dataesr/scientific-paragraphs-categorization huggingface dataset:
148). Une librairie en ligne met à disposition d'un internaute une base de données présentant l'offre éditoriale à laquelle sont associés un système de paiement et une logistique intégrée permettant l'acheminement rapide de livres vers le consommateur  (Gaudry, 2008). Parmi les détaillants, on observe plusieurs éléments de différenciation. Un premier découpage s'opère entre des acteurs disposant de leur propre offre (Lavoisier. fr, Eyrolles. com, Amazon. fr, FNAC. com, etc. ) et des plateformes présentant celle de partenaires, adhérents du site, qu'ils soient des librairies indépendantes ou des particuliers (Livreenpoche. com, PriceMinister. com, Marketplace 7  ). Un second clivage existe entre les « tout en ligne » (« pure players ») et les enseignes ayant ouvert une extension numérique de leurs magasins physiques (les « bricks and mortar »).
Parmi l'ensemble des dispositifs présents, on en distingue trois, qui occupent des fonctions différentes : la base de données bibliographiques vient informer le client, des outils typiques du marketing relationnel visent à anticiper la demande en tentant de cibler, grâce à des techniques précises, les envies de lecture des consommateurs, et enfin, le développement de contenus éditoriaux de la part des clients contribue à équiper l'acheteur de nouvelles ressources pour mieux le rassurer et le protéger des incertitudes du marché.
Une base de données quasi-exhaustive : l'accès commercial à l'information L'un des premiers investissements pour ces structures a été de constituer une base de données bibliographiques avant l'ouverture du site. Elle regroupe un ensemble très large de renseignements : le titre du livre, le nom de l'auteur, l'éditeur, le prix, l'  ISBN (l'International Standard Book Number) , la date de parution, le nombre de pages, le poids, le format, le résumé, la couverture, la critique des internautes et, parfois, des extraits du texte. La constitution de la base de données est la première innovation renouvelant non seulement les conditions d'achats du livre, mais également l'accès aux informations concernant la production éditoriale. Le développement des moteurs de recherche, outils puissants visant la quête de références, permet d'activer la base de données selon les requêtes de l'internaute.
Cette forme de vente prend cependant son envol au milieu des années 2000 avec l'accès élargi au réseau Internet et au haut débit. 5 L'appréciation du lecteur s'illustre par un système d'avis et de notation, mis en place par Amazon au cours des années 1990 et étendu aujourd'hui à la quasi-totalité des sites marchands(Beauvisage  et al. , 2013). 6 En France, l'invention du Minitel rend possible la consultation de bases de données et la commande d'ouvrages. La première expérience en la matière est celle de P. Magnard, fils du fondateur des éditions scolaires. Il crée en 1988 une base de données pour développer la vente par correspondance par Minitel sous l'enseigne Alapage. Dix ans plus tard, le même outil est exploité pour la librairie en ligne Alapage, inaugurée en 1996.
This is also expressed in the large fraction of individuals who do not become self-employed because of their inability to raise the necessary financial resources. Also for the UK,  Taylor (2001)  reports a positive effect of windfall gains (inheritance and lottery wins) on the probability of entering self-employment. The author emphasizes that liquidity constraints can be detrimental for starting a new business, for the growth of entrepreneurships and for the success of small businesses. Henley (2004)  analyzes the impact of both windfall financial gains and house price shocks on hours worked, and suggests that there are significant substitution effects, in particular, in response to house price shocks. In this paper, we analyses the linkages between windfall gains and working hours using data from the European Community Household Panel Longitudinal Users' Database.
Third, with the panel dataset, we observe a rich set of personal characteristics of individuals. This gives us an opportunity to better understand the ways that participation and working-hours decisions differ between individuals. Finally, given that the panel dataset covers a relatively long sample period, we can account for the time-variation in labour supply, a feature that would not be captured in a cross-sectional study. The remainder of the paper is structured as follows. Section 2 describes the data. Section 3 presents the econometric approach. Section 4 discusses the empirical results. Section 5 concludes.
Data The data is obtained from the European Community Household Panel Longitudinal Users' Database  (ECHP henceforth). This is a large panel data set that contains household-level and person-level information over time, covering eight survey years from 1994 to 2001 1. The data includes 15 EU countries: Germany, Denmark, The Netherlands, Belgium, Luxembourg, France, United Kingdom, Ireland, Italy, Greece, Spain, Portugal, Austria, Finland and Sweden. It is an unbalanced panel with a maximum length of 8 years for each individual 2. In what follows, the analysis is done at the individual level, rather than at the level of households, with age restricted to 25-60 years 3. This age band is set in order to avoid complications that arise due to education and retirement choices 4. The data on incomes and wages are converted using purchasing power parity (PPP) in order to allow for comparisons across countries and over time.
Therefore, our estimates can be thought of as being at the lower end of the "true" effect. To ease discussion, we label people that have received windfall gains as "winners" and the rest as "non-winners". If we only include individuals who were observed at least twice over time, there are 100,289 individuals in our sample. Most of them (88. 4%) never received any inheritance, gift or lottery winnings of more than 2000 EUR. 8,824 individuals (or a fraction of 8. 8%) received windfall gains only once, and about 2. 8% of individuals received windfall gains more than once. Because in the regression analysis it is not straightforward to deal with individuals who received windfall gains more than once we include in our empirical analysis only individuals who received windfall gains once. Compared to similar research done by other authors, this is quite a large sample and represents one of the advantages of using the ECHP dataset 8.
8 For instance,  Imbens et al. (2001)  have about 237 winners,  Joulfaian and Wilhelm (1994)  have 439 heirs in their sample,  Holtz-Eakin et al. (1993)  have 2,700 married couples and 1632 individuals in their sample, and  Henley (2004)  has around 5,400 men and women included. 9 Interestingly,  Joshi et al. (1996)  show that the presence of children reduces full-time employment among women. Similarly, Joshi (1998) highlights the impact of child-rearing on women's time use. 10 Hourly wage is a measure of offered wages in the labour market. Reported data is in purchasing power parity units in order to be comparable across countries. Hourly wage is calculated from net monthly wage given in the data, divided by weekly working hours times 4. 33 to correct for the average number of weeks in one month.
000 Household income -unearned income 1,448 6,651 848 74,598 0. 000 Personal income 15,589 6,674 12,095 75,040 0. 000 Personal income -from working 13,270 6,674 10,222 75,040 0. 000 Personal income -unearned income 690 6,674 376 75,040 0. 000 Personal hourly wage 7. 68 6,674 6. 78 75,040 0. 000 Total hours working per week 30. 57 6,497 28. 26 73,932 0. 000 Source: European Community Household Panel Longitudinal Users' Database. All individuals of age 25-60. Winners are observed one period before receiving windfall gains. This approximately corresponds to period 3 in the sample for non-winners.
1 This work has been carried out thanks to the support of the A* MIDEX project  (no  ANR-11-IDEX-0001-02 ) funded by the " Investissements d' Avenir" French Government program , managed by the  French National Research Agency (ANR). 2 We extend sincere thanks to the editors and staff of Ethics in Progress, especially  Ewa Nowak  for her continued support and assistance with this project.
The conventional tools of the "web as corpus" framework rely heavily on URLs obtained from search engines. Recently, the corresponding querying process became much slower or impossible to perform on a low budget. I try to find acceptable substitutes, i. e. viable link sources for web corpus construction. To this end, I perform a study of possible alternatives, including social networks as well as the Open Directory Project and Wikipedia. Four different languages (Dutch, French, Indonesian and Swedish) taken as examples show that complementary approaches are needed. My scouting approach using open-source software leads to a URL directory enriched with metadata which may be used to start a web crawl. This is more than a drop-in replacement for existing tools since said metadata enables researchers to filter and select URLs that fit particular needs, as they are classified according to their language, their length and a few other indicators such as host-and markup-based data.
Introduction 1. 1 The "web as corpus" paradigm and its URL seeds problem The state of the art tools of the "web as corpus" framework rely heavily on URLs obtained from search engines. The BootCaT method  (Baroni and Bernardini, 2004)  consists in repeated search engine queries using several word seeds that are randomly combined, first coming from an initial list and later from unigram extraction over the corpus itself. As a result, so-called "seed URLs" are gathered which are used as a starting point for web crawlers. This approach is not limited to English: it has been successfully used by  Baroni et al. (2009)  and  Kilgarriff et al. (2010)  for major world languages. Until recently, the BootCaT method could be used in free web corpus building approaches. To my best knowledge it is now passé because of increasing limitations on the search engines' APIs, which make the querying process on a low budget much slower or impossible.
ca, a microblogging service similar to Twitter; and Reddit, a social bookmarking and microblogging platform. Perhaps not surprisingly, these data sources display the issues linked to API instability mentioned above. The example of identi. ca is telling: until March 2013, when the API was closed after the company was bought, it was a social microblogging service built on open source tools and open standards, the advantages compared to Twitter include the Creative Commons license of the content, and the absence of limitations on the total number of pages seen. Another data source is the Open Directory Project (DMOZ 5  ), where a selection of links is curated according to their language and/or topic. The language classification is expected to be adequate, but the amount of viable links is an open question, as well as the content.
The first number can be used to find possible spam or irrelevant links, with the notable exception of websites like Amazon or Wikipedia, which are quite easy to list. The latter may be used to assess the richness (or at a given level the suspiciousness) of a website by the company it keeps. While this indicator is not perfect, it enables users to draw conclusions without fetching all the downstream URLs. Moreover, even if I do not take advantage of this information in this study, the fetcher also records all the links it "sees" (as an origin-destination pair), which enables graph-based approaches such as visualization of the gathered network or the as-sessment of the "weight" of a website in the URL directory. Also, these metadata may very well be useful for finding promising start URLs.
Language identification I consider the fact that a lot of web pages have characteristics which make it hard for "classical" NLP approaches like web page language identification based on URLs  (Baykan et al. , 2008)  to predict the languages of the links with certainty. That is why mature NLP tools have to be used to qualify the incoming URLs and enable a language-based filtering based on actual facts. The language identification tool I used is langid. py (Lui and Baldwin, 2012). It is opensource, it incorporates a pre-trained model and it covers 97 languages, which is ideal for tackling the diversity of the web. Its use as a web service makes it a fast solution enabling distant or distributed work. As the software is still under active development, it can encounter difficulties with rare encodings.
Characteristics of the BootCaT approach First of all, I let my toolchain run on URLs obtained using the BootCaT approach, in order to get a glimpse of its characteristics. I let the URL extractor run for several weeks on Indonesian and Swedish and only a few days for Dutch and French, since I was limited by the constraints of this approach, which becomes exponentially slower as one adds target languages. 6 The results commented below are displayed in table  1. The domain name reduction has a substantial impact on the set of URLs, as about a quarter of the URLs at best (for French) have different domain names. This is a first hint at the lack of diversity of the URLs found using the BootCaT technique. Unsurprisingly, the majority of links appear to be in the target language, although the language filters do not seem to perform very well.
Discussion I also analyzed the results regarding the number of links that lead out of the page's domain name. For all sources, I found no consistent results across languages, with figures varying by a factor of three. Nonetheless, there seem to be a tendency towards a hierarchy in which the search engines are on top, followed by social networks, Wikipedia and DMOZ. This is one more hint at the heterogeneous nature of the data sources I examined with respect to the criteria I chose. This hierarchy is also one more search engines queries are believed to be fast and reliable in terms of quantity. This method was fast, as the web pages are long and full of links, which enables to rapidly harvest a large number of web pages without having to worry about going round in circles. The researchers using the Boot-CaT method probably took advantage of the undocumented but efficient filtering operations which search engines perform in order to lead to reliable documents.
As a plea for a technicalities-aware corpus creation, I wish to bring to linguists' attention that the first step of web corpus construction in itself can change a lot of parameters. I argue that a minimum of web science knowledge among the corpus linguistics community could be very useful to fully comprehend all the issues at stake when dealing with corpora from the web. The toolchain used to perform these experiments is open-source and can be found online. 7  The resulting URL directory, which includes the metadata used in this article, is available upon request. The light scouting approach allows for regular updates of the URL directory. It could also take advantage of the strengths of other tools in order to suit the needs of different communities.
For several years, and even decades, data integration has been a major problem in computer sciences. When it becomes necessary to process information from different data sources, several problems may appear, making the process of integration more difficult. Nowadays, more and more information is being sent and received and is made available on the Web and Data Integration is becoming even more important. This is especially the case in the emerging trend of Open Data (OD). Integrating data from public entities can be a difficult process. Large quantities of datasets are made available. However, an important level of heterogeneity may also exist: Datasets exist in different formats, forms and shapes. While it is important to be able to access this information, it would also be completely useless if we were not able to interpret it.
INTRODUCTION The main aims of Data Integration are to select and combine information from different data sources/systems/entities into a unified view, in a way that users can exploit and analyse it conveniently. For several years, it has been a major subject of study in computer science  (Ziegler and Dittrich, 2004). The topic has recently gained new importance due to the appearance of numerous new information sources, like Social Media, Blogs, Scientific Data, commercial data, Big Data and Open Data (OD). These data sources increase the data volumes and the potential number of providers significantly, with data data coming from public and private entities, as well as from individuals. The relatively recent concept of OD is a major example of this phenomenon. OD makes information formerly hidden "inside" public and private organizations available and accessible to everyone at little or no cost and without permission limitations.
General Overview The appearance of new information sources not only contributes to the growing amount of information, it also increases the heterogeneity of data sources. Data Integration processes have become even more complicated and demanding. OD integration is currently a subject of major importance. As an example, it is in the focus of the current EU research framework programme Horizon 2020  (Commission, 2014). One topic of the ICT2014-1 call (EuropeanCommission, 2013) is ICT-15-2014: "Big Data and Open Data Innovation and take-up". It focuses on the entire value chains and reuse of Open (and Big) Data. It is a major problem because of the difficulty of integrat-ing heterogeneous datasets. Datasets may be built using completely different methods (formats, schema, metadata, etc. )  (Rivero et al.
Problems and Challenges The OD movement not only has benefits. The fact that public and private entities provide their datasets brings issues of privacy, ownership, availability, usability, accuracy and data combination  (Janssen et al. , 2012). Different challenges related to interoperability remain unresolved. Entities continue to build and furnish datasets without applying common standards and using heterogeneous systems. These datasets may be constructed using different and inconsistent techniques. Actually, and in general, Open Government Data initiatives publish their data using one of the following two general approaches  (Kalampokis et al. , 2011) : • The data is available on the Web as downloadable files in different formats, e. g. Excel, CSV, XML, etc. • The data is available on the Web using RESTful APIs and SPARQL interfaces, as linked data.
Individual datasets, made up of data -and metadata in the best case scenario -are interesting and useful on their own. Nevertheless, the positive and collaborative effect of using public and private information may be higher if data of different types (scientific, social media, etc. ) and delivered from several entities is combined, compared and linked. Some of the major problems and constraints which may be encountered when trying to integrate multi-source data are related to the following topics: • Structure and formats used -Given the high number of different sources and datasets, it is not astonishing that Public Sector Information (PSI) is published following different modelling paradigms (e. g. tabular, relational)  (McCusker et al. , 2012)  and formats: ZIP, CSV, XML, EX-CEL, PDF, etc.
Sometimes, data is even provided in non-machine-readable and/or proprietary formats; • Metadata -Metadata is of paramount importance for data integration and is one of the chief components of PSI systems for OD provisioning. A metadata schema is one of the main parts of a PSI system which should be characterized in a unified way  (Bountouri et al. , 2009). In other words, metadata may be defined as necessary and adequate so that data can be understood, shared and reused  (Edwards et al. , 2011). If metadata provided with a given dataset is not well-formed.
DATA2014-3rdInternationalConferenceonDataManagementTechnologiesandApplications and/or complete, final users may have difficulties finding its related dataset  (Houssos et al. , 2012). Metadata provides the means to discover datasets, access them and understand them. Metadata normally refers to information about context and content (for example, a title, a description, an author, etc. ) of datasets. Most of metadata schemas implemented in the public sector have been designed for national requirements. In Australia, for example, the AGLS Metadata Standard was adopted (NationalArchivesofAustralia, 2010), New Zealand adopted the New Zealand Government Locator Service (NZGLS) while the United Kingdom chose another option, the e-Government Metadata Standard (eGMS)  (Charalabidis et al. , 2009) ; • Accessibility, Permanence and Timeliness -If OD is commercially exploited, the providers should respond to typical business requirements in terms of accessibility, permanence and timeliness.
Outdated information, missing information, or information that is not accessible because of technical or other issues, cannot be the basis for reliable business processes. On the other hand, it seems unrealistic to hope that the public sector with its limited resources can offer the same service levels as commercial data providers. The integration processes must tackle these problems -or at least make them visible when they occur  (Gurstein, 2011) ; • Trust and Data Provenance -More and more, the need for having information and knowledge about data provenance is important. Data provenance, if it can be determined, may be used by users/data consumers to evaluate and interpret the information provided  (Moreau et al. , 2008). OD Integration processes and applications should be aware of data provenance, and offer efficient and reliable ways to visualize and judge it; • Multilingualism and cultural differences -The example of the European Union, with its 28 member states and a total of 24 official languages, shows that the wealth of data that has been described above is actually a linguistic mess.
Furthermore, cultural differences can already lead to different semantics for basic integration problems: An address in France is not necessarily the same "concept" as it is in Germany, for example. Ideally, information represented in different languages should not hinder its integration. (Rehm and Uszkoreit, 2011). Even in a scenario where OD integration is technically possible, organizational and legal barriers may exclude or complicate collaboration and the sharing of data. Public and private entities may have some constraints in opening and sharing their information. They may claim ownership and/or control over certain datasets  (Martin et al. , 2013).
Linked Open Data OD may be defined in different forms -it may be represented as Linked Data. Linked Data refers to best practices for publishing and connecting data on the web that are machine-readable and may come from different sources  (Bizer et al. , 2009). The adoption of these practices leads to a concept where there is a global web space in which both documents and data -from different and multiple domains -are linked. When OD is Linked Data, it is called Linked Open Data. The main objective of Linked Open Data is to help the Web of Data to identify datasets that are available under open licences (OD sets), convert them to a Resource Description Framework (RDF) applying Linked Data principles and finally publish them on the Internet. Furthermore, as well as Linked Open Data being concerned with the data publication aspect, it also takes the data consumption perspective  (Bauer and Kaltenböck, 2011).