Often, only institutional repositories offer made-to-measure safeguards that can include traceability or agree and close licences, such as those applied to the Talking Fish corpus  (Goodall, Frawley & Sewell, 2011). It is in the Data Management Plans (DMP's) for projects, such as Places, that these tensions between data openness and data protection play out. A DMP must negotiate the twin imperatives of curational fireguards (see also  Bouchet-Moneret, 2021; Stérin, 2018)  and the growing demand for open data.
(3. 2) PARTICIPANTS AND DATA Places is a project in process which aims to assemble 40 participants, or approximately 20hrs of fully transcribed talk. Places recruits English-language participants, or participants from predominantly English-speaking countries, who have been expatriated to France. Expatriation is taken simply to mean residing in a foreign country for reasons that involve work, as opposed to humanitarian or migratory reasons. 24 Expatriates maintain links to their home country and often return frequently. Participants are recruited using the 'snowball' method that involves contacts through associations or through networks of acquaintance. After making contact with the researchers, participants are invited to an interview. It is an informal interview format that is envisaged as a sharing between researcher and participant, in an (auto-) biographical fashion, since both lead researchers are also expatriates.
The. csv format in Extract 2 transcribes the interview following editing for sensitive and confidential information. This first verbatim transcription is then corrected and segmented by the researchers, working in collaboration on Sharedocs, in order to produce an ELAN. eaf transcription (given in Extract 3) that is timed down to intonation groups and that includes markers of backchannelling etc. It is this second transcription that is verified by the researchers which will be uploaded to Nakala. One can note that this version of the transcription has much shorter annotation blocks and indicates backchanneling etc. It is also a much closer transcription in that hesitations, false starts, and repairs are also transcribed. It is a transcription with which data analysis can begin. ELAN offers several advantages.
It marks annotations directly onto a. wav audio file and does so with a discrimination of 1000 th of a second. It offers a series of tiers for different participants and for different kinds of annotation. A research project can create a customised ELAN template that uses controlled vocabularies to standardise annotations between different researchers. A controlled vocabulary is a series of terms of interest to a particular type of analysis that can be pre-defined for a specific tier. When a segment of waveform is selected for annotation, the annotator chooses among the pre-defined terms This leads to a greater regularity in annotation. As a result, annotations can be compared across different dataset items. An example of tiers and controlled vocabularies is given in Extract 4. Extract 2 Participant Shadiya talks about grocery shopping in France.
Extract 3 The same segment as in Extract 2 that is now marked against the. wav waveform and separated by intonation groups. Kelleher and Bays Journal of Open Humanities Data DOI: 10. 5334/johd. 75 Extract 4 is an example of a first research orientation of Places that investigates repetition. The different tiers concern: i) the dynamics of repetition between interlocutors and between 'turns' or intonation groups, ii) the complexity of the repetition, iii) the placing of the repetition within story units or conversational projects, and iv) the discourse-related or performance-related function of the repetition (a distinction taken from  Auer, 1984). ELAN easily exports. xml or. csv formats that allow transcriptions to be easily embedded in other applications, and, thanks to the accuracy of the annotations on the waveform, other kinds of analysis, like phonemics using tools such as Praat  (Boersma & Weenink, 2022) , can be applied.
(4) PLACES AS AN EXAMPLE OF OPEN SCIENCE IN FRANCE Places, in its conception, development and, now, data collection and compilation, is very much interlinked with Open Science initiatives in France. Its Data Management Plan was developed with the aid of the OPIDoR 25 platform. The narratives it collects will be hosted on the Nakala repository. Its ethics clearance process has proceeded through one of the recently established committees, and its data architecture generally has benefitted from the advice and support of personnel involved either in research units, Open Science platforms, TGIR Huma-Num or the Human Sciences Foundation. A discussion of its data management, ethics, and reuse is a good way of exemplifying Open Science as it has been adopted in France. All documentation referred to below has been made available in the Places dataset  (Kelleher & Bays, 2022 ) hosted on Nakala.
(4. 1) DATA MANAGEMENT Since more than one researcher is involved in Places, its Data Management Plan has several key aims: i) to stabilise the interview process, ii) to standardise the project storage architecture (file extensions etc), iii) to increase the reliability and comparability of ELAN transcriptions uploaded to Nakala (their annotation), and iv) to ensure the regularity and findability of the dataset itself. As concerns the first point, i) the interview process is supported by comprehensive project information sheets, a guide to possible questions and themes. Participants are made aware of the aims and rationale of the project through concept notes, the DMP, and through this paper and the Places dataset itself. One of the aims of pursuing an open and shared architecture is to offer future participants the possibility to be able to listen to and read other testimonies and biographies gathered in the context of the project, thereby building a cumulative archive.
A data management checklist ensures that the same steps are followed for each participant: a) first contact, b) choice of interview site, c) recording and photographing of the interview, d) data storage on the researcher PC, e) sharing and inter-researcher editing on Sharedocs, and f) uploading on Nakala. 25 https://opidor. fr/ (last accessed: 16 March 2022). Extract 4 The same segment as in Extract 2 that has now been coded for instances of repetition, using controlled vocabularies, and tiers. Kelleher and Bays Journal of Open Humanities Data DOI: 10. 5334/johd. 75 The second point, ii) raises questions of project storage architecture. Storage architecture concerns the hierarchisation of files and formats, their naming, and the handling of access, rights, and procedures for revising and updating.
Places drew up its data plan in line with DoRANum best practice (DoRANum, 2022) and has made available file naming conventions. The architecture aims to ensure that Places data is archived and treated in a comparable way across researchers. It is also a means of ensuring ethical compliance since it avoids stray files through numerical progression in pre-edited, edited, shared, and hosted file versions. Point three, iii) linguistic and critical discursive analysis are normed activities, falling under ISO 12620:2019 that sets standards for analytic and pragmatic terms and categories. This allows ELAN controlled vocabularies to be marked to standards, should one so wish, and for metadata to be interoperable across ELAN and Nakala. ELAN, in a similar fashion, allows a great deal of annotator and participant information to be allocated to each tier.
Since Places is generating a considerable amount of transcription work, the decision was made to use a third-party service for each initial transcription. HappyScribe 26 was involved in the project and, after consultation with their engineer, now offers an ELAN-importable. csv format for their transcriptions. Before sending to HappyScribe, as noted, each researcher edits the waveform for sensitive and confidential information (see discussion above). Use of a transcription service allows an impartial and quality-controlled base from which to start more detailed transcription (see section 3. 4 above). Point four, iv) the Nakala repository uses, typically, the Dublin Core Metadata Initiative 27 for collections and datasets. For each participant data file, a. csv metadata sheet compiled during the interview includes the non-invasive information that a participant is comfortable with sharing and that will assist in the discoverability and, therefore, reuse of the data.
(4. 2) ETHICAL CONSIDERATIONS Places data is pseudonymised rather than anonymised. This is to say that whilst the participant names are changed, and there is no confidential or sensitive identifying information retained in the Nakala dataset. Interviews are concerned with a participant's personal appreciations and life experiences. This kind of data remains much more identifiable than data collected in the context of large institutional research where one participant's response is equivalent to those responses given by other members of the cohort. This made the finding of a middle ground, between completely open and completely locked data (see discussion in section 2. 2 above) so much more important. This is to say that Places data should be open and available, but it should not be something that can be downloaded irresponsibly or automatically by data trawlers.
The DMP that accompanies this article is the fifth iteration of the document. This shows how long the consultative process has been to achieve a satisfactory solution to this ethical conundrum. A first, tentative, solution was to upload the dataset and complete its metadata so that it would be findable, but to embargo the participant data subject to written request made to the lead researchers. This proved to be unsustainable for several reasons: it required too much of institutional data officers, it was not consultable by the participants, and, to a certain extent, did little more than place the problem at one remove, since any data administration raised the same questions of allowable and disallowable access. The second solution, presented in this article, has been to upload all project data and documentation in corresponding files that are password zipped using 7-Zip.
This solution seems to be satisfactory in light of the following: i) it allows Places data to be entirely accessible to participants and researchers, ii) it allows Nakala to serve its primary objective as an open, consultable, project archive where one can receive updates on data itself and publications related to the data, iii) actual use of the data requires the downloading of the full participant data file with its associated metadata, and iv) since the password is given in the ReadMe which also lists full project information, the contacts of the researchers, the institutional data officers, and the applicable Creative Commons licence, access to the password implies acceptance of the ReadMe contents, v) finally, 7-Zip technology provides a level of protection against trawlers. Generally, in its ethical response, Places has implemented the so-called 'data and paper' rule, where data is stored on disk whilst identifying information is signed and completed on paper.
(4. 3) APPLICATIONS AND RE-USE Re-use of the Places dataset  (Kelleher & Bays, 2022)  is two-fold. On the one hand, there is a proposed re-use of the project documentation and data architecture. On the other, there is the data itself and its re-use for both linguistic and socio-historic purposes. Concerning re-use of the project documentation and data architecture, several elements can be isolated: i) the use of the repository, metadata, and storage architecture, ii) data management plans and documentation, and, finally, iii) ethics documentation. Re-use of these elements would allow a humanities project to more easily transition to a research population in, or related to, francophone countries, since they offer bilingual French/English translations. They are also illustrative of an European research environment generally.
French. This is a template that can, again, be used by another project. One of the additional uses of a Nakala-hosted dataset concerns the participants themselves. Even if they do not consult their data, they are aware that they are contributing to an archive of contemporary speech and language behaviour. This further provides an element of reflexivity to Places. As researchers work on the data, they are conscious of the fact that it will be made public and invite comment and criticism. Open dataset hosting is part of the action-research paradigm, as evoked by the University of Liege ethics committee (2022). In this respect, one use of the Nakala platform is to serve in communication between the project leaders and the participants. Nakala hosts the data, but it can also indicate links to all those publications and conferences that use the data by including a DOI on the data page.
This means that participants can track and be informed of what's happening to their data. This is, perhaps, one of the nicest ancillary benefits of the repository. Once the data are published, a link can be shared with those involved in the project. The Places dataset is designed to promote continuing investigation. The. eaf transcription files are fully modulable, which means that a person accessing the data can reannotate on ELAN, export to other textometric applications such as Atlas. ti (Scientific Software Development GmbH, 2022) , AntConc  (Anthony, 2022)  or TGIR Huma-Num's TXM 29 , dialogue with other platforms and reintegrate data into new corpuses. These corpuses can be place-based, since, in each case, one of the metadata entries is the site of the interview. One very significant goal of Places is, in this light, to contribute to the valuing of spoken narratives and to better understand how public space is accessed in our present conjuncture.
The tier-based functioning of ELAN means that the dataset can be studied for patterning across entries, since a tier can focus on a specific aspect of analysis (prosody, morpho-syntax, semantics, paralinguistics, etc), be extracted, and then compared to a similar tier in a different entry. Re-use of participant data can therefore concern studies of place (useful for ethnographic analysis), studies of interaction, and the features and functions of linguistic realisation. The participants are also members of a very specific, and quite rare, cohort. They are English speakers in a situation of enforced and prolonged language contact. This corpus, then, can also be used in studies of language variation. BobbyG's data is a good example of trilingual contact, as an example. 29 https://txm. gitpages.