dataesr/scientific-paragraphs-categorization huggingface dataset:
The Data GrandLyon platform is not designed to provide these intermediary steps. This might be justifiedby the budget constraints and a risk of biased data interpretation. Capital cities like London, Chicago and Seoul provide open data visualisation and analysis themselves. However, for the so-called secondary cities, that is, average-size non-capital cities with less resources, but having a well-developed ecosystem of civil society actors, such as Lyon in France and many Latin American cities rich in civic engagement initiatives, a more collaborative solution might be more adapted to their context. The studied associations in Lyon have the expertise to fill in the missing elements between the open data and the end result in the field of transparency and citizen engagement. Additionally, they can offer solutions to many of the needs analysed in the case study, such as data co-contribution and analysis, user tutorials and animation of both online offline interaction, if they are engaged to participate, taking into account their own motivations, like financial sustainability, their pro-social motivations that are usually the initial reason of their existence, and recognition.
We analysed a few interaction and diversification modalities of the Data GrandLyon platform. The Web 2. 0 capabilities in combination with traditional participatory tools offer numerous instruments towards inclusion. At the same time, their straightforward application in an effort to achieve maximum openness without considering the existing ecosystem can lead to the lack of or even to negative results  (Huntgeburth & Veit, 2013). This paper shows that analysis of motivations of particular categories of actors can help understand which interaction modalities would bring the most desirable outcomes for public good in a given context. More qualitative and quantitative research is needed to understand the connection between specific individual motivations and the profiles of actors, as well as their behaviour strategies and contributions to different societal goals.
Societal benefits Social solidarity economy Economic growth Efficiency and effectiveness Transparency and accountability Participatory democracy Open data models from literature Interaction Accomplishment Self-fulfilment Pro-social motivations Motivations from literature 2013 Jetzek, Avital & Fun/Pastime Participation Bjorn-Andersen, mechanisms Relationship Innovation mechanisms Status and repu-tation Efficiency mechanisms Amateurism Transparency Altruism mechanisms Participation mechanisms Sieber & Own-goals Participatory open Networking Code exchange Recognition Data over Autonomy Civic issue Code exchange Ideology Participatory Johnson, 2015 data the wall tracker open data Money Kinship Self-esteem Learning Impact Danneels, Viaene Autopoietic Connectionistic Cognitivist Connectionistic Autopoietic Career & van den Bergh, Interaction Feeling of being a Intellectual 2017 'good citizen' challenge Open Reciprocity Linders, 2012 "Do It Yourself Government" (C2C) "Government as platform" "Citizen sourcing" (C2G) government (G2C) platform models from Nam, 2012 Social networking Contest Wiki Social voting literature Motivator Professional knowledge Innovative ideas Innovative ideas Collected Relationship Materials and Altruism and amateurism Efficacy (impact) wisdom career Platform Interaction Forum and offline Mainly through Explanation Clarification Editorial page, Forum and characteristics events, editorial page apps and services, of licences, contact of goals and benefits, tutorials, comments offline events, editorial comments on form citizen- page, external the platform sourcing app resources Diversification Visualised data Datasets Open Open Datasets form Visualised data from different form different government government different sources, from different reuse cases, data sources, re-use data data articles by reuse cases, submission cases, external including independent data submission links from citizens journalists, external as sensors links Individual Basic Career benefits Own goals Reciprocity Money Interaction Networking Interaction Kinship Kinship Relationship Accomplishment Recognition Status and 'Good citizen' Recognition reputation feeling Self-esteem Self-fulfilment Autonomy Intellectual Amateurism Fun/Pastime challenge Learning Pro-social Altruism Impact Ideology Septiembre -diciembre 2020.
The temporal evolution of the pumping rate of these tests is given by:     mean amp cos Q t Q Q t     ( 1 ) where Q is the pumping rate (m 3 /s), Qmean is the pumping constant mean signal (m 3 /s), Qamp is the pumping constant amplitude of oscillation (m 3 /s) and ω is the angular frequency (rad/s) also equal to 2 P  where P is the period (s). The harmonic pumping tests were led with mean Q = 8. 8 L/s and amp Q = 3. 7 L/s in P13, and with mean Q = 9. 7 L/s and amp Q = 4 L/s in P16. During these two pumping tests, the hydraulic level variations in 13 boreholes (including the two pumping boreholes) were continuously measured, in terms of pressure, with CTD Diver probes with an accuracy of +/-0. 05 %FS (%FullScale). Once the data processing has been performed for each measured well, a map of amplitude and phase offset responses can be produced (Figure  4 ).
Property maps The results of the different inversions are presented in term of maps of distributed transmissivity and storativity values in Figure  5 , in term of maps of diffusivity (calculated from the maps of transmissivity and storativity: T D S  ) values in Figure  6 , and in term of root mean square error (RMSE) between the measured and simulated amplitudes and phase-offsets in Table  1. Figure  7  also presents the maps of uncertainties on the inverted property values and the scatterplots obtained on the datasets after the inversions. Each separately inverted model allows for a good reproduction of the amplitude responses (0. 1 to 0. 3 mm RMSE) and the phase-offset responses (1° to 3° RMSE). The reproduction of the responses with amplitudes less than 1 mm appear to be less accurate (Figure  7 ).
In a recent application comparing the results obtained on the same site with oscillatory data and constant-rate data,  Cardiff et al. (2019)  observed that the characterization with oscillatory data provided lower conductivity values in the zone associated to low conductivities, thus accentuating the contrast between high and low conductivity distribution. This could be explained by the fact that low-period oscillations generate responses with spatial distributions highly dependent on the contrast existing in the property distribution around the pumping well. In this application, the oscillatory responses were extracted from a background tide signal. An eventual impact of the tide signal on the groundwater condition (groundwater level) during the pumping has been considered as negligible. This is mainly due to the fact that the background tide signal, throughout the pumping tests, generated a movement of the water table not exceeding 10 cm (< 2 % of the water column).
Performing a joint inversion with all data obtained with the two periods of oscillations results in lessuncertain property maps than the ones obtained with separate inversions, thus confirming the fact that both datasets carry different and complementary information. Oscillatory signals provided, for this application, several advantages. Firstly, spatial responses are exploitable only after several oscillations (6-7 in this case), thereby allowing for a reduction in the pumping time. Then, the ability to solve the model in a frequency domain with the oscillatory responses, rather than in a time domain, permits a considerable reduction in the computation time required for the inversion. Secondly, the data processing allows extraction of the responses even in an environment with a strong natural forcing, like in this case the tidal variation induced by the nearby Seine River.
Two separate inversions have been led with the responses associated to the two different periods of pumping signals (P = 5 and 10 minutes). This means that, for each separate inversion, both pumping test (P13 and P16) responses to one period of signal (5 or 10 min) are considered. Therefore, each separate inversion is led with a dataset of 26 couples of amplitude / phase-offset measured responses. Afterwards, a joint inversion, integrating the responses to the two periods of signals simultaneously, also for both pumping tests (P13 and P16), has been performed (with a dataset of 52 couples of amplitude / phase-offset measured responses).
, 2007]  and the ontology proposed by  Burroughes and Gao [Burroughes and Gao, 2016]. Other ontologies model sensory information, even it is not their main objective, such as: (i) RoboEarth ontology  [Riazuelo et al. , 2015] , (ii) the ontology of SEMAP, a framework for semantic maps representation in spatial databases, proposed by  Deeken et al. , in [Deeken et al. , 2018] ; (iii) the ontology proposed by  Wu et al. , in [Wu et al. , 2014] ; (iv) the ontology used in OMRKF (Ontology-based Multi-layered Robot Knowledge Framework)  [Suh et al. , 2007] ; (v) based on OMRKF, the knowledge framework OUR-K  [Lim et al. , 2011]  is presented to be used for service robots, (vi) OASys ontology, that treats sensors as a type of device; it is developed for Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV); and (vii) Robot Ontology, where the structural characteristics are captured when the robot is defined; one of this characteristics is related to sensors (e.
, in [Deeken et al. , 2018]  for semantic maps in spatial databases, whose mapping approach consists on obtaining absolute geometric data from the environment to model objects and their relative spatial relationships. There are proposals that do not generate a metric map as a result of their SLAM stage, in contrast they generate a graph where each node represents a possible place or position where the robot can be. The Knowledge Base ontology of ROSPlan framework  [Cashmore et al. , 2015] , uses the structural similarities between many robotics planning domains. For example, in the case study presented authors represent the areas, where an Autonomous Underwater Vehicle (AUV) can move, showing with points its possible locations (waypoints). In a similar way of  [Cashmore et al. , 2015] , KNOW-ROB  [Tenorth and Beetz, 2009]  models robot pose in a list of places where the robot could be, using the RobotPlace entity; and the ontology proposed by  Hotz et al.
d) Robot trajectory information: Considering that a trajectory is a sequence of positions in a given time, an ontology has to model time to properly model trajectories. Two ontologies comply with this temporal characteristic, the one proposed by Burroughes and Gao  [Burroughes and Gao, 2016]  and the proposal of Fortes-Rey  [Fortes, 2013]. The first one has a module called Proccess Ontology related to Temporal Ontology (see Figure  2. 1). Instead, Fortes-Rey proposes a relationship, called posAtTime, that allows to relate a robot to a position and timing. Then, it is possible to describe the trajectory of a robot.
a) Geographical information: In this category of information, RoboEarth ontology  [Riazuelo et al. , 2015]  is the most outstanding. This is reflected in its ability to model the location of objects with respect to the robot, the geometry of the scene, as well as the relationships and concepts between objects and maps. There are other ontologies that model geographic information in a general way. This is the case of: (i) Space Ontology  [Belouaer et al. , 2010] , which is a spatial knowledge representation complemented with a reasoning system, able to model and manage the space (e. g. , hierarchical organizations, spatial entities); (ii) the ontology proposed by Burroughes and Gao  [Burroughes and Gao, 2016]  has two modules related to geographic information: the Simple Map Ontology and the Topological Map Ontology; and (iii) the ontology proposed by Hotz et al.
b) Mobile objects: We can say that the proposal of Burroughes and Gao  [Burroughes and Gao, 2016]  allows to recognize mobile objects, if we analyze the relationships among the ontologies of Objects and Single Map, with the Temporal Ontology. Also the work of Fortes-Rey  [Fortes, 2013]  allows to differentiate objects that move from those that do not, since the ontology can represent an object placed in a position at a given time. Ontologies such as RoboEarth  [Riazuelo et al. , 2015]  and OMRKF  [Suh et al. , 2007]  recognize mobile objects from databases, according to their visual characteristics, instead of their temporal characteristics. For example, a bicycle is considered a mobile object because of its shape but not because of its movement. c) Discussion:   2. 3 shows, less than a half of the selected ontologies comply with modeling timely knowledge, mainly with concepts related to temporal information associated to positions and objects.
, 2015]  provides a sub-database of relevant object models that will be needed to fulfill the target task. Thus, its semantic reasoning enhances recognition by reducing the false positive rate and computation. Table  2. 4 summarizes the inclusion of the relevant ontology features, related to the workspace, for the analyzed ontologies. As for the dimensions that are handled, there is a predominance in 3D. This means that ontologies are looking to model more and more real data. In relation to specific domain information, we note that there is a preference to model indoor environments. These include academic environments such as offices and laboratories. There are also environments that describe the interior of a house, such as a living room or a kitchen. These works present applications of service robots which is an area that is being quite developed in mobile robots, which use ontologies to model the knowledge collected by SLAM.
Implementation In this phase we will implement two modules: Robot Position Uncertainty (RPU) and Landmark Position Uncertainty (LPU). Those were implemented using OWL, language that is being used as standard for the development of web ontologies. Specifically, we will use it with RDF/XML serialization. We will also use Protegé, which is a free, open-source ontology editor and framework for building intelligent systems. It also has a viewer that allows us to see the ontology developed in the form of a graph. To see how the concepts are related as we formalize them. How this is an ontology developed on the basis of Fortes-Rey's work, we got the source codes and went through an analysis process. Which consists of checking if resources, including their properties, are not incomplete and if the relationships between the resources are not damaged.
Levels of evaluation We are going to use the levels proposed by  Brank [J Brank, 2005]  grouping them in the two perspectives of Hlomani and Stacey  [Hlomani and Stacey, 2014]. In the Quality we will make the evaluation at linguistic level (string analyze) and at structural level (graph analyse). Related to the Correctness we will check the capacity of modeling the problem through the elicitation of the knowledge of an expert in the area of SLAM. Linguistic Level: Generally, linguistic analyze relies on their names, labels,comments and some other descriptions. But also the number of resources of the ontology, the properties of type object and type data of each resource, the number of classes and individuals. Structural Level: Using directed bipartite graphs to represent ontologies. We will analyze statements (triples) composed of subject, predicate and object.
<!--RobotsAutomation. owl#CartesianCoordinateSystem --> <owl:Class rdf:about="&RobotsAutomation;CartesianCoordinateSystem"> <rdfs:subClassOf rdf:resource="&RobotsAutomation;CoordinateSystem"/> <rdfs:subClassOf> <owl:onProperty rdf:resource="&RobotsAutomation;ofCS"/> <owl:allValuesFrom rdf:resource="&RobotsAutomation; CartesianPositionPoint"/> </rdfs:subClassOf> </owl:Class> We use the the WebVOWL  [Lohmann et al. , 2014]  Viewer to ensure the good development of the proposed new ontology (SLAM-UP), as well as to analyze the entities of the base ontology (fr2013). With the help of this viewer we noticed one problem in the base ontology, when we are defining the RPU module, that the main concepts for modeling the Robot Position Uncertainty generated two disconnected graphs: one of the Robot model and the second of the Position model, as can be seen in  Figures 4.
Domain of Knowledge Level For the third level it has been proposed a set of questions. That will be done through the SPARQL language  [Hayes, 2013]. SPARQL is an RDF query language capable of retrieving and manipulating data stored in RDF format, such as our web ontologies. This tool allows the consultation of triple patterns, conjunctions, disjunctions and optional patterns. Below are some of the queries made in SPARQL with the corresponding output: For answer question: 1a. The Ontology allows to represent the pose of a robot? In fr2013, a complex query had to be made, since it did not have the "Pose" class defined explicitly, like other positioning ontologies. In this ontology the pose of the robot it can represent with a vector of points with their respective cartesian Ppoints, each one associated with a representative part of the robot.
El microanalizador marca OXFORD, modelo Penta FETx3, que utiliza la técnica de microanálisis por EDX, con una sensibilidad mayor de 0,1 %, capaz de detectar elementos químicos desde el boro hasta el uranio. La rugosidad fue medida usando un microscopio de barrido por sonda SPM, marca Bruker, modelo Dimension Edge AFM (Microscopio de Fuerza Atómica), provisto de un cantiléver RTESP de antimonio dopado con silicio a 0. 01-0. 025 ohm-cm, radio de curvatura de la punta 8 nm, número de puntos de datos por línea, 512x512 pixeles, frecuencia de barrido 10000 Hz, constante elástica k = 40 N/m y una frecuencia de 300 kHz en el modo de barrido de contacto intermitente (Tapping mode). La recolección y procesamiento de los datos se realiza con el software Nanodrive V8. 02. Para calcular las rugosidades se usó el programa Nanoscope analysis.
Para la Concreción de la Fundamentación La investigación documental utilizó un enfoque de naturaleza inductiva. Se aplicó como técnica de recolección de datos: heurística en la selección de publicaciones útiles a la investigación. Para la interpretación documental, se empleó la hermenéutica, desarrollando el análisis cualitativo de los datos con apoyo del computador, mediante el software Atlas Ti; logrando un acercamiento progresivo a la estructuración de las causas de los ciber-riesgos en la red social mediante la aplicación de los lineamientos dados por la Teoría Fundamentada: ejecutar iterativamente la organización de los datos en códigos, conceptos y categorías, para finalmente concretar los términos descritos en la Tabla 1.
En resumidas cuentas, se trabajó en base a la presencia/ausencia de atributos para cada representación registrada, considerando las variables anteriormente expuestas, además de agregar una última categoría denominada como localidad (área), con la finalidad de identificar dónde se encontraba emplazado cada motivo. Fue así como se definieron cuatro áreas: LO1 cerro Benítez/lago Sofía, LO2 Torres del Paine, LO4 archipiélago Madre de Dios y LO5 canal Beagle/ cabo de Hornos. Al unir los resultados con la información bibliográfica se incluyeron dos nuevas áreas: LO3 Campo Volcánico de Pali Aike/río Gallegos y LO6 fiordo de Última Esperanza. El AFC fue trabajado a partir del programa estadístico Module Stat 2, donde cada motivo fue designado con una letra según el sitio al que pertenecía, seguido por un número correlativo.
AGRADECIMIENTOS Mi inmensa gratitud a Marianne Christensen, quien dirigió la memoria de máster que da origen a este artículo; además de Georges Sauvet, ya que sin su ayuda hubiese sido imposible realizar los análisis estadísticos. Eterna gratitud a Fabiana Martin por su apoyo al momento de registrar los sitios y a Nelson Aguilera por proporcionarme las fotografías (de su autoría) de Grotte du Pacifique y Cueva Augusta 1 en Madre de Dios. Finalmente, agradezco a la Agencia Nacional de Investigación y Desarrollo (ANID)/Subdirección de Capital Humano/Programa de Becas/DOCTORADO BECAS CHILE/2020-72210018 y al proyecto Fondecyt 1190984 a cargo de Flavia Morello, debido a que permitirán seguir desarrollando esta línea de trabajo.
La red se construyó con la ayuda del software EgoNet 5  que, entre otras virtudes, permitió visualizar las redes en el acto. Esto dio la oportunidad de poder reflexionar con cada entrevistado sobre su propia red, e indagar más sobre su entorno relacional a nivel cualitativo. Para construir la red personal se utilizó un generador de nombres múltiple que consistió en tres preguntas que abarcaron tanto a la familia, como a los amigos y otros contactos relevantes. El número de los contactos a recolectar fue fijo, establecido a 30, que es el mínimo requerido para que las características estructurales de las redes sean comparables entre sí y en el tiempo (véase McCarty y Killworth 2007). A nivel de relaciones, se tuvieron en cuenta los vínculos fuertes, débiles y negativos (un tipo de relaciones normalmente ignorado, a pesar de que algunos estudios demuestran su importancia (p.
GEPS S2007/ HUM-0517 y Su ampliación postdoctoral fue apoyada por "Excellence Laboratory" "Structuring of Social Worlds" (SMS ,  ANR-11-LABX-0066 )  como parte de un programa del Estado francés  ( ANR-11-IDEX-0002-02 ). 3 El estudio UCRAM 2009-2016 contiene una muestra aparte de migrantes retornados que fueron entrevistados en el año 2010 en Ucrania en distintas regiones. Sin embargo, estos datos no están discutidos ni analizados en el presente artículo, ya que no forman parte del seguimiento.
También se utilizaron como variables el incumplimiento o no de cada uno de los principios del código de buenas prácticas (tabla 2). Se estableció una variable añadida de «uso», que incluía el incumplimiento de al menos uno de los 6 principios del código de buenas prácticas. Los datos recogidos se registraron en una hoja de cálculo (Excel Microsoft), y posteriormente se importaron al software estadístico SPSS v. 24  En la última columna aparecen los valores de p resultantes de utilizar el test Chi cuadrado para contrastar la asociación entre estas características y el uso inadecuado de la figura del menor. * valor de p significativa con un IC 95%. tistics, 2016), con el fin de realizar un análisis descriptivo de las variables categóricas, y el análisis de interdependencia mediante el uso de tablas de contingencia, con la prueba Chi-cuadrado de Pearson.
AGRADECIMIENTOS La intervención y el estudio de materiales antiguos en la cueva de Abittaga, fue autorizada y subvencionada por el Servicio de Patrimonio Cultural de la Diputación Foral de Bizkaia (A013/2016, 72095530YA). AGO ha recibido apoyo de FEDER/Ministerio de Ciencia e Innovación-Agencia Estatal de Investigación (proyecto PGC2018-093925-B-C33), del Grupo de Investigación IT1418-19 de Eusko Jaurlaritza-Gobierno Vasco y tiene un contrato Ramón y Cajal  (RYC-2017-22558). AGS tiene un contrato predoctoral de la UPV/EHU para realizar la tesis en cotutela entre dicha universidad y la Universidad de Burdeos. Iñaki Intxaurbe (UPV/EHU) nos ha proporcionado las coordenadas de los yacimientos reflejadas en el mapa de la Figura 1. Queremos agra-.
Agradecimientos A la Comunidad Indígena Quechua de Quipisca, la Comunidad Indígena Quechua de Iquiuca, la Comunidad Indígena Quechua de Mamiña, la Asociación Indígena Aymara Kespi Kala y la Asociación Indígena Aymara Cuenca de Quipisca por la confianza y la generosidad concedida al equipo de investigación. A Bernardita Brancoli y sus dibujantes; a Alex Paredes y su equipo de topografía; a Carole Sinclaire, Diego Artigas, Consuelo Carracedo y Francisca Fernández, participantes del registro arqueológico. A Josefina Domeyko y Daniela Uribe, ayudantes de la investigación etnohistórica y a Gabriel Ruy-Pérez, ayudante de la investigación etnográfica. A Maricel Beltrán, Nicolás Riquelme y Raúl García por sus gestiones. A Diego Salazar por sus valiosos comentarios para mejorar el manuscrito. Al proyecto FONDAP 15110006.