Abdelkader Dellal
email: adellal@yahoo.fr

Johnny Henderson
email: johnnyhenderson@baylor.edu

Abdelghani Ouahab
email: aghouahab@yahoo.fr

Existence of solutions for Solitons type equations : Derrick's Problem with twice p-laplacian

Keywords: Soliton, variational calculus, splitting lemma. AMS (MOS) Subject Classifications:35C08, 35J35, 35J60

 will be the topic of this paper. The main purpose is to obtain soliton-like solutions with twice p-Laplacian.

Introduction

A soliton is a solution of a field equation whose energy travels as a localized packet and which preserves its form under perturbations. In this respect solitons have a particle-like behavior and they occur in many areas of mathematical physics, such as classical and quantum field theory, nonlinear optics, fluid mechanics, and plasma physics; see [START_REF] Dodd | Solitons and Nonlinear Wave Equations[END_REF]. Probably, the simplest equation which has soliton solutions is the sine-Gordon equation,

- ∂ 2 ψ ∂x 2 + ∂ 2 ψ ∂t 2 + sin ψ = 0, (1.1)
where ψ = ψ(x, t) is a scalar field, x, t are real numbers, representing, respectively, the space and the time variable. Derrick, in a celebrated paper [START_REF] Derrick | Comments on Nonlinear Wave Equations as Model Elementary Particles[END_REF], considers the more 1 realistic three-space-dimension model,

-∆ψ + ∂ 2 ψ ∂t 2 + V (ψ) = 0, (1.2)
∆ being the 3-dimensional Laplace operator and V is the gradient of a nonnegative C 1 real function V. In [START_REF] Derrick | Comments on Nonlinear Wave Equations as Model Elementary Particles[END_REF] it is proved by a simple rescaling argument that (1.2) does not possess any nontrivial finite-energy static solution. This fact leads the author to say, "We are thus faced with the disconcerting fact that no equation of type (1.2) has any time-independent solutions which could reasonably be interpreted as elementary particles." Derrick proposed some possible ways out of this difficulty. The first proposal was to consider models which are the Euler-Lagrange equations of the action functional relative to the functional S = Ldxdt.

The Lorentz invariant Lagrangian density proposed in [START_REF] Derrick | Comments on Nonlinear Wave Equations as Model Elementary Particles[END_REF] has the form

L(ψ) = -|∇ψ| 2 -|ψ t | 2 p 2 -V (ψ), p > 3. (1.3)
However, Derrick does not continue his analysis and he concludes that a Lagrangian density of type (1.3) leads to a very complicated differential equation. He has been unable to demonstrate either the existence or nonexistence of stable solutions. In this spirit, a considerable amount of work has been done by Benci and collaborators, and a model equation proposed in [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF]. The Lorentz invariant Lagrangian density proposed in [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF] has the form

ρ = |∇ψ| 2 -|ψ t | 2 ; α(ρ) = aρ + b|ρ| p 2 , p > n, L(ψ, ρ) = - 1 2 α(ρ) -V (ψ). (1.4)
In the case where p is constant, various mathematical results (existence, multiplicity results, asymptotic behavior, . . . ), have been obtained for different classes of solution models (see [START_REF] Badiale | Solitary Waves: Physical Aspects and Mathematical Results[END_REF][START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF][START_REF] Benci | Solitons and the electromagnetic field[END_REF][START_REF] Benci | Solitons like solutions of Lorentz invariant equation in dimension-3[END_REF][START_REF] Berger | On the existence and structure of stationary states for a Nonlinear Klein Gordon equation[END_REF][START_REF] Pisani | Remarks on the topological invariants of a class of solitary waves[END_REF][START_REF] Dodd | Solitons and Nonlinear Wave Equations[END_REF] and the references therein).

The aim of this paper is to carry out an existence analysis of the finite-energy static solutions in more than one space dimension for a class of Lagrangian densities L which include (1.4) with (r, p)-Laplacian

Statement of the Problem

The class of Lagrangian densities we consider generalizes the problem studied in [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF], Lagrangian density with variable exponent, in such a way as to include the Lorentz invariant Lagrangian density proposed in [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF]. First we introduce some notation. If n, m are positive integers, and will denote, respectively, the physical space-time (typically n = 3) and the internal parameters space. We are interested in the multi-dimensional case, so we assume that n ≥ 2. A point in R n+1 will be denoted by X = (x, t), where x ∈ R n and t ∈ R. The fields we are interested in are maps ψ :

R n+1 → R m , ψ = (ψ 1 , . . . , ψ m ) We set ρ = |∇ψ| 2 -|ψ t | 2 ,
∇ψ and ψ t denoting, respectively, the Jacobian with respect to x and the derivative with respect to t.

We shall consider Lagrangian densities of the form

L(ψ, ρ) = - 1 2 α(ρ) -V (ψ), (2.1)
where the function V is a real function defined in an open subset Ω ⊂ R m and α is a real function defined by

α(ρ) = aρ|ρ| r 2 -1 + b|ρ| p 2 , a ≥ 0, b > 0, 2 ≤ r ≤ n < p. (2.2)
The results of [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF] were concerned with the case: r ≡ 2. The action functional related to (2.1) is

S(ψ) = R n+1 L(ψ, ρ)dxdt = R n+1 - 1 2 α(ρ) -V (ψ)dxdt.
So the Euler-Lagrange equations are

∂ ∂t (α ψ t ) -∇ α ∇ψ + V (ψ) = 0, (2.3)
where ∇ α ∇ψ denotes the vector whose j -th component is given by div α ∇ψ j , and V denotes the gradient of V. The equation (2.3) is Lorentz invariant. Static solutions ψ(x, t) = u(x) of (2.3) solve the equation

-∇ α ∇u + V (u) = 0. (2.4)
Using (2.2) and (2.4) we obtain

-a r 2 ∆ r u -b p 2 ∆ p u + V (u) = 0, (2.5)
where ∆ r u = ∇ |∇u| r-2 ∇u ,

∆ p u = ∇ |∇u| p-2 ∇u .
Recall that the results of [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF] were concerned with the case r ≡ 2.

It is easy to verify that, if u = u(x) is a solution of the (2.3) and v = (ν, 0, . . . , 0) with |ν| < 1, the field

ψ ν (x, t) = u x 1 -νt √ 1 -ν 2 , x 2 , . . . , x n (2.6)
is solution of (2.3). Notice that the function undergoes a contraction by a factor,

γ = 1 √ 1 -ν 2 ,
in the direction of the motion; this is a consequence of the fact that (2.3) is Lorentz invariant. Clearly (2.5) are the Euler-Lagrange equations with respect to the energy functional

f a (u) = R n a 2 |∇u| r + b 2 |∇u| p + V (u) dx, (2.7)
where m = n + 1, so the time independent fields u are maps

u : R n → R m . For every ξ ∈ R n+1 , we write ξ = (ξ 0 , ξ) ∈ R × R n . V : Ω → R where Ω = R n+1 \ {η}, η = (1, 0)
, and V is positive and singular in η. More precisely we assume:

(V 1 ) V ∈ C 1 (Ω, R). (V 2 ) V (ξ) ≥ V (0) = 0.
(V 3 ) V is twice differentiable in 0 and the Hessian matrix V (0) is nondegenerate.

(V 4 ) There exist c, ρ > 0 such that if |ξ| < ρ then

V (η + ξ) ≥ c|ξ| -q where 1 q = 1 n - 1 p .
(V 5 ) For every ξ ∈ Ω\{0} we have V (ξ) > 0, and lim

|ξ|→∞ inf V (ξ) = v > 0. (V 6 ) There exist R > 0 , |ξ| < R =⇒ V (ξ) ≥ ω R |ξ| r , ω R > 0.
Example 2.1. A potential satisfying the assumptions

(V 1 ) -(V 6 ) is V (ξ) = ω 2 0 |ξ| r + |ξ| 4 |ξ -η| q .
3 Functional Setting Let p > n ≥ 2 and, with no loss of generality, we can consider the functional (2.7) with b = 1. It will be convenient to introduce the following notation:

f a (u) = R n a 2 |∇u| r + 1 2 |∇u| p + V (u) dx,
and we define the space E a to be the completion of .

C ∞ 0 (R n , R n+1 ) with respect to the norm u a = a ∇u L r + ∇u L p + u L r , a > 0, p > n ≥ r ≥ 2 i.e., E a = C ∞ 0 (R n , R n+1 ) • a u L r = n+1 j=1 u j r L r 1 r ∇u L r = n+1 j=1 ∇u j r L r
For every a > 0, the norms • a are equivalent, so we have to study only two cases: a = 0, a > 0.

Proposition 3.1. The Banach space E 0 is continuously embedded in L s (R n , R n+1 ), for every s ∈ [2, ∞]. Corollary 3.1. The Banach space E 0 is continuously embedded in W 1,p (R n , R n+1 ).
Corollary 3.2. For every a > 0, the space E a can be identified with the Banach space

W = W 1,p (R n , R n+1 ) ∩ W 1,r (R n , R n+1 ),
equipped with the usual norm

u W = u W 1,r + u W 1,p .
Recall that η is a singular point of the potential V, so it is reasonable to consider in space E a , the open subset

Λ a = {u ∈ E a : u(x) = η, for all x ∈ R n } , which is open in E a .
The boundary of Λ a is given by

∂Λ a = {u ∈ E a : there exist x ∈ R n such that u(x) = η} .
We can show that Λ a has a rich topological structure, more precisely it consists of infinitely many connected components. These components are identified by the topological charge we are going to introduce.

Topological charge and connected components of Λ a

For the sake of simplicity, we consider the function space

C = u : R n → R n+1 \{η}
K u = {x ∈ R n : u 0 (x) > 1}.
Then we define the topological charge of u ch(u

) :=    deg(ũ, K u , 0) if K u = ∅, 0 if K u = ∅. Such that deg(ũ, K u , 0) = x∈ũ -1 (0) sgnJ ũ(x),
(Brouwer degree) For more information about this subject, see [START_REF] Okavian | Introduction a la Théorie des Points Critiques[END_REF];

where J ũ denotes the determinante of the Jacobian matrix.

We notice that this definition of charge is the same as in [START_REF] Benci | Solitons in several space dimensions: Derrick's problem and infinitely many solutions[END_REF]. We recall that the topological charge is continuous with respect to the uniform convergence. Now, for every q ∈ Z we set

Λ q = {u ∈ Λ a : ch(u) = q}.
Since the topological charge is continuous with respect to the uniform convergence and the continuity of the embeddings E a in L ∞ (see proposition 3.1 )assure that the topological charge is continuous on Λ a , it follows that Λ q is open in E a , since we have also

• Λ a = q∈Z Λ q , • Λ q ∩ Λ p = ∅, p = q.
We conclude that every Λ q is a connected component of Λ a . We assume that the space dimension is odd then we conclude that for every q ∈ Z the component Λ q is isomorphic to the component Λ -q .

So for every u ∈ Λ a we can define the charge ch(u) ∈ Z. Now, we consider the set of a minimizer of f a in the open set

Λ * q = {u ∈ Λ a : ch(u) = 0}.
5 Properties of the energy functional Lemma 5.1. The functional f a takes real values and it is continuous on Λ a .

Lemma 5.2. The map f : E a → E a defined by

< f a (u), v > = < -a r 2 ∆ r u -b p 2 ∆ p u + V (u), v > = R n a r 2 |∇u| r-2 (∇u|∇v) + b p 2 |∇u| p-2 (∇u|∇v) + V (u).v dx is continuous . Lemma 5.3. The functional f a is coercive in Λ a ; that is, for every sequence u k ⊂ Λ a such that u k a → ∞, we have f a (u k ) → ∞.
Lemma 5.4. Let (u k ) ⊂ Λ a be a weakly converging sequence. If the weak limit belongs to ∂Λ a , then f a (u k ) → ∞ as k → ∞. Lemma 5.5. The functional f a is weakly lower semicontinuous in Γ a .

Proposition 5.1. There exists ∆ a > 0 such that, for every u ∈ Λ a satisfied u L ∞ ≥ 1 we have f a (u) ≥ ∆ a .

6 Existence result Theorem 6.1. The minimum points u ∈ Λ a for the functional f a are weak solutions of the system (2.5).

Proposition 6.1. (Splitting proposition) Let (u k ) ∈ Λ * a be a sequence and M be a positive real number such that f a (u k ) ≤ M.

Then there exists l ∈ N such that

1 ≤ l ≤ M ∆ a
where ∆ a was introduced in Proposition 5.1 and there exist ū1 , . . . , ūl ∈ Λ a , (x 1 k ), . . . , (x l k ) ⊂ R n such that, up to a subsequence,

u k (• + x i k ) → ūi , |x i k -x j k | → ∞, i = j, l i=1 f a (ū i ) ≤ lim inf k→∞ f a (u k ), and
ch(u k ) = l i=1 ch(ū i ).
The minimum is attained on the set Λ a , and it is easy to see that u ≡ 0 is a trivial solution of the problem. But, of course, we are interested in nontrivial solutions, We consider the following problem

I * = inf u∈Λ * a f a (u), Λ * a = {u ∈ E a : ch(u) = 0}.
The functional is bounded below and the set E a is not empty. We consider fields u having the form u(x) = ( 2 1 + |x| m , 1 1 + |x| m x).

(6.1) Lemma 6.1. There exists a suitable m ≥ 1, such that, the field u defined in (6.1) belongs to Λ * a . And moreover the set Λ * a is open in the space E a ;indeed,

• Λ * a = q∈N * Λ q a ,
• Λ q a ∩ Λ p a = ∅, p = q.

where Γ q is a connected component Theorem 6.2. Let a, b > 0, p > n ≥ r ≥ 2 . Then, if V satisfies (V 1 )-(V 6 ), then there exists a weak solution of (2.5) (i.e., a static solution of (2.3)), which is a minimizer of the energy functional (2.7) in the class of maps whose topological charge is different from 0.

Definition 4 . 1 .

 41 is continuous and lim |x|→∞ u(x) = 0 where η = (1, 0). Every function u ∈ C we write in the form u(x) = (u 0 (x), ũ(x)) ∈ R n+1 where u 0 : R n → R and ũ : R n → R n . For every function u ∈ C we define the support of u

Corollary 5 . 1 .

 51 For every b > 0, there exist d = d(b) such that, for every u ∈ Λ a we have f a (u) ≤ b ⇒ min x∈R n |u(x) -η| ≥ d.


Philippe Caillou

Jonas Renault

Senior Member, Jean-Daniel Fekete

Anne-Catherine Letournel

Michèle Sebag

Cartolabe: A Web-Based Scalable Visualization of Large Document Collections

We describe CARTOLABE, a web-based multi-scale system for visualizing and exploring large textual corpora based on topics, introducing a novel mechanism for the progressive visualization of filtering queries. Initially designed to represent and navigate through scientific publications in different disciplines, CARTOLABE has evolved to become a generic framework and accommodate various corpora, ranging from Wikipedia (4.5M entries) to the French National Debate (4.3M entries). CARTOLABE is made of two modules: the first relies on Natural Language Processing methods, converting a corpus and its entities (documents, authors, concepts) into high-dimensional vectors, computing their projection on the 2D plane, and extracting meaningful labels for regions of the plane. The second module is a web-based visualization, displaying tiles computed from the multidimensional projection of the corpus using the UMAP projection method. This visualization module aims at enabling users with no expertise in visualization and data analysis to get an overview of their corpus, and to interact with it: exploring, querying, filtering, panning and zooming on regions of semantic interest. Three use cases are discussed to illustrate CARTOLABE's versatility and ability to bring large scale textual corpus visualization and exploration to a wide audience.

INTRODUCTION

The visualization of large collections of documents, or corpora, faces both computational challenges and sense-making issues. These challenges and issues are at the crossroad of Visualization (VIS) and Machine Learning (ML). On the VIS side, the objective is to provide a suitable overview and enable the user to get a quick understanding of the data through an effective 2D representation, as well as to provide means to interact with this representation to explore it in a fluid and controlled manner. On the ML side, the objective is to achieve compressed representations of large corpora -typically using dimensionality reduction techniques -in a way that preserves meaningful arrangements of the material and is computationally efficient. This article presents a software framework called CARTOLABE (cartolabe.fr) comprehensively addressing the above algorithmic challenges related to visualization, machine learning, and sense-making. This system is intended for several application domains, e.g., exploring the state of art in a scientific field, getting an overview of the expertise of an organization or a country through documents, and making sense of a large set of documents produced by citizens over a national debate. CARTOLABE addresses several types of needs for mainly three categories of users: i) Organizations interested in sharing large collections of documents, making them readily accessible and searchable online; ii) Experts interested in making sense of their corpus, and exploiting it for diverse information retrieval tasks; iii) Data scientists and NLP experts, interested in the fast assessment of their data summarization and querying pipelines.

From a data compression perspective, CAR-TOLABE extensively relies on ML methods specifically dedicated to natural language processing (NLP) [START_REF] Deerwester | Indexing by latent semantic analysis[END_REF], [START_REF] Blei | Latent Dirichlet Allocation[END_REF] and on dimensionality reduction [START_REF] Nonato | Multidimensional projection for visual analytics: Linking techniques with distortions, tasks, and layout enrichment[END_REF] methods. From an interactive visualization perspective, CARTOLABE relies on the state of the art in web-based interactive visualizations, supporting both the general display of a data landscape and the dynamic exploration of the contextual information through querying, progressive filtering, panning and zooming.

The combination of both VIS and ML expertise enables users to visualize collections of millions of documents and to interactively explore the data through progressive computation and visualization [START_REF] Fekete | Progressive Data Analysis and Visualization (Dagstuhl Seminar 18411)[END_REF]. Furthermore, these functionalities are offered on the web, freeing the end-users from deploying or maintaining any infrastructure, storage, or computational resources.

CARTOLABE was initially designed to handle a corpus of scientific publications from the HAL repository (hal.archives-ouvertes.fr), containing about 700k documents and 2M authors. Its specificity is to rely on the textual information, as opposed to the other main systems relying on the authorship and citation graphs. This specificity was instrumental in extending CARTOLABE to other types of data collections, ranging from Wikipedia (4.5M documents) to Le Grand Débat (4M documents), recording the citizens' contributions to the national debate organized by the French government in May 2019.

Interactive systems offering map visualizations of large corpora, e.g., PAPERSCAPE (paperscape.org), most generally use graph layout techniques to compute the document positions, emphasizing the social ties between articles through co-authors or citations. In contrast, CARTOLABE focuses on the document contents: topics or linguistic properties. A topic map provides an intrinsic view of the scientific domains that is complementary to social ties-based maps and, for quite a few tasks, might be less biased. It can be used, for example, to find representative authors around a topic (e.g., to select reviewers), to find representative topics around authors (e.g., to understand the main thematic topics covered by an author), or to find representative articles around a topic (e.g., for literature reviews). Its filtering functionalities also allow CARTOLABE to support comparisons across organizations or years. We do not pretend CARTOLABE addresses all the issues related to document exploration and distant reading. The IN-SPIRE system [START_REF] Wise | Visualizing the non-visual: Spatial analysis and interaction with information for text documents[END_REF] has clearly made the point that it was important to provide multiple visualizations and interfaces on document collections to fully grasp their multiple facets; CARTOLABE is one component in that landscape, with scalability to tens of millions of documents and higher flexibility in NLP methods for its preparation pipeline.

CARTOLABE has become a generic system or a software framework, able to process and visualize a large variety of corpora. It is made of modular building blocks, which can be replaced or customized depending on the different types of entities to visualize and explore.

A particular usage of CARTOLABE is to support the visual assessment of new NLP methods, providing a fast and versatile interactive environment to visually explore the extracted concepts and their organization. The system, taking in charge the visualization and interaction parts, allows NLP experts to focus on the data processing methods and to assess the impact of new methods or hyper-parameter settings.

The main three contributions of CARTOLABE are: i) to support web-based real-time visualization and filtering of large document collections, up to tens of millions of documents; ii) to provide contextual information during the interactive navigation, allowing for scalable targeted search and filtering; and iii) to provide a platform to test new NLP methods for computing document similarities and search. These contributions rely on the combination of VIS and ML techniques, constructing an annotated landscape and generating tiled density maps to support navigation, search, filtering, and exploration at scale. The remainder of the paper will describe and exemplify CARTOLABE on the HAL usecase. After briefly discussing the state of the art, we give an overview of the CARTOLABE architecture and functionalities. Then, we describe the CARTOLABE-DATA and the CARTOLABE-VIS pipelines. Applications (Wikipedia and Le Grand Débat) are discussed further in section "Use Cases" and a preliminary evaluation in the section "Evaluation".

Related works

CARTOLABE's inspiration can be traced back to the GALAXIES visualization [START_REF] Wise | Visualizing the non-visual: Spatial analysis and interaction with information for text documents[END_REF], still used in the IN-SPIRE system from Pacific Northwest National Laboratory. GALAXIES builds a scatterplot view based on NLP and projection methods, displaying a few thousand documents according to their similarity. Although the concept remains similar, CARTOLABE relies on modern NLP and projection methods that have progressed greatly in the last decades. As noted in the original article, multiple visualizations are needed to reveal different facets of a corpus, and CARTOLABE replace, extends, and enhances the Galaxies module in multiple ways: it is more scalable, uses a modern projection method, and can be tailored to use any NLP method available from Python.

According to the survey and taxonomy of text visualization tools by Kucher and Kerren [START_REF] Kucher | Text visualization techniques: Taxonomy, visual survey, and community insights[END_REF] CARTOLABE supports the analytic tasks "Text Summarization / Topic Analysis / Entity Extraction", the visualization tasks "Overview", "Navigation / Exploration", and "Cluster / Classification / Categorization", in the domains of "Scientific Articles / Papers", "Reviews / (Medical) Reports", "Editorial Media", and others not listed. The data it represents are corpora represented as "Networks", implicitly through k-nearest neighbors computation. CARTOLABE is a "2D" visualization, representing items as "Clouds / Galaxies" with a "Metric-dependent" alignment. Compared to similar tools listed in the "Text Visualization Browser" (textvis.lnu.se), it can visualize large datasets and is not meant for one specific corpus but is meant to be tailored to different kinds of textual corpora. CARTOLABE is both an application and a framework to create corpus visualizations using the Galaxy metaphor.

Several recent visualizations for document corpora use a network layout approach: the document similarities rely on co-authorship or cocitation relationships and a graph layout algorithm computes the document positions based on their connections. PAPERSCAPE (paperscape.org) offers a map representing about 1.6M articles from the arXiv repository, enabling its interactive exploration using a scrollable and zoomable tiled structure. The Maps of Computer Science (MOCS) [START_REF] Fried | Maps of computer science[END_REF] propose a representation of terms from research papers in the DBLP repository, extracting and visually displaying the topics similarity. Various heatmaps can be overlaid to visualize the profile of specific researchers or institutions; however the MOCS system is static and limited in interactive functionalities such as filtering and searching. Another project, VOSVIEWER [8] aims to visualize bibliometric networks, representing both articles, authors and labs, and using NLP techniques to construct term similarity maps based on a relationship network. Its scalability, as reported in the original article, seems to be limited to some thousands of items (as opposed to tens of millions for CARTOLABE).

Another trend is that of multidimensional projections (MDP), mapping high-dimensional points (up to thousands or even millions of dimensions) into low-dimensional ones (typically 2D or 3D; only 2D is considered in this article). The last decade has seen many improvements in the quality, applicability, and scalability of MDP techniques, as detailed in recent MDP surveys [START_REF] Nonato | Multidimensional projection for visual analytics: Linking techniques with distortions, tasks, and layout enrichment[END_REF], [START_REF] Espadoto | Towards a Quantitative Survey of Dimension Reduction Techniques[END_REF]. A recent MDP approach, UMAP [START_REF] Mcinnes | UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction[END_REF], delivers projections with similar quality as those of rigorous mathematical grounding, revealing meaningful global structures, offering the possibility of quickly projecting new points on a learned manifold and having good clustering properties. A main strength of UMAP is its reasonable computational complexity.

Contrasting with PAPERSCAPE and VOSVIEWER, CARTOLABE relies on the document contents to build their similarity, as opposed to co-authoring and co-citation graphs. This choice was instrumental to extend CARTOLABE to various document collections besides scientific articles. Contrasting with GALAXIES and MOCS, CARTOLABE facilitates the user's exploration of data through an interactive map, with panning, zooming, and searching functionalities. Finally, CARTOLABE uses the UMAP projection, projecting millions of points based on their similarity into a 2D map in a few hours on a standard desktop.

CARTOLABE shares many of the goals of the UTOPIAN system [START_REF] Choo | UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization[END_REF], that is also meant to explore text corpora such as publications, using MDP techniques for visualization and NLP technique for topic analysis. Contrary to CAR-TOLABE, UTOPIAN can refine and change the NLP parameters interactively to tune the analysis and visualization as part of its exploration process. Providing interactive control over the NLP analysis is a very useful tool for application designers but not for CARTOLABE target users. CARTOLABE performs the NLP analyses offline and does not expose its pipeline to the final users. Whereas UTOPIAN relies on Nonnegative Matrix Factorization for topic modeling, CARTO-LABE allows choosing among a large variety of modelings, including LSA, LDA, doc2vec, and any other implemented in Python, depending on the characteristics of the corpus. Additionally, UTOPIAN is not designed to scale to millions of documents and is not web-based.

CARTOLABE also shares many of the goals of the "BioVis Explorer" [START_REF] Kerren | BioVis Explorer: A visual guide for biological data visualization techniques[END_REF] that presents all publications in biological visualization using a MDP technique and allows filtering based on different features of its corpus. Compared to CAR-TOLABE, each article is presented as a thumbnail image in a 2D map, allowing an easy selection. However, while the BioVis Explorer visualizes about 150 articles, CARTOLABE is meant to scale to tens of millions and therefore should uses a heatmap instead of showing the individual points as thumbnail images. In addition, CARTOLABE shows both articles and authors over the same map by considering them both as bag of topics. It actually also considers higher-level entities such as teams, labs, and organizations as bag of topics too; CARTOLABE displays them on the same map accordingly.

CARTOLABE also shares the goal of NANOCUBES [START_REF] Lins | Nanocubes for Real-Time Exploration of Spatiotemporal Datasets[END_REF] to provide interactive visualization, searching, filtering, and aggregation capabilities over the web. Contrary to NANOCUBES, CARTOLABE uses progressive mechanisms [START_REF] Fekete | Progressive Data Analysis and Visualization (Dagstuhl Seminar 18411)[END_REF] to support these searching and filtering functionalities, simplifying its architecture while sustaining interactive latencies with large data over the web. CARTOLABE CARTOLABE (Figure 1) is a web-based visualization and exploration system originally targeted at an audience of scientists of any discipline, to visualize their publications arranged on the 2D plane according to topic contents. The only requirement on the target users is a general un-derstanding of the considered corpus; no expertise in visualization or data analysis is assumed.

Architecture overview CARTOLABE comprises two modules that can be used independently: a data processing module and a visualization module respectively referred to as CARTOLABE-DATA and CARTOLABE-VIS. Both modules are publicly available (gitlab.inria.fr/caillou/cartolabe-data and gitlab.inria.fr/caillou/cartolabe-visu) and can be customized for various document collections.

CARTOLABE-DATA uses unsupervised text analysis to build a 2D representation of the document collection. This collection, typically retrieved by harvesting a site through a web API and transformed into a csv file for ingestion in CARTOLABE-DATA, is first processed to yield a compressed representation including all information required for the visualization (entity labels, 2D coordinates, and nearest neighbors). CARTOLABE-VIS imports this file and acts as a visualization server to display the map from web browsers, supporting its flexible exploration by the user.

We first describe the functionalities of the system before detailing its architecture and modules.

Functionalities CARTOLABE provides a general overview of the document collection (Figure 1). In the HAL application, the main entities are authors (visualized in red) and articles (blue). Both author and article maps are represented as heatmaps, with denser areas being brighter. These maps are blended by default but can be shown separately if the user is only interested in one of the entities, and labels are displayed on top of these density maps to give contextual information and help users identify the specifics of a region:

• Yellow labels characterize thematic regions.

For instance, the cluster on the very right of the map includes articles and authors related to "nuclear & TEV". • White labels indicate the most important entities in the map, depending on the zoom level. Their color background characterize the type of the entity (articles in blue, authors in red, laboratories in green and Inria "Project Teams" in brown). This map conveys some organization of the data, displaying well-separated clusters and summarizing their themes (reminding that the textual analysis is unsupervised). Users can pan and zoom the map to get an overview of the data organization; the labels are refreshed accordingly to display the important entities according to the scale and viewport. Users can also select an item on the map and read the associated details on the search box on the top left of the screen, or search for an item based on its name and see where it is located on the map.

Search and Neighborhoods

A main functionality of CARTOLABE is to retrieve the entities (articles or authors) close to a given entity. This information retrieval ability supports different usages, such as finding experts to review a paper or a technical proposal, or finding papers relevant to a topic to complete a bibliographic study. For instance, let us query an author (here Jean-Daniel Fekete, visible in the bottom of the screen; Figure 2). The most semantically related articles or authors are highlighted in the map and displayed in the search box.

Note that these semantic nearest neighbors might be far from the location of the query, due to artifacts of the dimensionality reduction [START_REF] Nonato | Multidimensional projection for visual analytics: Linking techniques with distortions, tasks, and layout enrichment[END_REF]: entities naturally live in a much higher dimensional space than the 2D space. We shall come back to this issue later (Section "Landmarks").

Filters

While density maps efficiently aggregate high amounts of information, they make it hard to see details beyond the white and yellow landmarks. To see the actual points in a region and get the details, users can specify a filter and only retain entities that match the filter (type of entity or property). For instance, using the filter "CERN", Figure 3 shows only articles and authors linked to the CERN Physics Laboratory, greying-out other entities. As intended, this filter makes it clear that the thematic areas most relevant to CERN are astrophysics and particle physics; other areas contain few, if any, publications or authors associated with CERN.

The overall CARTOLABE pipeline is detailed in the next two sections, distinguishing CARTOLABE-DATA and CARTOLABE-VIS parts.

CARTOLABE-DATA Pipeline

The CARTOLABE-DATA pipeline is illustrated on Figure 4. The first step is to collect the data, i.e., the document corpus. In the HAL application, the repository is queried through its open API, serving metadata on circa 800k scientific publications and 600k full texts in PDF format, including most (ideally all) articles funded by the French public research.

Note that the corpus involves different types of entities, e.g., articles, authors, laboratories, and institutes. The core of CARTOLABE-DATA consists in homogeneously and efficiently transforming this textual corpus and all entities therein into a collection of points usable by the visualization engine CARTOLABE-VIS.

After pre-processing, the entities are mapped onto a high-dimensional space. Landscapes and clusters are formed and named to facilitate the further navigation of the map. CARTOLABE-DATA eventually outputs a file storing the 2D coordinates of all the entities and their relationships that will be exploited by CARTOLABE-VIS.

Pre-processing

Each article is described by its identifier, title, abstract, keywords, publication date, research domain, authors, and author institutions, each collected automatically from the HAL metadata.

Entities include: words (more specifically ngrams, terms made of sequences of at most N = 5 words); articles (viewed as bags of words); authors (viewed as bags of articles); and laboratories or institutes (viewed as bags of articles). Only the titles, abstracts and keywords of the articles are used at the moment; we can use the full text or any section that would be the most informative, but due to the lack of quality measures to determine which sections of the text are the most informative ones, we use the simplest parts: the title, the keywords and the abstract. As of Dec. 2019, the HAL collection includes 800k articles, 200k authors, 10k laboratories, and 100k N-grams.

Articles undergo standard NLP preprocessing, including stop words removal and cleanup, only retaining terms with a minimum number m = 25 of occurrences. This step also determines the size (V = 64, 000) of the considered vocabulary. Thereafter, a word matrix and an author matrix are computed.

The word matrix M T,V is a T × V matrix, with T the number of articles and V the vocabulary size. M T,V (i, j) is the term-frequencyinverse-document-frequency (tf-idf) of term j in document i. Likewise, the author (and laboratory) matrix M T,L is a T × L matrix, with L the number of authors (resp. laboratories), where M T,V (i, k) = 1 iff the k th author (resp. laboratory) co-authored the i th article. Only authors and laboratories with a minimum number of papers (set to 3 in the following) are considered.

Continuous Embedding

Besides their above primary representation, entities are attached a latent representation: a continuous embedding is used to map each entity onto a vector in R d , with d typically in the hundreds. This continuous embedding firstly re-duces the dimensionality of the problem by two orders of magnitude, enhancing the computational tractability of our approach. Secondly and most importantly, it supports the definition of a sensible similarity among entities, avoiding the pathologies of Euclidean distance in high dimensional spaces, the so-called curse of dimensionality.

Preliminary experiments were conducted considering Latent Semantic Analysis (LSA) [START_REF] Deerwester | Indexing by latent semantic analysis[END_REF] and Latent Dirichlet Allocation (LDA) [START_REF] Blei | Latent Dirichlet Allocation[END_REF] with d ranging from 80 to 500. In the following, we use LSA with d = 300 that we found effective for HAL after several trials. Each article is therefore represented as a vector of 300 topics (the latent space) computed by LSA; authors are represented in the same space, as well as laboratories, teams, and institutions.

Topology

To each entity are associated its neighbors of each type, where the distance among two entities is their Euclidean distance in the latent space R d . This topology supports a main CARTOLABE functionality, namely visual information retrieval. As explained, users might want to find articles similar to an article, or relevant to a topic. More generally, the topology of the latent space is good iff the user can make sense of the map, finding that similar items are (most of the time) close to each other.

For the sake of real-time querying, the k nearest neighbors of each article are pre-computed (k = 10); a fast approximate k-nn algorithm is used, with quasi-linear complexity in the number of articles.

2D Projection

CARTOLABE uses the UMAP [START_REF] Mcinnes | UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction[END_REF] multidimensional projection technique for its good scalability and stability to project high-dimensional data in 2D, focusing on preserving close neighborhood relationships. Most interestingly, UMAP enables to approximate the 2D projection in the case of very large datasets (Section "Use Cases").

Landmarks

Navigating on the map is facilitated by defining and naming topics. The construction of meaningful cluster topics proceeds by using a k-means clustering on the articles and setting the distance of any two articles to their Euclidean distance in R 2 to avoid the issue of so-called stressed entities. This issue reflects the fact that entities related to different themes (e.g., an author working on several topics) that are projected in different regions of the 2D map, will be located in between these regions, and thus far from each of them, hindering its interpretation.

Topics are defined at 4 levels of granularity: 8 top-level, 24 medium-level clusters, 72 lowlevel clusters and 216 very low-level clusters, from the most general to the finest-grained topics. We selected these values experimentally, too-few would leave large areas unlabeled and too many would overcrowd the display. Each cluster is labeled after the most frequent word or term in the cluster (compared to the other clusters). If there exists no sufficiently frequent word in the cluster's articles, a second term (the most frequent one in the articles that do not contain the first term) is retained and both terms form the cluster name. A further requirement enforced is that two adjacent clusters should have different names.

Cluster labels are located at the cluster center and displayed in yellow, according to the level of zoom of the viewport. Other landmarks, defined as the most important entities (e.g., prolific authors and highly cited articles according to a score of interest, see below), are displayed in white next to their entity's position. They appear dynamically according to the viewport, the display density, and their relative score.

Scoring

To each entity is attached a score, expectedly reflecting its interest for the user. The design of more sophisticated scores (e.g., the citation counts for articles) is typically domain-dependent. Note that the modular organization of our pipeline permits specific implementations of the scoring functionality depending on the available data and its semantics. In the HAL application, the scores attached to authors and laboratories (respectively words) are their number of articles (resp. the number of articles they appear in). The score of articles is set to the number of views in HAL. Only the 10 entities with highest score appearing in the viewport are displayed.

Export

The output of CARTOLABE-DATA is a tabular file that is used as input by the CARTOLABE-VIS server. This file contains, for each entity: i) its id, its label, its score, its 2D position, and its type (article, author, . . . ); ii) its 10 nearest neighbors; iii) the relevant metadata depending on the type of the entity (e.g., the HAL link for the articles).

CARTOLABE-VIS Pipeline

As described above, CARTOLABE-VIS is provided with the data structure generated by CARTOLABE-DATA. Most generally, this data structure is made of a list of entities or points, where each point is attached to its main features and its 10 nearest neighbors in each category. The simplicity of this data structure is at the core of the CARTOLABE genericity, allowing it to handle diverse types of documents and data collections as long as they can be represented as a list of positioned entities.

Visualization

The main goal of CARTOLABE is to make sense of large scale data, up to tens of millions of entities. A first functionality thus is to provide a high-level visualization, displaying an overview of the collection. To do so, CARTOLABE-VIS creates density map images, reflecting the density of the point distribution in the diverse regions of the 2D space. This functionality is achieved using standard Python libraries: NumPy to compute 2D histograms, SciPy to apply a smoothing Gaussian blur, and Pillow to convert them into images. Still, it is essential for users to interactively zoom, pan, and filter the data according to their exploration. Thus, a multi-scale visualization is produced by i) generating offline static images; ii) tiling them and serving them interactively. The tiled pyramid is created by building static images of each zoom level of the density maps and splitting them into 256 × 256 pixel grey-scale tiles. These tiles are sent by the web server application to the browser following the tiled image protocol of D3. We generate a different heatmap for each entity that we want to visualize (authors and articles for HAL). This allows the users to show either of them dynamically. The heatmaps, created as standard grey-scale PNG images, are combined by the browser using standard SVG filters to color and blend them.

The Context CARTOLABE-VIS enables users to look for a specific region or point of interest, through displaying contextual information and/or enabling direct search and filters (below). The contextual information, characterizing the region currently displayed on the screen, consists of labels superimposed on top of the tiled density maps. For the sake of readability, only the top-scored entities and most general clusters located on the viewport are made visible (see "Scoring" Section). We chose a yellow color for the cluster labels to limit their saliency since they remain displayed all the time and are only useful as area landmarks, we do not want them to attract the reader's attention as much as other landmarks. To be fully readable, the popular entities' labels appear in white with a black outline. This increases their contrast and they stand out independently of their background. Instead of outlining the labels with a colored border according to their type, we only draw a colored "wedge" in a corner of the label bounding box, pointing to the exact position of the label (see Figure 1). This encoding, similar to a glyph, saves the visualization from becoming overcrowded and is easily understood by users.

CARTOLABE-VIS relies on a standard database to efficiently select the most important entities based on their score and position to be labeled on the current viewport.

Contextual Filters

Besides panning and zooming, users can tailor the map to their current goals by using filters, e.g., showing only articles and authors associated with a targeted laboratory (the CERN in Figure 3) and greying out the others. In the HAL application, filters can specify the desired laboratory names (HAL references 10,000 of them) and the publication period (from 2008 to now). Filters can be combined, e.g., enabling to visualize the entities associated with the CERN or INRIA laboratories and published in 2018.

As pre-computing density maps for all possible filter masks is not feasible, contextual filtering proceeds by generating density maps upon users' query in a progressive way [START_REF] Fekete | Progressive Data Analysis and Visualization (Dagstuhl Seminar 18411)[END_REF]. Specifically, CARTOLABE-VIS uses the Roaring Bitmaps library [START_REF] Lemire | Roaring bitmaps: Implementation of an optimized software library[END_REF] to create and store compressed indices of the entity identifiers associated with each el-ementary filter value. CARTOLABE-VIS thus is provided with a bitmap pre-computed for each map tile, storing all entities located in the tile region, and a bitmap for each filter value (lab and year), storing all ids of all articles matching this filter value. All bitmaps are combined interactively in a few milliseconds to retrieve the identifiers of all articles matching the contextual filter, e.g., the CERN or INRIA articles published in 2018 and falling in the displayed tiles.

Eventually, the selected entities are superimposed on the current density map image. Our library is quite efficient at generating density images, this last operation can be done in reasonable time (< 500ms), creating a tiled portion of the density map matching the users' criteria that is displayed on top of the shaded overall map. This process is done progressively, using a thin red progress bar on top of the screen as visual feedback indicating that the operation is ongoing during the 500ms to 2s of its duration, taking into account the time to send images through the network.

Progressive computation and rendering is repeated each time the user zooms and pans the map, with controlled caching to improve performance. This progressive generation of a multiscale filtered density maps is a unique feature of CARTOLABE-VIS. It opens new perspectives for implementing scalable web-based visualizations with dynamic queries.

Use Cases

Several use cases of CARTOLABE are described to illustrate its flexibility (Table 1): basically all key components presented in the previous sections can be replaced with other Python libraries to accommodate other data structures or needs. Interestingly, new algorithms (achieving e.g., word embedding, 2D projection or clustering) can also be integrated into the CARTOLABE framework for comparative assessment with the state of the art: CARTOLABE is designed to be agnostic about the methods used to generate its data and flexible enough to accommodate most of them. CARTOLABE-DATA comes with multiple pipelines, including the use cases described below. It also includes examples using different topic modeling methods such as LSA and LDA (used for all the production pipelines). We also provide example pipelines using word embedding methods such as doc2vec and even an example using the MNIST hand-recognition dataset made of images instead of texts to showcase the flexibility of our framework.

Wikipedia

We used the Wikipedia dataset as a scalability study, confirming that CARTOLABE can manage millions of documents with no performance degradation. The main difference compared to the HAL application regards the UMAP projection: when building a map of all articles in the English Wikipedia, an approximated projection was trained from a uniform sample of 20% of the articles and used for all articles, to preserve the projection performance. Another difference is that a single density map, reflecting the articles and based on the top 200k words, was built instead of two for HAL (one for the articles and one for the authors). Lastly, the scoring functionality was modified to account for the article popularity in Wikipedia, first displaying the most popular articles in the viewport.

Le Grand Débat

The Grand Débat dataset includes the citizens' full-text contributions in response to the French government questions about societal and political issues. This Grand Débat initiative took place in France from January to March 2019 (granddebat.fr), gathering circa 4M full-text contributions. CARTOLABE was successfully used to explore this large and heterogeneous corpus upon an official request from a French regulation organization, to check if the eventual analysis and summary of these contributions were fair and unbiased in terms both of topic coverage and summary contents.

Like for Wikipedia, the real-time performance is enforced by approximating the UMAP projection, using a projection model learned from a subset of the data. The filtering options include each one of the 600k extracted terms, supporting the full-text querying of the dataset.

Evaluation

We conducted a usability study approved by our Institutional Review Board with 7 users from our laboratory (face to face before the COVID-19 outbreak) on the HAL dataset. This preliminary study was found insightful, and it will be continued to improve CARTOLABE. We had three goals: 1) Verifying the usability of CARTOLABE-VIS for our target users; 2) Verifying the quality of CARTOLABE-DATA regarding the distance measure and its projection; and 3) Collecting feedback on possible improvements regarding both CARTOLABE-DATA and CARTOLABE-VIS. Demographic The 7 users (2 female, 5 male, age range 30-60) were researchers (2 full professors, 4 assistant professors, 1 researcher). They were recruited by sending an email to the laboratory mailing list. None of them were familiar with visualization or projection methods, and they did not receive any compensation. Setup The study lasted about one hour. Each user started by reading a consent form explaining the goal of the study, with the ability to ask questions to the interviewer, and then signing the form. Each session was split in four parts: 1) Training; 2) Usability testing; 3) Assessing the metrics and its visualization; and 4) Collecting feedback.

Participants filled a questionnaire during and after the study to keep track of their answers and comments.

Training We introduced the main features of CARTOLABE-VIS and its UI, starting with the visible features without interaction, then the possible interactions on each of the visualized items and UI areas, explaining the function of each button, text area, and icons. Then, the search capability was explained with several examples. Usability Testing We asked each user to perform a standardized set of tasks to make sure they understood the training well enough and were able to use CARTOLABE by themselves. Assessing the metrics and its visualization We designed a five steps protocol to assess the quality of the distance metrics and its visualization. 1) We asked users to list the names of french authors well-known in their area of competence, not using any tool. 2) We then asked them to find the authors using CARTOLABE and to comment on the cluster names while navigating around; 3) We asked if, in light of the results, CARTOLABE appeared trustworthy. Then, we asked to repeat the same task (gather names and check with the tool) for other domains or fields they were familiar with, and report on their findings. 4) We asked to assess the proximity of articles and authors, starting from a recent article well known by the user, select a list of authors related to it and check if they were close in the visualization. 5) We asked to select three PhD students and to assess the accuracy of their clusters and their neighborhoods. Collecting feedback Users were asked if they wished to continue exploring the map, and then to report at a higher level on what they liked, what they found useful and less useful, difficult, and about the utility of the tool.

Results

We gathered a total of 180 comments, 2/3 were about the UI and visualization, and 1/3 about the metrics. Usability Testing All the users were able to complete all the tasks we asked them to do after the training, validating the usability of CARTOLABE-VIS for the selected tasks. Assessing the metrics and its visualization Due to limited space, we only report on the results on steps 1-3. Users have listed a total of 28 names at step 1, representative of their domain. 25 have been found on the map at step 2 (90%), 3 were not found, and 2 were found at unexpected positions (missing neighbors artifact from the UMAP projection). During step 3, our users have collected 53 names around their areas of interest on the map (including their ground truth), none of which were considered as obvious mistakes (no false neighbors). Therefore, they all considered CARTOLABE trustworthy.

All the users who looked at the 10 closest ngrams to an article or an author were satisfied by the results, meaning that the topic modeling results were good for our small sample.

All the users have been able to perform the tasks on metrics and visualization as expected by our protocol and to answer all our questions without major problem, witnessing that CARTO-LABE is already usable in its current form for neighborhood exploration tasks, and that the NLP and projections were fair to the data. Collecting feedback The main UI issues raised were: 1) improve the icons and their affordance when they can be used to toggle some features, such as hiding/showing layers under the visualization, 2) add bookmarks to keep track of and retrieve interesting views, 3) improve the highlighting of selected features (selected labels and points not salient enough), and 4) improve the topic clusters labels (shown in yellow) and their stability during the navigation. We are working on addressing these usability issues but were pleased by these initial usability results. We even received an unexpected use case from a PhD student, who realized that the list of well-known authors close to his articles gave him hints on where to apply for a position.

Overall, this preliminary study has validated our design goals. We still need to continue our evaluation with more users, but our protocol seems valid and we will continue to use it to further improve CARTOLABE.

Scalability

CARTOLABE is scalable to circa ten million documents: it was specifically designed to handle large datasets. While the text processing pipeline might take time to complete, this is an offline process that does not hinder CARTOLABE interactive system performance. The use cases described in the previous section demonstrate that CARTO-LABE can display millions of points in a browser without any visible slowdown. The use of static images as density maps is not affected by the size of the data. Though CARTOLABE relies on an external database to index the points and query them to display labels in the viewport, the scalability of existing databases is well documented and can sustain the browsers' demand. The use of the Roaring Bitmap library to build indices for the filter function also offers high scalability and performs well even with millions of points and filter values.

As for the human side, we believe CARTO-LABE's visualization can scale to tens of millions of documents for overview tasks using its heatmap. The labeling and selection mechanisms rely on a good scoring for items that is sometimes difficult to obtain for large datasets. We have been able to get it for HAL with difficulties, Wikipedia provides its access statistics, but arXiv does not. Without these scores, there is no simple way to label the most important items in the visualization and the labels shown are random samples instead of real landmarks. When selecting an author, an article, or a word, we only allow displaying its ten closest neighbors. Some users complained about it and for larger datasets, we will have to increase this number, but this is currently a parameter set in CARTOLABE-DATA and in CARTOLABE-VIS and it can already be changed. More user studies will inform us of possible issues for larger datasets.

Conclusion and Perspectives

The CARTOLABE framework is a web-based system aimed at visualizing and exploring large document collections for users interested in these documents but not familiar with visualization and machine learning. This framework, initially designed to explore a scientific publication corpus, has evolved towards a generic system accommodating different document collections. Written in Python, it is freely available online.

The CARTOLABE design relies on a multiscale 2D representation (map) that allow to make sense of large-scale data through an overview, and panning and zooming navigation. In addition, multiple interactive features allow to search, filter, and explore the neighborhoods of selected items or regions.

Our next step will be to launch a call to gather new corpora to further test the genericity of CAR-TOLABE, to perform more exhaustive evaluations of the multiple stages of the system, and to apply it to new interesting corpora needing exploration by topics such as libraries, archives, and software repositories.

Figure 1 .

 1 Figure 1. The CARTOLABE system: A Web-based, zoomable, 2D visualization of the HAL scientific publication repository, involving 700k articles and 170k authors. This visualization is aimed at a large scientific audience with no particular knowledge in visualization. Topic headlines are displayed in yellow; important articles and authors are displayed in white.

Figure 2 .

 2 Figure 2. Zooming on a specific point of interest: its semantic nearest neighbors are displayed as dots with a cyan border.

Figure 3 .

 3 Figure 3. Dynamically filtering the density maps by content lets users explore specific contextual areas and visually check their scope. Here only articles and authors associated with the CERN are displayed while the rest of the map is grayed out.

Figure 4 .

 4 Figure 4. CARTOLABE-DATA data processing pipeline illustrated on the HAL use case.

Table 1 .

 1 Three CARTOLABE Use Cases: Datasets and Computational Time to process them.

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c 2020 IEEE Published by the IEEE Computer Society Cartolabe

March 2020

Cartolabe

Mich èle Sebag, is Senior Research Scientist at CNRS, France, head of the A&O team at the CS department of Universit é Paris-Saclay and CNRS. Contact her at Michele.Sebag@lri.fr.


Azanzi Jiomekong
email: fidel.jiomekong@facsciences-uy1.cm

Hippolyte Tapamo

Gaoussou Camara

Combining Scrum and Model Driven Architecture for the development of the EPICAM platform

Keywords: EPICAM, Tuberculosis, Epidemiological surveillance, Scrum, Model Driven Architecture

The problem of failed software developed for epidemiological surveillance is often the result of an unsystematic transfer of business requirements to the implementation. However, empirical research shows on the one hand that, in certain conditions, Model Driven Architectures (MDA) are more effective than code-centric approaches for the development and the maintenance of software. On the other hand, Agile Processes such as Scrum are more effective than Structured. Processes when requirements are subject to frequent change. In this paper, we show how Scrum and MDA were used to develop EPICAM, a platform for epidemiological surveillance of Tuberculosis in Cameroon.

I INTRODUCTION

Epidemiological surveillance systems enable the collection, analysis, and interpretation of data, closely integrated with the dissemination of these data to stakeholders for preventing and controlling disease and injury. To be usable, epidemiological surveillance systems use surveillance software to provide timely, accurate, comprehensive and update information to stakeholders [START_REF] Choi | The Past, Present, and Future of Public Health Surveillance[END_REF][START_REF] Richards | Advances in Public Health Surveillance and Information Dissemination at the Centers for Disease Control and Prevention[END_REF]. Depending on the data gathered on the field, epidemiologists may need to collect a new parameter in order to explain a phenomenon. For example, in the case of Covid-19, data can be collected in order to determine if people of a certain race are more at risk. This task may be done by using supplementary materials such as paper forms or spreadsheet software and lead to the problem of data integration [START_REF] Lenzerini | Data integration: A theoretical perspective[END_REF]. To collect new data, another solution consists of updating the software used for the surveillance. This solution is expensive and may lead to the problem of software regression [START_REF] Bin | On the search for industry-relevant regression testing research[END_REF] because bugs can be introduced during the source code update. These problems occur because of the problem of failed software -often caused by an unsystematic transfer of business requirements to the implementation [START_REF] Hajou | An Insight into the Difficulties of Software Development Projects in the Pharmaceutical Industry[END_REF][START_REF] Schlieter | Towards Model Driven Architecture in HealthCare Information System Development[END_REF].

The problem of unsystematic transfer of business requirements to the implementation can be avoided if the system is established using a well-defined framework/architecture such as Model Driven Architecture, permitting the rapid development/update of the surveillance software. Model Driven Techniques in general relies on models and model transformations for the development, maintenance and evolution of software. Through the architectural separation of concerns, the Model Driven Architecture (MDA) in particular assumes the evolutivity, portability, interoperability and reusability [START_REF] Martínez | Empirical study on the maintainability of Web applications: Model-driven Engineering vs Code-centric[END_REF]15]. Graphical modeling permits non-informatics experts to be able to build graphical models and automatically generate their software. Empirical research shows that the main motivations for companies to use Model Driven techniques are cost saving, rapid development / update / maintenance, improvement of productivity, software quality, and the maintaining of the architecture consistency from analysis to implementation [START_REF] Martínez | Empirical study on the maintainability of Web applications: Model-driven Engineering vs Code-centric[END_REF]. In the health domain, many authors have proven that Model Driven techniques is an effective approach for the development of health software [START_REF] Schlieter | Towards Model Driven Architecture in HealthCare Information System Development[END_REF][START_REF] Atanasovski | On defining a model driven architecture for an enterprise e-health system[END_REF][START_REF] Jiomekong | Model-Driven Architecture Based Software Development for Epidemiological Surveillance Systems[END_REF].

On the other hand, translating requirements to a solution using either code-centric or MDA approach requires the use of a software development process. Software development process defines a scheme to structure and manage the various aspects of software development. Software development processes are grouped into Structured Processes such as the waterfall or V-model and Agile Processes such as Scrum [START_REF] Pressman | Software Engineering : A Practitioner's Approach[END_REF]. With Structured Processes, specifications are fixed in advance and the software is developed and delivered thereafter. In the health domain, empirical research demonstrated that software developers experience difficulties when following Structured Processes [START_REF] Hajou | An Insight into the Difficulties of Software Development Projects in the Pharmaceutical Industry[END_REF][START_REF] Heeager | Meshing agile and plan-driven development in safetycritical software: a case study[END_REF]. In the particular case of a pandemic, it can be very difficult to capture all the requirements of its epidemiological surveillance system at such an early stage of a project. However, Agile software development processes such as Scrum [START_REF] Pressman | Software Engineering : A Practitioner's Approach[END_REF] experience great success in software development organizations. Many empirical studies report significant benefits being gained from utilizing Agile practices such as reducing costs, reducing time to market and increasing quality [START_REF] Heeager | Meshing agile and plan-driven development in safetycritical software: a case study[END_REF].

Concerning Cameroon, given the problem of unsystematic transfer of business requirements to the implementation, the EPICAM1 (Epidemiology in Cameroon) project was set up. This is a project of academic (University of Yaounde I in Cameroon2 ), clinical (fifty hospitals in Cameroon), epidemiological (Centre Pasteur du Cameroun3 -Epidemiology and Public Health department and NTCP), and industrial (MEDES 4 in France) partners. It aims to provide methodologies, methods, models and tools for improving the development of epidemiological surveillance of infectious diseases. Firstly, a pilot project consisting to set-up the epidemiological surveillance of Tuberculosis (TB) was put in place. In effect, given the burden of TB in Cameroon, the government has put in place the National Tuberculosis Control Program (NTCP). Thereafter, the NTCP has set-up epidemiological surveillance. Even if some tools like Microsoft Excel are used, this system is mainly manually managed. Given the limit of the manual management [START_REF] Mapatano | Quelques erreurs courantes d'analyse d'un syst'eme d'information sanitaire(RD Congo)[END_REF][START_REF] Jiomekong | Model-Driven Architecture Based Software Development for Epidemiological Surveillance Systems[END_REF], the NTCP expressed the need for an electronic system. Thus, the purpose of the pilot project was to describe the methodologies, methods and tools for the development of epidemiological surveillance of TB. This paper presents how we proceed to develop the EPI-CAM platform for epidemiological surveillance of TB in Cameroon. In the remainder of this paper, we present the research design in Section II, research results in Section III and conclusion in Section IV.

II RESEARCH DESIGN

The research design was inspired by empirical research methods in software engineering [START_REF] Easterbrook | Selecting Empirical Methods for Software Engineering Research[END_REF][START_REF] Martínez | Empirical study on the maintainability of Web applications: Model-driven Engineering vs Code-centric[END_REF][START_REF] Heeager | Meshing agile and plan-driven development in safetycritical software: a case study[END_REF]. On the question of how to develop epidemiological surveillance software, evidence shows on the one hand that Agile Processes are more effective than Structured Processes when the specification cannot be fixed at the beginning of the project [START_REF] Heeager | Meshing agile and plan-driven development in safetycritical software: a case study[END_REF]. On the other hand, MDA is more effective than code-centric approach during the development and the update/maintenance of the software [START_REF] Martínez | Empirical study on the maintainability of Web applications: Model-driven Engineering vs Code-centric[END_REF]. Then, our intuition is that: "meshing Scrum and MDA improves the development of epidemiological surveillance software". This led to the following research question: how to mesh Scrum and MDA to develop epidemiological surveillance software? We have used the term meshing as the common term for combining, mixing, and coexisting.

Our aim in this work was to do intensive research on the development of epidemiological surveillance software in order to provide a deeper understanding. Then, we choose the case study method because it is suited for understanding the complex real-world setting [START_REF] Heeager | Meshing agile and plan-driven development in safetycritical software: a case study[END_REF]. The selection of the case of epidemiological surveillance of TB was made because of the NTCP's interest to replace manual management with software management. Thus, our aims were to portray and provide a deeper understanding of the development of epidemiological surveillance of TB using MDA and Scrum Process.

To understand the current system, we thought it necessary to investigate the opinions of the stakeholders about the current system and its replacement with a software approach. To this end, a survey was conducted. This was a qualitative study during which open-ended questions were asked to the participants in order to allow them to furnish all the information required to build the system (more detail is given in Appendix A).

Stakeholders allowed us to find a real problem that health software generally faced: this is the problem of failed software mainly caused by the fact that requirements cannot be fixed. In this situation, we completed our methodology with action research [START_REF] Easterbrook | Selecting Empirical Methods for Software Engineering Research[END_REF]. In effect, we were having the NTCP willing to collaborate to both identify the problem, and engage in an effort to solve it.

Globally, the research methodology was composed of the (1) Pre-Intervention phase during which the problems at the NTCP are identified, the method to solve these problems and the list of interventions to implement are defined. (2) Intervention phase during which the solution to the problem is developed. This is a cyclic process during which the list of interventions identified during the Pre-Intervention Phase are implemented. These interventions are executed in iterations. Each iteration is composed of the planning, the implementation, the validation, the reflection. The iteration nature of the process provides us opportunities for improvements to the knowledge, methods, and better understanding of the approaches and methods. (3) Post-Intervention phase during which, all the tasks to implement (deployment, training end users, vulgarization, etc.) in order to make the solution available to the end users take place.

To collect data, we used two data collection techniques: semi-structured interviews and observations. Additional sources of data includes: supports such as pictures of paper data collection forms, Excel documents, etc.; Email which was the online channel of information exchange, decision discussion and sometimes, decision making; Meetings with stakeholders during which we took useful notes. After the data collection, the analysis consisted of labeling and organizing the data in order to identify codes, themes and relationships between them. At the end of each phase, a report was prepared and shared by email and during the meetings. The summary of the collection and analysis method is given by Tab. 1 in the Appendix B.

In this research, we choose the MDA approach, Scrum process, dia (diagramming software) and Imogene tools. (1) MDA allows us to define the conceptual models (Platform Independent Model -PIM and Platform Specific Model -PSM), which are used thereafter to automatically generate the executable source code. (2) Dia5 is used to manually construct the Platform Independent Model, represented by a class diagram. (3) Imogene6 was closer to the features expected by the NTCP. Our proximity with the MEDES, the company which developed Imogene motivated us to adopt it. (4) Scrum was used as the software development process.

Globally, the PIM was designed using Dia. Thereafter, the PIM was transformed into the PSM. Once the PSM is constructed, the corresponding applications are generated. In this research, given that there was not a tool for direct transformation of PIM to PSM, this task was done manually. The table 2 in the Appendix B presents an overview of the transformation from the PIM into the PSM and from the PSM into the source code.

Complementary information on the study design is given in Appendix A.

III RESULTS

As the result of this research, we portrait in this section the development of the EPICAM platform. Thus, Section 3.1 presents the results of the survey beside the health workers, Section 3.2 presents the results obtained during the implementation of the approach and Section 3.3 presents the results of the evaluation of the approach by people who participated to this research.

Users survey

The survey of health workers involved 8 (53%) health professionals working in four hospitals where TB patients are treated, 1 (7%) health regional delegate, 6 (40%) managers at the National TB Control Program. All the managers have worked in hospitals before being managers. During the survey, a number of data collection tools (such as registers, statistics templates, data collection sheets) were collected at the hospital, regional and central levels. Given the small sample size, we did not produced the statistics based on the questionnaire, but have summarized the findings per questions asked:

• On the question: "How do you manage your data?" We noted that at the level of hospitals, only manual management was used. At the regional and the central level, manual management was combined with software management using Microsoft Excel. • On the question: "What are the main problems you generally have?" Many problems were reported, the main are: [START_REF] Davis | Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology[END_REF] The problem of manual collection and management of data. [START_REF] Lenzerini | Data integration: A theoretical perspective[END_REF] The problem of manual analysis of data. This problem causes many other problems such as completeness, promptitude and erroneous statistics. [START_REF] Mapatano | Quelques erreurs courantes d'analyse d'un syst'eme d'information sanitaire(RD Congo)[END_REF] The problem of transmission of data using land transport. The main consequences of this problem noted were the late arrival of data collection tools, data collected and epidemiological reports at their destination. At the Regional level, the promptness was estimated less than 70%. The rapid exchange of data between doctors is done using phone calls (for instance, during a transfer/referral). The awareness of patients and the general population was done using SMS. (4) Another problem not directly linked with the system such as power and Internet outage were reported.

Only one health personnel reports that he did not have any problem with data management. We noted however that he treated less TB patients per week (generally, less than thirteen), compared to the other hospitals.

• On the question: "What is your knowledge on the use of IT tools?" Six health personnel affirm that they have basic knowledge on IT tools like Word and Excel. One of the six affirms that she already used an electronic health record. All the people from the Regional and the NTCP affirm that they have good knowledge on the use of Word and Excel, but they prefer to hire IT experts to build the Excel files they need for their statistics. • On the question "What do you expect from the use of a software for epidemiological surveillance?" Only one health worker estimated that he did not see what would be the benefit of the electronic system to his work. From the others, if we want to improve their work with an electronic tool, this tool must: (1) Solve the previous problems and be close as possible to the current tools (data collection sheets and reports) to facilitate the ease of use; (2) Consider data management such as patient registration and following, sharing patient information to entitled users, automatic generation of patient cards, easy identification of lost sigh patients, easy identification of all health centers where TB patients are treated;

(3) Allow the production and distribution of basic statistics automatically.

Implementation of EPICAM

In this section, we present the outputs of the interventions implementation. This constitutes the results of the action research applied in this study. In effect, the combination of Scrum and MDA is deemed successful when its effectiveness can be demonstrated. The successful implementation of interventions is a testimony to the success of the approach. In the next sections, we present these results organized into Pre-Intervention, Intervention and Post-Intervention.

Pre-Intervention

The aim of the Pre-Intervention was to produce a preliminary list of interventions (the summary is presented by the table 3 in the Appendix B) for the NTCP to assess, enhance and approve.

Lesson learned. The first lesson we learned was that epidemiological surveillance systems requirements cannot be fixed and change generally. Then, we should be careful of the approach and tools to use for the development of related software.

Intervention

The Intervention phase was organized into six Sprints. During the development, Scrum boards were used to display the status and progress of each sprint. Ad hoc meetings were also used when some issues were identified. During the Scrum meetings, the developers found it easy to define a common goal and commit to achieve the goal with the product owner on the one hand, and the NTCP staff on the other hand. The following paragraphs give the details of the execution of each Sprint.

Sprint 1: development of a first prototype. The goal of the first Sprint was to design the platform and to develop the first prototype. This Sprint took four iterations of one week each. All the interventions involved were not completely implemented successfully. The table 4 in the Appendix B presents a summary of the interventions implemented in this Sprint.

Lessons learned many lessons were learned during this Sprint:

• We should be careful when using a tool for the complete generation of the software: we remarked that it is difficult to find a tool that fits the requirements of a specific context. • Domain experts are not generally available: NTCP staff were involved in the modeling and the generation of the software. However, we noted during the Scrum meetings that they were not generally attending.

After a deep reflection during ad hoc meetings between the researchers, the MEDES engineer, the NTCP staff and CPC expert it was decided to develop and update the Imogene platform with the user management module that fit to the NTCP needs. Tests and experimentation. The second Sprint permitted us to obtain a first working version of the system that the end users in the field can use in a real environment. After the tests and the Scrum review meeting with the working group, we validated the developed platform with eight health workers in six hospitals.

Lesson learned globally, two lessons were learned at the end of this Sprint: (1) beyond the Scrum team, the end users must be integrated in the validation of the software; (2) the immaturity of the MDA tool can slow down the development of the software system. Then, it can be a serious barrier to its adoption.

Sprint 3: Updating the application. The third Sprint consisted of the updating of the application by the integration of the end users remarks and the generation of another prototype. This was done in only one week and the Scrum weekly meeting allowed us to validate the new version.

Sprint 4: Developing the reporting and mapping modules. During the fourth Sprint, the reporting and the mapping modules were developed (by the developers supervised by MEDES engineers) in two months, organized in 5 Sprints. The reporting module was developed using Business Intelligence and Reporting Tool (BIRT 7 ). The mapping module was developed using Open Street Map (OSM 8 ). During the Scrum meetings with the working group, the users validated these modules. Then, they were tested, validated at the NTCP and integrated in the code generator. A new version of the platform was validated by the previous users in the field.

Sprint 5: Developing the SMS module.

The fifth Sprint consisted of the development of the SMS module in one month with 3 Sprints. To this end, we used Spring Rest API 9 . Actually, to send SMS using the platform, we decided to use a service provided by an SMS provider. The SMS module was tested, validated at the NTCP and integrated in the code generator. The new version of the epidemiological surveillance software generator containing a new version of user management module, reporting module, mapping module and SMS module were named EPICAM 10 and hosted on github. The PIM was transformed into PSM and a platform that we also named EPICAM was generated for the epidemiological surveillance of TB in Cameroon.

As a code-centric developer, we found the development of additional modules arduous than the development of code-centric application. In effect, it was question to reverse engineer Imogene in order to add new elements to generate in the code generator and to link these elements to the graphical interface for the modeling. Sprint 6: system update by non-informatic experts. In this research, we wanted a method that allows non-informatic experts to be engaged in the development/updating of their system. Thus, after the development of the platform, the goal of the current Sprint was to prepare the health workers to take charge of the updating. Then, it involved the simulation of the interventions summarized by the table 6 in the Appendix B.

Lessons learned: we learned that counting on health workers to update the system is not advisable. In effect, generally, they have a full time employment and their commitment to contribute to implement interventions is during their sparse time.

Although these can be classified as failed interventions, the experience has some merits. It gave insights on what should be done to make non-informatic experts update or even develop their system: develop a drag and drop modeling tool.

Post-intervention

The Post-Intervention consisted of training end users in the use of the software developed for epidemiological surveillance of TB, deploying the final platform and disseminating the outcomes of the project.

The final version 11 were experimented in 25 pilot sites across the country. Given the success of this pilot phase, the NTCP has adopted the software as its electronic epidemiological surveillance software and extended it in twenty new health centers during the years 2016 and 2017.

Perceived ease of use and perceived usefulness

The developers and the NTCP staff involved in the development were invited to give their opinion on the combination of MDA and Scrum to develop epidemiological surveillance systems. The analysis of the case data using the Technology Acceptance Model [START_REF] Davis | Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology[END_REF] showed that the developers have found it easy and useful to combine agile and MDA for the development of epidemiological surveillance software. However, even if non-informatic experts easily handled and adopted Scrum practices, they found the approach difficult to use because of the lack of skills in modeling and the use of the modeling tool. Table 7 in Appendix B provides an overview of the results.

IV DISCUSSION AND CONCLUSION

In this research, we show how to combine Scrum and MDA to develop epidemiological surveillance software. At its end, we found that if the MDA tool is mature enough, the combination of Agile and MDA have positive effects on programmer productivity and satisfaction, costeffectiveness, timelines and customer satisfaction.

The generalization of this research can be seen at the level of the case study research. In fact, the selection of a case must be done so that if the research works for this case, it is likely to work for many other cases. But we just chose the epidemiological surveillance of TB because the NTCP were available to collaborate with us in order to find a solution to their problems. We can think that this may hamper the generalizability at the level of epidemiological surveillance systems. But not really because the head of the epidemiological service at Centre Pasteur du Cameroon were involved in the research. This service is specialize in the monitoring of several infectious diseases whose rabies, HIV, Influenza, meningitis, etc.

A DETAILS ON STUDY DESIGN

The research team consisted of two persons playing the role of researchers and software developers. Both had a strong background and experience in Scrum and Model-Driven Engineering Techniques and tools. The target population of the research was a big stakeholder group including: the product owner working at NTCP, the NTCP Staff who is the technical staff at the NTCP, end users who are the health workers at the different levels of the health system and two epidemiologists -one epidemiologist from the NTCP and one epidemiologist from Centre Pasteur du Cameroun (CPC). The NTCP represented by the Product Owner led the recruitment of the NTCP staff and the end users. Globally, all the people at the NTCP willing to participate in the project were accepted. At the hospital level, the NTCP have chosen the ones that furnish greater amounts of data in the center region for the survey, in the Center region and Littoral Region for the tests.

To understand the current system, we collected the opinions of the final users at all levels of the NTCP. To this end, we conducted the survey. The main goal of this survey was to find out what the stakeholders think of the replacement of manual management by software management. The specific objectives were: Understand the current network, Know how stakeholders collaborate, Collect the specific needs of users in the field to complete the specifications already gathered, Determine the computer skills of users of the current surveillance network, Know the opinion of final users about an electronic network. These objectives gave rise to the following questions:

1. How do you manage your data? 2. What are the main problems you generally have? 3. What is your knowledge on the use of IT tools? 4. What do you expect from the use of a software for epidemiological surveillance? During this research, we collaborated with the NTCP which were using manual tools for epidemiological surveillance in order to identify the problems they have and the challenges to effectively replace this manual management by the software approach. To this end, we needed a method and a process that fully engaged the stakeholders. That is why we set-up an action research method in which we as researchers and the NTCP as the problem owner were engaged collaboratively to identify the problems and develop effective solutions. This process is constituted by a set of consecutive actions and reflections forming a collaborative approach to research whereby the researcher partners with the subject being studied to achieve a particular outcome. It consisted of a set of aggregated interventions to develop epidemiological surveillance software of TB. These interventions involved a series of actions taken during the development of the epidemiological surveillance of TB in order to come up with an effective system. It is organized into the Pre-Intervention, the Intervention and the Post-Intervention phase.

Pre-intervention phase. During the Pre-Intervention, we identified the problems and proposed solutions.

These solutions are divided to give a list of interventions. Thereafter, we conduct an empirical investigation of the research environment by interviewing health workers at all the levels of the health system. This empirical investigation allows us to identify problems and issues related to the current system. At the end, we identified a shared practical problem that was presented to the NTCP staff.

Intervention phase. Involves the development of the solution to the problem. It is cyclic, implemented through iterations of planning, implementing, validation, and reflecting. During the Intervention Phase, the list of interventions identified during the Pre-Intervention Phase are implemented. These interventions are executed in iterations. Each iteration is composed of the planning, the implementation, the validation, the reflection. The iteration nature of the process provides us opportunities for improvements to the knowledge, methods, and better understanding of the approaches and methods.

Post-Intervention Phase. Once the Intervention Phase is completed, Post-Intervention takes place. It includes all the tasks to implement (deployment, training end users, vulgarization, etc.) in order to make the solution available to the end users.

To collect data during the project, we used two data collection techniques: semi-structured interviews and observations. The data were recorded by taking notes in structured form in a notebook. These notes were supplemented with pictures (for instance, the photos of data collection forms). After the data collection, the analysis consisted of labeling and organizing the data in order to identify codes, themes and relationships between them (the summary is given in table 1).

Sprint 2 :

 2 implementing user management module generator. The interventions involved in this Sprint comprised on the one hand the specification, analysis, design, development and integration of the user management module in the Imogene platform and on the other hand, the modeling and generation of the first prototype. These interventions were done by the researchers supervised by the MEDES engineers. It lasted 4 months with 8 Sprints. The table 5 in the Appendix B presents the summary of the list of interventions implemented during this Sprint.

http://www.medes.fr/fr/nos-metiers/la-e-sante-et-l-epidemiologie/la-tele-epidemiologie/projet-epicam.html

https://uy1.uninet.cm

https://www.pasteur-yaounde.org

http://www.medes.fr

www.dia-installer.de

https://github.com/medes-imps/imogene

https://www.eclipse.org/birt/

https://www.openstreetmap.org/

https://spring.io/guides/tutorials/rest/

https://github.com/UMMISCO/EPICAM

Source code generated: https://github.com/ummiscolirima/epicam_tb

B LIST OF TABLES

Complete

After the definition of the product backlog, the definition of the specifications, analysis and product backlog goes in Scrum iteration. During this process, Scrum meetings allowed the NTCP to make remarks and improve the product.

Incomplete

The installation difficulties discourage the health worker from continuing the experience. The customer were more close to the development and the use of models facilitated the communication.

The early deployment allowed us to discover new requirements and facilitate the acceptance of the final product.

Table 7: Overview of the results of the evaluation of the combination of Scrum and MDA by the two developers and three health personnel (representing 27% of the whole team who were involved at the beginning)


Bérard Emilie

Dillmann Philippe

Réguer Solenn

Vega Enrique

Verna Catherine

Toureille Valérie

Guillot Ivan

Understanding the manufacturing techniques of Renaissance armour: a coupling between metallographic and SR-XRD investigations

From the late Middle Ages onwards, complete suit of armour is a highly manufactured product, composed of a multitude of ferrous alloys plates skilfully articulated to protect its wearer. Studying the nature of metal used to make such pieces is of great interest for historical research, especially for the understanding of manufacturing techniques, including how materials were produced and traded by ancient societies. To decipher the structure of alloys, metallography is a very efficient technique but required to take samples on the artefacts. Furthermore, to be representative of the ancient ferrous metals that are very heterogeneous, it is in many cases necessary to get several samples on the same piece. As sampling possibilities are limited in case of museum artefact, non-invasive techniques as X-ray diffraction (XRD) are well suited to identify the different phases, characteristic of ancient ferrous alloys, such as ferrite and cementite (Fe3C). Nevertheless, such experiment presents analytical challenge due to the complex shape of armours. A specific methodology was therefore developed to conduct XRD measurements under synchrotron radiation at the SOLEIL-DiffAbs beamline to study fifteen pieces of armour, all stamped with the mark of Valentin Siebenbürger's workshop, armourer in Nuremberg at the beginning of the 16th c. This was a unique opportunity to assess the nature of the metal of artefacts made in a same workshop, thanks to the collaboration of the Musée de l'Armée (Paris, France) and the Musée des Beaux-Arts of Rennes (Rennes, France). The study presents and discusses the methodology developed for XRD measurements to determine the spatial distribution of mineral phases in ferrous alloys directly on large and complete museum amour pieces. Thanks to the very high brightness of the synchrotron source and the fast acquisition time using the pixel-hybrid 2D detector CIRPAD, it was possible to multiply the analyses on the same object in order to estimate the variability of the alloys used (carbon content, heat treatments...) at the scale of separate plates. Heterogeneities related to the nature of the metal, revealed by variations in the intensity and shape of certain peaks (as for cementite and ferrite phases), were highlighted. These results were coupled and discussed with metallographic investigations performed on a few samples and raise new questions about the manufacturing processes of the armours.


Promoting Access of Transgender and Gender Diverse People to Primary Care

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Promoting Access of Transgender and Gender Diverse People to Primary Care -A systematic review of activist literature

Baleige A 1 , Guernut M 2 , Denis F 1,3 ¹EA 7505 Éducation Éthique Santé -Tours University, Tours, France; ²UMR 8163 Savoirs Textes Langage -Lille University -CNRS, Lille, France; ³Faculty of Dentistry -Nantes University, Nantes, France

Discrimination appears as a central factor, as lack of training of professionals…

Systemic discriminations against transgender and gender diverse individuals impact access to information and services, quality of service received, as well as training and research.

These elements appear all the more important as people evolve outside the norms of heterosexual gender binarity, i.e. non-heterosexual orientation or gender diverse identity.

Transgender organizations have a high level of expertise on identifying ecologically valid problems and solutions.

BACKGROUND

The visibility and number of the transgender and gender diverse population is increasing. They present transdisciplinary needs and face systemic barriers to accessing care. Primary care is promoted as a new organizational entry point for care. Yet, a significant number of individuals report poor experiences and avoid seeking help.

What are ecological barriers and levers of access to primary health care for trans people?

We conducted a systematic review of activist literature from Europe… …and modelized the impacts of discriminations on primary care

The image above shows a modelization of the impact of discriminations on access to primary care, based on data codes and a network analysis of cooccurrences of data codes

We are now working on specific data extractions for main health challenges: STDs, procreation, addictions, … And advocating for public health reform based on health promotion strategies from experiential and field knowledge


Frédéric Denis

Meeting Health Needs of Transgender and Gender Diverse People in Primary Care based on Free and Informed Consent

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Meeting Health Needs of Transgender and Gender Diverse People in Primary Care based on Free and Informed Consent

Baleige A 1 , Guernut M 2 , Denis F 1,3 ¹EA 7505 Éducation Éthique Santé -Tours University, Tours, France; ²UMR 8163 Savoirs Textes Langage -Lille University -CNRS, Lille, France; ³Faculty of Dentistry -Nantes University, Nantes, France

Support self-determination and human rights!

Public health-based approaches share an epistemic proximity to arguments from the activist world, unlike specialized approaches, particularly in mental health, which lack ecological validity. Concrete examples of successful implementation also tend to reinforce this practical validity.

Conceptualizing trans people as a population at risk for systemic risks appears a better solution than hyperspecialized approaches based on diagnostic and prognostic assessment.

Thus, transforming health care services towards primary care does not mean shifting tasks, but rather putting forward new practices and a new medical and paramedical stance in the service of self-determination and human rights.

FIELD DYNAMICS

Transgender and gender diverse individuals represent a heterogeneous and growing population. Unmet needs, epistemic changes and political activism are leading to a transformation of care delivery. The free and informed consent model based on primary care is widely promoted. General practitioners remain insufficiently trained and informed about trans issues.

Literature reviews and consensus support a public health approach based on trans people health needs

(this means understanding that trans healthcare is more than medical transition)

For activist data, see ePOSTER P10-008

The image above shows a modelization of current dynamics in innovative field practices to integrate trans healthcare in primary care based on the community care model, WHO & Wonca We need to build shared knowledge between consumers and professionals to face epistemic inconsistencies. We are advocating for public health reform based on health promotion strategies from experiential and field knowledge.