dataesr/scientific-paragraphs-categorization huggingface dataset:
In 2011, the MMSH audio archive catalogue was integrated into the portal Isidore, which provides access to digital and digitised research data in humanities and social sciences in French-speaking countries internationally. In February 2013, the MMSH Sound Archives Centre was involved in the Europeana and Europeana Sounds project coordinated by the British Library, which brings together 7 national libraries, 5 archive and research centres, 2 other public bodies, 4 non-profit organisations, 3 universities, and 3 companies in 12 -European countries. The Europeana Sounds project deserves special attention because of its innovative potential for audio archives: not only does it allow access to one million audio documents, but it is also focused on promoting a creative re-use of the recordings. Scheduled to run from February 2014 to January 2017, Europeana Sounds is co-funded by the European Commission and the Europeana Sounds consortium.
In the case of audio material, the so-called 'related rights' appear to be very relevant too: they warrant a different term of protection and are given to performers, producers, recordists and broadcasters. Therefore, although a composition may be in the public domain, the related digital object may not enjoy the same status, exactly because of the related rights. The time limit concerning the related rights is 50 or 70 years after the first publication or the first communication to the public. A rather different case is represented by the database rights, whose time limit is 15 years after creation: they turn out to be very relevant in case an institution receives digital sound archives from another institution. Second, after a very careful analysis of Intellectual property rights, in case one or more of these rights applies to a certain digital work, it is important to obtain permission from all the rights' holders before publishing and reproducing it.
Finally, the guide provides a detailed account of the Europeana licensing framework, in order to facilitate Europeana's activities and, in particular, data ingestion into Europeana space. Although 'spoken word digital audio' objects are specifically mentioned in the Guidelines when describing the possible Intellectual property rights involved, the extraordinary variety of practices in fieldwork in oral history, linguistics, anthropology, and sociology certainly requires a more in-depth analysis, in order to both cover unpublished audio archives and consider the ethical issues involved in their dissemination (Zeytlin 2012). This is why the MMSH Sound Archive Centre is at present engaged in a project that focuses more directly on the dissemination of research data in the social sciences and humanities: a working group under the auspices of the DARIAH (Digital Research Infrastructure for the Arts and Humanities) consortium is elaborating a best practice document entirely dedicated to ethical and legal issues.
Ethical and Legal Issues: An Example from the MMSH Audio Archive In partnership with the team of the MMSH Sound Archives Centre, and according to the topics explored, the researchers choose the terms of access to their data at the moment in which they create the deposit. The MMSH Sound Archive Centre offers the scholars a set of tools (e. g. legal agreements, classification and cataloguing templates) to help them disseminate their research in accordance with best practices and ethical and legal guidelines. As a result, around 2000 h of audio recordings are directly accessible online. From the ethical and scientific viewpoint, field recordings cannot be disseminated as standalone materials, i. e. without any contextual information. Audio documents in archives need to be carefully interpreted in order to be understood, and any relevant note, drawing, or diary produced by the researcher before, during and after the fieldwork constitutes a precious resource for correctly interpreting the documents.
In this respect, the contextualisation of field recordings is a thorny issue: each recorded document collected during fieldwork has to be used and re-used together with all the different elements of the scientific research from which it originates  (Descamps et al. 2005). It is very important to clarify that these recordings are not 'the truth'. Indeed, they refer to the witnesses' representation of the given situation. For this reason, sound archives centres usually make sure that they embed as much contextual information as possible into the digital materials. At the MMSH Sound Archives Centre, the sound archives can be harvested in Dublin Core (DC) on Isidore, a platform allowing access to the digital data of Humanities and Social Sciences, in Europeana Data Model (EDM) on Europeana, or in Encoded Archival Description (EAD) on Calames, i.
The matched use of VIAF and Worldcat ensures two intertwined properties first, informants are no longer hidden in archive databases, and second, their contribution is held in academic databases throughout the world. Furthermore, once the informants' names have been identified, they are given an international identifying number and thus benefit from the standard features ensured by the International Standard Name Identifier (ISNI): uniqueness, stability, visibility, sustainability, interoperability, and independence  (Angjeli et al. 2014). Uniqueness comes from the fact that a name is unique and duplication is not allowed. Stability derives from the fact that ISNI is an ISO standard (ISO 27729:2012). As for visibility, ISNI facilitates the process of Search Engine Optimization in order to identify the informants' names.
3 efore ethical and legal issues were at the centre of the scientific debate, the voices of the witnesses recorded in fieldwork were not integrated in academic databases. Finding a way to face ethical and legal issues might ensure that the sound archives' voices be listened online as a part of our common cultural heritage. Clarifying these issues is crucial in order to reach the main objectives of dissemination, crowdsourcing, creative re-use, discovery and referencing of sound data, as also the Gra. fo project proves.
4. 2 From the Database to the Website The Gra. fo database uses the MySQL system and consists of 59 interconnected tables, some of which have specific constraints. The tables contain information on the fields created for cataloguing and for the creation of the preservation copies, stored in a specific server archive with Raid 5 configuration. The collaborators devoted to digitizing and cataloguing interact with the database through specific applications, respectively called Audiografo PP and Audiografo CP, with userfriendly interfaces consisting of drop-down menus, checkboxes and open fields. The web portal is a technological interface which, by querying the database and the server archive containing the preservation copies, allows the end user to search all documents collected in Gra. fo (cataloguing records,.
With regard to processing of oral sources [of information], it will be necessary for the interviewees to give their express consent, whether orally or not, even based on summarized information including at least the interviewer's identity and activity and the purpose of the data collection. 2. If an Archive acquires oral sources, the interviewer will be requested to produce a written statement to the effect that the purposes of the interview have been notified and the relevant consent has been obtained from the interviewees. 6 Secondly, given this rather thorny framework, the key word of the Gra. fo staff has been 'transparence', specifically by making the project' aims explicit-either by a face-to-face communication or by letter-to all persons involved: interviewees, interviewers, archive owners, but also archive curators, and-if possible-the descendants of interviewees and interviewers.
Scientific communities are increasingly concerned with community engagement and empowerment, in order to enhance good behavioural norms inside the communities themselves. As claimed in Art. 15 of the UNESCO Convention for the Safeguarding of the Intangible Cultural Heritage, heritage communities, groups and, where appropriate, individuals are asked to create, maintain and transmit such heritage, and to be actively involved in its management. Finally, the issue of audio archives accessibility has encouraged the rethinking of personal data protection. This should be viewed as a renewed impulse to re-define the privacy value, considering the need to rethink what people consider really worth of protection  (Dewandre 2015: 203). As  Oates (2015: 225).
claims: The online agora is a precious public resource. Currently, it is being colonized by corporations and states, in ways that asymmetrically reassign the power of information and personal data to the elites. What is needed is an understanding that a public agora should be conceptualized and protected in a way that tips the balance away from the elites and toward the citizens. In the realm of the digital sound archive, ethical and legal issues are no longer themes for bureaucrats. Asking all stakeholders involved in the process of building digital audio archives (from individual researchers, to archives' owners, from interviewees and interviewers and their descendants to public and private institutions) what can be freely accessed on the web (and with what kind of constraints) amounts to setting the ethical issues at the foreground of research.
In order to obtain useful answers, and positive attitudes towards web diffusion, it is necessary to clearly and honestly explain the reasons behind accessibility. In other words, communication of research results becomes an essential task for scholars. In this respect, the most crucial topic with respect to accessibility concerns the legal issues related to the digital archives that were produced when the web did not yet exist and legal agreements during fieldwork were the exception rather than the rule. A large amount of such data could run the risk of remaining forever inaccessible on the web, unless adequate and careful balance is found between open access on the one side, and ownership rights and ethical issues on the other side. Digital audio archives can thus offer a valuable contribution in establishing rights, duties and ways to access important pieces of the European Intangible Cultural Heritage.
We merged all sequences extracted from each individual, and randomly sampled a single sequence with minimum mapping and sequence quality to represent each SNP, restricting to individuals with at least 9,000 SNPs covered at least once (Methods). We obtained genome-wide data passing quality control for 45 individuals on whom we had a median coverage of 172,819 SNPs. We assembled radiocarbon dates for 26 individuals (22 new generated for this study) (Supplementary Data Table  1 ). The newly reported ancient individuals date to ~12,000-1,400 BCE and come from the southern Caucasus (Armenia), northwestern Anatolia (Turkey), Iran, and the southern Levant (Israel and Jordan) (Supplementary Data Table  1 , Fig. 1a ). (One individual had a radiocarbon date that was not in agreement with the date of its archaeological context and was also a genetic outlier.
) The samples include Epipaleolithic Natufian hunter-gatherers from Raqefet Cave in the Levant (12,000-9,800 BCE); a likely Mesolithic individual from Hotu Cave in the Alborz mountains of Iran (probable date of 9,100-8,600 BCE); Pre-Pottery Neolithic farmers from 'Ain Ghazal and Motza in the southern Levant (8,300-6,700 BCE); and early farmers from Ganj Dareh in the Zagros mountains of western Iran (8,200-7,600  BCE). The samples also include later Neolithic, Chalcolithic (~4,800-3,700 BCE), and Bronze Age (~3,350-1,400 BCE) individuals (Supplementary Information, section 1). We combined our data with previously published ancient data  7, 8, 9, 10, 8, [10] [11] [12] [13] [14] [15]  to form a dataset of 281 ancient individuals. We then further merged with 2,583 present-day people genotyped on the Affymetrix Human Origins array  13, 16  (238 new) (Supplementary Data Table  2 ; Supplementary Information, section 2).
We grouped the ancient individuals based on archaeological culture and chronology (Fig. 1a ; Supplementary Data Table  1 ). We refined the grouping based on patterns evident in Principal Components Analysis (PCA)  17  (Fig. 1b ; Extended Data Fig. 1 ), ADMIXTURE model-based clustering  18  (Extended Data Fig. 2a ), and 'outgroup' f 3 -analysis (Extended Data Fig. 3 ). We used f 4 -statistics to identify outlier individuals and to cluster phylogenetically indistinguishable groups into 'Analysis Labels' (Supplementary Information, section 3). We analyzed these data to address six questions. (1) Previous work has shown that the first European farmers harboured ancestry from a Basal Eurasian lineage that diverged from the ancestors of north Eurasian hunter-gatherers and East Asians before they separated from each other  13.
Migrations from the Near East also occurred towards the southwest into East African populations which experienced West Eurasian admixture ~1,000 BCE  31, 32. Previously, the West Eurasian population known to be the best proxy for this ancestry was present-day Sardinians  32  , who resemble Neolithic Europeans genetically  13, 33. However, our analysis shows that East African ancestry is significantly better modelled by Levantine early farmers than by Anatolian or early European farmers, implying that the spread of this ancestry to East Africa was not from the same group that spread Near Eastern ancestry into Europe (Extended Data Fig. 5 ; Supplementary Information, section 8). In South Asia, our dataset provides insight into the sources of Ancestral North Indians (ANI), a West Eurasian related population that no longer exists in unmixed form but contributes a variable amount of the ancestry of South Asians  34, 35  (Supplementary Information, section 9) (Extended Data Fig.
5 ). We show that it is impossible to model the ANI as being derived from any single ancient population in our dataset. However, it can be modelled as a mix of ancestry related to both early farmers of western Iran and to people of the Bronze Age Eurasian steppe; all sampled South Asian groups are inferred to have significant amounts of both ancestral types. The demographic impact of steppe related populations on South Asia was substantial, as the Mala, a south Indian population with minimal ANI along the 'Indian Cline' of such ancestry  34, 35  is inferred to have ~18% stepperelated ancestry, while the Kalash of Pakistan are inferred to have ~50%, similar to presentday northern Europeans  7.
Testing for contamination and quality control For each ancient DNA library, we evaluated authenticity in several ways. First, we estimated the rate of matching to the consensus sequence for mitochondrial genomes sequenced to a coverage of at least 10-fold from the initial screening data. Of the 76 libraries that contributed to our dataset (coming from 45 samples), 70 had an estimated rate of sequencing matching to the consensus of >95% according to contamMix  5  (the remaining libraries had estimated match rates of 75-92%, but gave no sign of being outliers in principal component analysis or X chromosome contamination analysis so we retained them for analysis) (Supplementary Data Table  1 ). We quantified the rate of C-to-T substitution in the final nucleotide of the sequences analyzed, relative to the human reference genome sequence, and found that all the libraries analyzed had rates of at least 3%  38  , consistent with genuine ancient DNA.
Affymetrix Human Origins genotyping data We genotyped 238 present-day individuals from 17 diverse West Eurasian populations on the Affymetrix Human Origins array  16  , and applied quality control analyses as previously described  13  (Supplementary Data Table  2 ). We merged the newly generated data with data from 2,345 individuals previously genotyped on the same array  13. All individuals that were genotyped provided individual informed consent consistent with studies of population history, following protocols approved by the ethical review committees of the institutions of the researchers who collected the samples; the ethical reviews applying to each of these individual sample collections are specified in Supplementary Data Table  2. The collection and analysis of genome-wide on anonymized samples at Harvard Medical School for the purpose of studying population history was approved by the Harvard Human Research Protection Program, protocol 11681, re-reviewed on July 12 2016.
Anonymized aliquots of DNA from all individuals were sent to the core facility of the Center for Applied Genomics at the Children's Hospital of Philadelphia for genotyping and data processing. For 127 of the individuals with newly reported data, the informed consent was consistent with public distribution of data, and the data can be downloaded at http://genetics. med. harvard. edu/ reich/Reich_Lab/Datasets. html. To access data for the remaining 111 samples, researchers should send a signed letter to D. R. containing the following text: "(a) I will not distribute the data outside my collaboration; (b) I will not post the data publicly, (c) I will make no attempt to connect the genetic data to personal identifiers for the samples, (d) I will use the data only for studies of population history, (e) I will not use the data for any selection studies, (f) I will not use the data for medical or disease-related analyses, (g) I will not use the data for commercial purposes.
Datasets We carried out population genetic analysis on two datasets: (i) HO includes 2,583 presentday humans genotyped on the Human Origins array  13, 16  including 238 newly reported (Supplementary Data Table  2 ; Supplementary Information, section 2), and 281 ancient individuals on a total of 592,146 autosomal SNPs. (ii) HOIll includes the 281 ancient individuals on a total of 1,055,186 autosomal SNPs, including those present in both the Human Origins and Illumina genotyping platforms, but excluding SNPs on the sex chromosomes or additional SNPs of the 1240k capture array that were included because of their potential functional importance  8. We used HO for analyses that involve both ancient and present-day individuals, and HOIll for analysis on ancient individuals alone. We also use 235 individuals from Pagani et al.
ADMIXTURE Analysis We carried out ADMIXTURE analysis  18  of the HO dataset after pruning for linkage disequilibrium in PLINK  45, 46  with parameters --indep-pairwise 200 25 0. 4 which retained 296,309 SNPs. We performed analysis in 20 replicates with different random seeds, and retained the highest likelihood replicate for each value of K. We show the K=11 results for the 281 ancient samples in Extended Data Fig. 2a  (this is the lowest K for which components maximized in European hunter-gatherers, ancient Levant, and ancient Iran appear).
f-statistics We carried out analysis of f 3 -statistics, f 4 -ratio, and f 4 -statistics statistics using the ADMIXTOOLS 16 programs qp3Pop, qpF4ratio with default parameters, and qpDstat with f4mode: YES, and computed standard errors with a block jackknife  47. For computing f 3statistics with an ancient population as a target, we set the inbreed:YES parameter. We computed f-statistics on the HOIll dataset when no present-day humans were involved and on the HO dataset when they were. We computed the statistic f 4 (Test, Mbuti; Altai, Denisovan) in Fig. 2  on the HOIll dataset after merging with whole genome data on 3 Mbuti individuals from Panel C of the Simons Genome Diversity Project  48. We computed the dendrogram of Extended Data Fig. 3  showing hierarchical clustering of populations with outgroup f 3 -statistics using the open source heatmap.
Testing for the number of streams of ancestry We used the qpWave  34, 49  software, described in Supplementary Information, section 10 of ref. 7  , to test whether a set of 'Left' populations is consistent with being related via as few as N streams of ancestry to a set of 'Right' populations by studying statistics of the form X(u, v) = F 4 (u 0 , u; v 0 , v) where u 0 , v 0 are basis populations chosen from the 'Left' and 'Right' sets and u, v are other populations from these sets. We use a Hotelling's T 2 test  49  to evaluate whether the matrix of size (L-1)*(R-1), where L, R are the sizes of the 'Left' and 'Right' sets has rank m. If this is the case, we can conclude that the 'Left' set is related via at least N=m+1 streams of ancestry related differently to the 'Right' set.
Extended Data Figure 4. Reduction of genetic differentiation in West Eurasia over time We measure differentiation by F ST. Each column of the 5×5 matrix of plots represents a major region and each row the earliest population with at least two individuals from each major region. Extended Data Figure 5. West Eurasian related admixture in East Africa, Eastern Eurasia and South Asia (a) Levantine ancestry in Eastern Africa in the Human Origins dataset, (b) Levantine ancestry in different Eastern African population in the dataset of Pagani et al. (2012); the remainder of the ancestry is a clade with Mota, a ~4,500 year old sample from Ethiopia 50. (c) EHG ancestry in Eastern Eurasians, or (d) Afontova Gora (AG2) ancestry in Eastern Eurasians; the remainder of their ancestry is a clade with Onge.
Acknowledgements We thank the 238 human subjects who donated samples for genome-wide analysis, and  D. Labuda  and  P. Zalloua  for sharing samples from Poland and Lebanon. The Fig. 1a map was plotted in R using the worldHiRes map of the 'mapdata' package (using public domain data from the  CIA World Data Bank II). We thank  O. Bar-Yosef ,  M. Bonogofsky ,  I. Hershkowitz ,  M. Lipson ,  I. Mathieson ,  H. May ,  R. Meadow ,  I. Olalde ,  S. Paabo ,  P. Skoglund , and  N. Nakatsuka  for comments and critiques, and  D. Bradley ,  M. Dallakyan ,  S. Esoyan ,  M. Ferry  and  M. Michel , and  A. Yesayan , for contributions to bone preparation and ancient DNA work D. F. and M. N. were supported by  Irish Research Council  grants  GOIPG/2013/36  and  GOIPD/2013/1 , respectively. S. C. was funded by the  Irish Research Council for Humanities and Social Sciences (IRCHSS) ERC   Support Programme.
Q. F. was funded by the  Bureau of International Cooperation of the Chinese Academy of Sciences , the  National Natural Science Foundation of China  ( L1524016 ) and the  Chinese Academy of Sciences Discipline Development Strategy Project  ( 2015-DX-C-03 ). The Scottish diversity data was funded by the  Chief Scientist Office of the Scottish Government Health Directorates  [ CZD/16/6 ], the  Scottish Funding Council  [ HR03006 ], and a project grant from the  Scottish Executive Health Department, Chief Scientist Office  [ CZB/4/285 ]. M. S. ,  A. Tön. , M. B. and P. K. were supported by the  German Research Foundation  ( CRC 1052 ;  B01 ,  B03 ,  C01 ). M. S. -P. was funded by a  Wenner-Gren Foundation Dissertation Fieldwork  Grant (# 9005 ), and by the  National Science Foundation DDRIG  ( BCS-1455744 ).
P. K. was funded by the  Federal Ministry of Education and Research, Germany  (FKZ:  01EO1501 ). J. F. W acknowledges the  MRC "QTL in Health and Disease" programme grant. The Romanian diversity data was supported by the  EC Commission, Directorate General XII (Supplementary Agreement   ERBCIPDCT 940038  to the Contract  ERBCHRXCT 920032 , coordinated by  Prof. A. Piazza , Turin, Italy). M. R. received support from the  Leverhulme Trust 's  Doctoral Scholarship programme. O. S. and A. Tor. were supported by the  University of Pavia  ( MIGRAT-IN-G ) and the  Italian Ministry of Education, University and Research :  Progetti Ricerca Interesse Nazionale 2012. The Raqefet Cave Natufian project was supported by funds from the  National Geographic Society  (Grant # 8915-11 ), the  Wenner-Gren Foundation  (Grant # 7481 ) and the  Irene Levi-Sala CARE Foundation , while radiocarbon dating on the samples was funded by the  Israel Science Foundation  (Grant  475/10 ;  E.