Vincent Malleron
email: vincent.malleron@liris.cnrs.fr

Véronique Eglin

Hubert Emptoz

Stéphanie Dord-Crouslé
email: stephanie.dordcrousle@ens-lsh.fr

Philippe Régnier

Text lines and snippets extraction for 19th century handwriting documents layout analysis

In this paper we propose a new approach to improve electronic editions of human science corpus, providing an efficient estimation of manuscripts pages structure. In any handwriting documents analysis process, the text line segmentation is an important stage. The presence of variable inter-line spaces, of inconstant base-line skews, overlapping and occlusions in unconstrained ancient 19th handwritten documents complexifies the text lines segmentation task. In this paper, we only use as prior knowledge of script the fact that text lines skews can be random and irregular. In that context, we model text line detection as an image segmentation problem by enhancing text line structure using Hough transform and a clustering of connected components so as to make text line boundaries appear. The proposed approach of snippets decomposition for page layout analysis lies on a first step of content pages classification in five visual and genetic taxonomies, and a second step of text line extraction and snippets decomposition. Experiments show that the proposed method achieves high accuracy for detecting text lines in regular and semi-regular handwritten pages in the corpus of digitized Flaubert manuscripts ("Dossiers documentaires de Bouvard et Pécuchet", 1872-1880).

Introduction

Our work takes place in an human science project which aims at the realization of an electronic edition of the "dossiers de Bouvard et Pécuchet" corpus. This corpus is composed of French 19th century manuscripts gathered by Gustave Flaubert in order to prepare the redaction of a second volume to his Novel "Bouvard et Pécuchet". Corpus contents are diversified in term of sense as well as in term of shape (different writers, styles and layouts). Besides, the corpus is mainly composed by text snippets (Newspapers extracts, various notes, etc.) put together by Flaubert. To produce the electronic edition we must consider the particular framework of the corpus : structure informations must be known in order to reproduce as well as we can its primary state, and restore snippets mobility. In order to retrieve structure informations we propose a three-step algorithm : at first, we roughly determine the page layout, then we extract the lines of the manuscript, and we finally rebuild the page structure. This paper is organized as follows : section 2 will detail previous works on text line extraction and structure recognition, section 3 and 4 will present our approach for page layout analysis, text lines and snippets extraction, section 5 provides results and perspectives, section 6 gives concluding remarks.

Related works

Handwritten text line segmentation is still a challenging task in ancient handwritten document image analysis. All segmentation techniques that must be applied to handwritten documents provide information for skew correction, zone segmentation, and sometimes character recognition. As related in [START_REF] Sulem | Text line segmentation of historical documents: a survey[END_REF], some preprocessing techniques must be performed before text line extraction so as to enhance text lines. Here we only focus on text lines and zones extraction techniques. In works on handwritten documents it is often assume that text lines are already segmented or easy to be segmented so that conventional methods can be applied. But in practice handwriting variability is omnipresent in ancient handwritten documents and it is not trivial to extend machine printed documents algorithms to handwritten documents, especially when handwritten text lines are curvilinear and when neighboring handwritten text lines may be close or touch each other. In handwriting drafts for example, the page layout cannot be handled by simple rules, such as grouping based on geometric relationships of neighboring components, [START_REF] Fletcher | A robust algorithm for text string separation from mixed text/graphics images[END_REF][START_REF] Rothfeder | A scale space approach for automatically segmenting words from historical handwritten documents[END_REF][START_REF] Manmatha | Scale space technique for word segmentation in handwritten documents[END_REF][START_REF] Martin | Text line segmentation and word recognition in a system for general writer independent handwriting recognition[END_REF]. So it is a real challenge to analyze freestyle handwritten document also due to non standard and irregular layout at the page level. At lines level, conventional approaches based on linear approximation and regression can not always be efficient. At words level, due to the frequent connectivity between characters and words, it is often complex to process the connected components. A connected component can represent character of different sizes that is considered as an important parameter for the bottom-up connected component based text line segmentation algorithms, [START_REF] O'gorman | The document spectrum for page layout analysis[END_REF]. Most of works based on text line segmentation can be roughly categorized as bottom-up or top-down approaches. In the top-down methodology, a document page is first segmented into zones, and a zone is then segmented into lines, and so on. Projection based methods is one of the most successful top-down algorithms for printed documents and it can be applied on handwritings only if gaps between two neighboring handwritten lines are sufficient [START_REF] Yu | A robust and fast skew detection algorithm for generic documents[END_REF]. Of course, one strong hypothesis for the application of such techniques is the existence of standard and regular page layout. Other researchers use different assumptions for specific script and specific contexts in mixed strategies, both top down and bottom up [START_REF] Pal | Multioriented and curved text lines extraction from indian documents[END_REF]. An achieved taxonomy of approaches reveals six major categories [START_REF] Sulem | Text line segmentation of historical documents: a survey[END_REF] : projection-based, smearing, grouping, Hough-based, repulsive-attractive network and stochastic methods. For the authors, most of these methods are able to face some image degradations and writing irregularities specific to historical documents. In that context, we propose an approach that is well adapted to authors handwritings.

Page layout analysis

Our corpus is composed by pages of various styles and shapes. We can classify most of the pages in the following categories, represented on figure 1 : (1-Note pages, 2-Gathered Informations, 3-Letters, Novel extracts, 4-Dictionary, 5-Printed text (not represented)) We introduce three simple rules to classify corpus pages into those fives categories : number of library stamps in the page, amount of data in page and profile dispersion. For the original handwritten pages conservation, the library has appended a stamp near each pasted textual fragments. Therefore number of stamps in the page allow us to separate easily dictionary pages, gathered informations pages and others : a dictionary page has a least seven stamps, pages of gathered informations have between two and six stamps, other pages have one stamp or none. The number of library stamps in page is retrieved by template matching. Printed text pages are generally pages of high text density. We computed the amount of data in each page in order to separate printed text pages from others. The separation be- where I is the vertical projection profile value and X the width of the page. Figure 2 shows that vertical profile projection characterizes the layout of the page. Typical profiles and dispersion values are provided.

The knowledge of page layout style helps us to choose algorithms and decision values for lines and snippets extraction. In the following sections we will only present our algorithm on exclusive handwritten pages of the corpus. Machine printed pages are easy to separate from the rest of the corpus and have been processed successfully with an OCR.

Text Line and Snippets Extraction

Text line extraction is the preliminary work for snippets extraction. Retrieving the lines of the text in the manuscript is also an important issue for transcription matching with the manuscript. Our algorithm relies on 5 steps : connected components extraction and neighborhood-fan computation, corner and borders detection, line orientation estimation, line construction and post-processing.

Corner and Borders extraction

Corner and Borders extraction provide a primary information of the document structure and an initialization for text line reconstruction. Extraction is realized using a k-means classification on a neighborhood fan based vector. We extract the 5 following classes : Left components, Right components, Top components, down components and inside-text components. We use a 18 value vector, each value standing for a spatial direction. The value is 1 if there is no neighbor in the direction of the space, and 0 is there is one. The distance between two vectors is computed as follow :

D(V 1 , V 2 ) = 17 i=0 ρ i |V 1 (i) -V 2 (i)|
with ρ i = 2 if i ∈ 0, 4, 8, 9, 13, 17, ρ i = 1 elsewhere ρ i gives more weight to components located in the most frequent space directions. Figure 3 presents the result of border extraction on a sample snippet and associated neighborhood-fans.

Line orientation estimation

For each component we estimate the local line orientation with Hough transform. The transform is performed at low resolution after application of a canny edge detector. We compute an orientation map of extracted hough lines and each component gets its orientation from the associate line in orientation map. Out of bound orientations are filtered in order to avoid errors. We consider that line orientation in our document is in a -45/+45 degrees range. Hough based methods are mainly adapted to straight lines but the Hough transform has been computed here for each local connected component considered as small window of text inspection. It allows to solve some recurrent problems of line proximity, overlapping and fluctuating close lines. Some local considerations (i.e. in small inspection windows that can be included into connected components bounding boxes) could be thought to solve some other difficulties based on touching strokes.

Line construction

Line construction is realized using the results of the two previous steps for the initialization. A text line starts on a right-labeled component and stops on a left-labeled component. Research direction is given by the hough transform result and by the latine script direction. We consider that orientation has a small variation in a line. When hough transform result differs from more than 10 degrees to the current line mean orientation, mean orientation is used for the next computation step. Sample results of the line extraction are shown on figures 4,5,6. A post-processing step is performed to merge line detected at the same horizontal position and include a component positioned between two components of the same line in the line.

Snippets decomposition

Snippet extraction has been developed here to perform transcript mapping with non rectangular polygonal fragments. The method must fit the document layout : Novel extracts or letters pages generally contain only one snippet, containing the whole page. Gathered Informations snippets are generally easy to extract on those pages, because the interline space between snippets is high. An example of a typical gathered informations page is illustrated on figure 4. Notes pages have the most complicated structure type : we must use relationships between sense and structure to perform snippet decomposition. We can also notice on figure 6 some errors occurring on the two text

Results and Discussion

Our page layout classification heuristic has been evaluated on a sample of 280 labelled images of the corpus, representative of the corpus diversity (about 3000 pages). Table 1 shows that we characterize pages layout with 3 simple characteristics. Addition of other characteristics could improve our results but a rough classification is enough to perform the followings steps of our algorithm. Figure 4 shows the result of snippets decomposition on a gathered informations page. The layout of this page is relatively easy The major difficulty on this kind of page consists in obtaining a precise text line, with all descenders and ascenders segmented for accessing isolated and non overlapping components. As segmentation and text line reconstruction are two dependent tasks, an exact segmentation of touching writing connected components pieces may need some knowledge about possible and regular touching configurations. Figure 5 exposes results for fourth category pages. We obtain similar results on dictionary pages. Line structure information is successfully retrieved. Fourth category pages structure are mainly composed by a single snippet : we only extract line structure. Dictionary pages are preprocessed using a vertical profile projection to separate the two columns. Afterward we use the same algorithm to extract line structure of the column. Figure 7 shows the current result of our approach on a more complicated page of the corpus. Current limitations are enlighted : a wrong border extraction leads to the omission of several lines. A false orientation information, line overlapping can occur. Bad snippets extraction could also appear when a line is not well detected. Our approach will be completed by using non textual elements (diacritics, stamps or underlines) to improve snippets decomposition.

Concluding remarks

In this paper, we proposed a dedicated text line segmentation approach for author's draft handwritings. Knowing that snippets extraction on an humanist corpus is usually a costly and time-consuming hand-made task, it is necessary to provide useful tools for the pre-extraction of snippets in a drafts documents. Experiments of our approach show that our proposition is really consistent regarding the complexity of many page layouts in the corpus. Our methodology can be compared to conventional text line segmentation methods, such as projection based top-down approaches and other connected component based bottom-up approaches and shows very promising results.

Acknowledgment

These studies had the support of the Rhone-Alpes Region in the context of cluster project. We also want to acknowledge the consortium of the "Bouvard et Pécuchet" ANR Project. Images are property of Rouen's town library.

Figure 1 .

 1 Figure 1. Sample images of our corpus

Figure 3 .

 3 Figure 3. Borders and NeighbouroodFan

Figure 4 .

 4 Figure 4. Gathered Information structure

Figure 5 .Figure 6 .

 56 Figure 5. Novel extract page structure

Figure 7 .

 7 Figure 7. Complex Note Page

Table 1 . Recall/Precision Table of classifica- tion

 1

	Class	Images Recall Precision
	Letters	50	0.90	0.92
	Gathered Inf.	45	0.95	0.86
	Printed Text	50	0.90	0.96
	Notes	70	0.71	0.78
	Dictionary	52	0.96	0.88
	All	267	0.884	0.88


Olivier Glassey
email: olivier.glassey@idheap.unil.ch

Method and Instruments for Modeling Integrated Knowledge

Rules: statements which can be proven true within some logical framework, usually represented as a set of attributes value.

-Frames: a structural skeleton used to collect information on a given concept and associated actions.

-Semantic networks: directed graphs consisting of vertices which represent concepts and edges which represent semantic relations between the concepts.

-Concept diagrams: graphical display of concepts connected by directed arcs, in many aspects similar to semantic networks.

) definition of knowledge visualization. They studied all graphic means that can be used to construct and convey complex insights and they propose several visualization types:

-Heuristic sketches or ad-hoc drawings.

-Conceptual diagrams: abstract, schematic representations of structural relationships.

-Visual metaphors: used to structure information and convey normative knowledge through the connotations of the metaphor.

-Animations: interactive descriptions of procedural knowledge.

-Knowledge maps: they do not represent knowledge but rather reference it.

-Scientific charts: based on computational algorithms.

As MIMIK is a formalized method, we chose not to use ad-hoc drawings or animations. The representation types we found most relevant to our work were the conceptual diagrams and the knowledge maps. In section 3 we will show how MIMIK relies on these conceptual diagrams and knowledge maps to model processes and knowledge within organizations, and particularly those involved with public administration where our approach has been applied and validated.

 classifies knowledge representation within organizations in three categories of knowledge maps:

-Concept-based maps: taxonomies for capturing and organizing knowledge of an organization around topical areas; they improve visibility and usability of organizational knowledge.

-Competency-based maps: overview of expertise that resides in an organization, along with the identification of entities who possess such expertise; they improve the usability of intellectual capital within an organization.

--From implicit to implicit knowledge: socialization.

-From implicit to explicit knowledge: externalization.

Introduction

The goal of this paper is to present a framework developed in order to model and share knowledge within large organizations whether they be private or public. Called MIMIK (Method and Instruments for Modeling Integrated Knowledge), it is based on a methodology, on eight different models for graphical representation and on a knowledge-sharing system. MIMIK provides an explicit representation of reality in terms of concepts (or processes) and their relationships with the overall objective of supporting the processing, storing and retrieving of knowledge.

The field of knowledge representation is not new: mathematical tables, graphs or set theory has been used to structure and represent knowledge long before information systems were developed. However, whereas mathematical models rely only on mathematics for expression, interpretation and validation of a model, other types of models, such as political, social or psychological models need to define their own concepts and relationship types (what is now called an ontology) and furthermore these models have to be validated through experience. Models are used to provide a framework to describe concepts and to reason about these concepts in order to create new knowledge. It is appropriate to note that philosophers have been debating for centuries about knowledge, perception and representation. Although, in this paper we make reference to concepts that are located in other fields of research such as philosophy or psychology, the focus of this paper is on knowledge management within organizations and on knowledge sharing through information technology.

To define our methodology we make use of the knowledge management life-cycle proposed by [START_REF] Nissen | A Framework for Integrating Knowledge Process and System Design[END_REF]. They studied four different characterizations of the knowledge management life-cycle and from these they created a combined model consisting of 6 phases: create, organize, formalize, distribute, apply and evolve knowledge. They also presented a review of the tools, technologies and practices were available for each of these phases. In a similar fashion we propose a set of instruments for each phase which are described in section 2.

According to Gordon [START_REF] Gordon | Creating Knowledge Maps by Exploiting Dependent Relationships[END_REF], there are several accepted methods of knowledge representation in the domain of AI applications and information systems:

Process-based maps: representation of business processes and related knowledge; they show which type of knowledge is to be applied at a certain process stage and provide pointers to locate that specific knowledge; they are also useful to identify critical knowledge for the core business of an organization. MIMIK's approach to knowledge representation is based on diagrams that graphically display concepts and their relationships. It does not use rule-or frame-based representation. In order to visualize knowledge we chose to use the knowledge maps approach and we cover the concept, competency and process types of knowledge representation. However MIMIK does not only provide for the representation, organization and storage of knowledge, it also provides instruments that support knowledge sharing, such as the prototype described in section 4.

In their review of the conceptual foundations for knowledge management and in the section dedicated to knowledge transfer, [START_REF] Alavi | Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues[END_REF] classify knowledge transfer channels as informal or formal, personal or impersonal. They provide a few illustrative examples: coffee break meetings are typically informal, personnel transfers within departments during a training period are formal and personal, knowledge repositories are formal and impersonal, and so on. As a basis for their analytic framework, [START_REF] Alavi | Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues[END_REF] rely on the four processes of knowledge creation defined by [START_REF] Nonaka | The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Evolution[END_REF][START_REF] Wasko | Why should I share? Examining Social Capital and Knowledge Contribution in Electronic Networks of Practice[END_REF] explain that the availability of electronic communication technologies is no guarantee that knowledge sharing will actually take place and examine why people voluntarily contribute knowledge. They make a distinction between communities of practice, i.e. groups whose members are engaged in a shared practice and know each other and work together, and networks of practice, i.e. loosely knit groups of individuals who are engaged in a shared practice but who do not necessarily know each other. [START_REF] Wasko | Why should I share? Examining Social Capital and Knowledge Contribution in Electronic Networks of Practice[END_REF] studied knowledge sharing within networks of practice and identified two main potential problems:

-Knowledge seekers have no control over the respondents and over the quality of the responses.

-Knowledge contributors have no assurances that those they are helping will ever help them in return (reciprocity).

McLure at al. believe this sharply contrasts with traditional communities of practice where people typically know each other and interact over time, creating expectations of obligations and reciprocity that are enforceable though social sanctions. From their detailed survey on knowledge sharing, they conclude that contributors care just as much about their personal/professional reputation within the network of practice and that reputation is sufficient to guarantee the quality of responses in most cases. Furthermore they found out that contributors do not expect direct reciprocity (from a person that they responded to or helped once) but rather third-party reciprocity. Indeed members expect answers from third-parties, i.e. people that they did not help directly but that were helped by some other member of the community. Third-party reciprocity implies a critical mass of active participants within the network of practice.

Modeling Knowledge

As mentioned in the introduction, MIMIK aims at providing a method and instruments for modeling integrated knowledge. Method is understood here as a series of steps taken to reach a certain objective, and the term instruments is used in the sense of concrete or abstract tools intended to assist their users in fulfilling a given objective. These instruments consist mainly of abstract models that represent reality symbolically, making use of concepts and relationships, and implemented as diagrams, i.e. simplified and structured visual representations of concepts and relations. In this paper we will often use model and diagram synonymously and we will define MIMIK recursively by using MIMIK models. Fig. 1. MIMIK is intended to reach pre-defined objectives by applying a defined method and using a set of existing models. [START_REF] Nissen | A Framework for Integrating Knowledge Process and System Design[END_REF]. However we considered that creating and evolving knowledge belonged to the same phase: in most cases organizations do no create knowledge ex-nihilo and then work on its evolution; we would rather consider it as a continuous creation cycle. It is also important to note that the steps identified in MIMIK do not necessarily have to be taken in a predefined order.

MIMIK relies on graphical representation to create and organize knowledge and Fig. 3 shows how it supports the knowledge transfer types defined by [START_REF] Nonaka | The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Evolution[END_REF], although these knowledge creation modes are not pure, but highly interdependent and intertwined [START_REF] Alavi | Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues[END_REF]:

-Organizing and formalizing knowledge helps making implicit knowledge explicit (externalization).

-Formalized knowledge can be used to create new explicit knowledge and to share it (combination).

-Shared explicit knowledge can be used and applied by actors that will interiorize this new knowledge (internalization).

-As MIMIK works on knowledge representation and formalization, it is rather selfevident that it does not support implicit to implicit knowledge transfer (socialization).

MIMIK Models

MIMIK is based on the model theory approach developed by [START_REF] Wyssusek | Business Process Modeling as an Element of Knowledge Management -A Model Theory Approach[END_REF]) who aimed at integrating process modeling and knowledge management. They provide an epistemological foundation to justify their approach, but they do not offer any practical methodology or examples. We analyzed the concepts, the models and the application domains of Adonis, OSSAD and UML [START_REF] Glassey | Comparaison de trois techniques de modélisation de processus: ADONIS, OSSAD et UML[END_REF] and furthermore studied several modeling methodologies with very different backgrounds in order to provide a practical approach:

-Adonis is a software tool for modeling operational processes and it has its own proprietary modeling technique and description language [START_REF] Junginger | Ein Geschäftsprozessmanagement-Werkzeug der nächsten Generation -ADONIS: Konzeption und Anwendungen[END_REF]. It is one of the many commercial methodologies that are tightly integrated with a modeling environment, such as Aris Toolset (from IDS Scheer AG), Mega Process / Mega Designer (from Mega International, Inc.) or Bonapart (from Pikos GmbH). These tools are widely used in large firms and the public domain.

-ARIS is a very successful method and toolset for modeling business process, used in many universities throughout the world for research and teaching activities [START_REF] Scheer | ARIS -Modellierungsmethoden, Metamodelle, Anwendungen[END_REF]).

-

OSSAD is an open and standard modeling method for organizations and information systems [START_REF] Chappelet | Un langage pour l'organisation : l'approche OSSAD[END_REF][START_REF] Dumas | La Méthode OSSAD, pour maîtriser les technologies de l'information[END_REF]. It was developed as part of an ESPRIT research project. Open source modeling methodsare not very common, the only comparable one is OPEN (Object-oriented Process, Environment and Notation), developed and maintained by a not-for-profit consortium [START_REF] Henderson-Sellers | The OPEN Toolbox of Techniques[END_REF].

-MOKA is a methodology for developing knowledge-based engineering applications, in particular in the fields of aeronautical and automotive industries, and it is used for designing complex mechanical products (MML, 2000).

-CommonKADS is a methodology developed to support structured knowledge engineering also as part of the ESPRIT Program. It is now essentially a European de facto standard for knowledge analysis and knowledge-intensive system development, used by many companies and universities [START_REF] Schreiber | Knowledge Engineering and Management: The CommonKADS Methodology[END_REF].

-UML is a non-proprietary modeling and specification language, with a strong focus on object-oriented software-intensive systems [START_REF] Booch | The Unified Modeling Language User Guide[END_REF].

We also used the work of Mentzas et al. (Mentzas et al., 2001) on process modeling and workflow models. They present several techniques for workflow modeling, amongst them activity-based workflow modeling. A workflow is defined as a partial or total order of a set of tasks, and a task is defined as partial or total orders of operation or descriptions for human actions. Mentzas et al. also integrate the concepts of manipulated objects (documents, data records, hardware, etc.), roles (responsibility for a particular task) and agents (humans or information systems filling roles).

MIMIK consists of 8 types of diagrams (Fig. 4), most of them being inspired or directly taken from existing modeling techniques. As in UML or other modeling languages, it is not necessary to use all of them in order to provide a good representation of reality. Users should rather select the diagrams that suit their needs and goals in terms of modeling. Concept maps are the top-level diagrams that show the strategic goals of an organization in terms of functions or processes and their relationships. The metamodel of our framework is itself described with concept maps (Fig. 1234). These concept maps can be decomposed into several levels. When a concept map does not have any "child" map, it is considered as a terminal node. Normally a terminal node of a concept map should be described by a context diagram. Concept maps were developed by [START_REF] Novak | Learning, Creating , and Using Knowledge: Concept maps as facilitative tools for schools and corporations[END_REF] and we designed them with IHMC CmapTools (cmap.ihmc.us). A knowledge packet is an abstract representation of a set of knowledge components. These components encapsulate documents, databases, files, implicit knowledge, etc. and they will be explained in detail further on in this section. Knowledge packets represent, at the abstract level, what type of knowledge is necessary in order to complete a process and which knowledge is relevant in a given context. At this level actors are also represented generically and no difference is made between physical actors and their roles. This will be described with the actors-roles diagrams, as explained further on.

One of the goals of MIMIK is to describe the interactions between strategic goals, actors, knowledge and processes. That is why we developed the concept of knowledge matrices, in order to provide formal links between knowledge and processes (Knowledge-interaction matrix) and knowledge and actors (Knowledge-actor matrix). Each context diagram has a single corresponding knowledge-interaction matrix and a single corresponding knowledgeactor matrix. Fig. 6. Knowledge-interaction matrix formally linking MIMIK diagrams (represented as knowledge components) to MIMIK strategic processes or objectives. Some new models are introduced here, but they will be clarified further on. Actor-role diagrams can be either classical organizational charts, actors-role diagrams such as shown in Fig. 8, or matrices that formally link actors and roles in cases where the organization is too complex to be able to show these relationships graphically in an intelligible way. In a similar fashion to the way that knowledge-interaction matrices link knowledge components and interactions, knowledge-actor matrices (Fig. 9) create a formal relation between knowledge components and real actors within an organization. This proves very useful in order to introduce implicit knowledge in a graphical model: it might not be possible to transform such implicit knowledge into explicit knowledge but at least we know who has this knowledge and where it is in the organization. As the main goal of our work was to represent knowledge graphically, we needed a formalism to do so and we analyzed what was being done in process methodologies. One basic way to represent knowledge in organizations is the use of business rules (introduced in Brachman, Levesque, 1985 and popularized by [START_REF] Ross | The Business Rule Book: Classifying, Defining and Modeling Rules[END_REF]. These business rules can be used to represent all types of activity and do not have to be implemented in an information system. Some of these rules are implicit, meaning that they are not written anywhere, they are an integral part of the "business culture". However the basic formalism proposed by [START_REF] Ross | The Business Rule Book: Classifying, Defining and Modeling Rules[END_REF] is not sufficient in all cases to model knowledge. Indeed, a "knowledge unit" [START_REF] Fraser | Knowledge Management Applied to E-government Services: The Use of an Ontology[END_REF] is anything worth storing that may help things to be done better in the future: help, best practices guidelines, examples, stories, lessons learned, troubleshooting advice or training material and business rules cannot model all these types of knowledge. A different approach is described by authors such as [START_REF] Gamper | Combining Ontologies and Terminologies in Information Systems[END_REF] and [START_REF] Gruber | Towards principles for the design of ontologies used for knowledge sharing[END_REF] that use ontologies (explicit specification of a conceptualization, the latter consisting of identified concepts and relationships assumed to exist and to be relevant) in order to model knowledge. We prefer this method as we previously used RDF to build a data-model for e-Government [START_REF] Glassey | Developing a one-stop government data model[END_REF] and found it more powerful and flexible than classical data models such as Entity-Relationship-Model used in ARIS [START_REF] Scheer | ARIS -Modellierungsmethoden, Metamodelle, Anwendungen[END_REF] or than business rules. RDF (Resource Description Framework) is a W3C standard for defining metadata and encoding machine-readable semantics [START_REF] Noy | The Knowledge Model of Protégé-2000: combining interoperability and flexibility[END_REF]. It is based on XML and uses graph theory to represent knowledge. It is also a suitable format for specific domain ontology modeling. However ontologies still cannot represent complex knowledge such as storytelling or human advice. As Samuel Johnson stated in the 18th century: "Knowledge is of two kinds. We know a subject ourselves or we know where we can find information upon it". The goal of the component-based architecture we propose is to model "the information upon knowledge", i.e. to provide metadata on "knowledge units". We identified several attributes that allowed us to do so, beginning with the type of knowledge. [START_REF] Capurro | Skeptical Knowledge Management[END_REF] proposes a knowledge typology by comparing the one defined by [START_REF] Zahn | Nachhaltige Wettbewerbsvorteile durch Wissensmanagement[END_REF] with the classical Aristotelian one. He furthermore builds on existing knowledge typology, such as the one defined by Gilbert Ryle that distinguishes between know-how and know-that. Here we will only summarize the main points of Capurro's knowledge typology:

Note -correct spelling of advises

-Know-how: knowledge about how to make things (technical knowledge) and knowledge acquired through experience and remembrance (empirical knowledge).

-Know-why: logical reasoning (scientific knowledge).

-Know-what: knowledge about the best means to achieve given goals, usually a combination of know-how and know-why (practical knowledge). [START_REF] Capurro | Skeptical Knowledge Management[END_REF] furthermore states that what can be managed is information or explicit knowledge and that implicit knowledge can only be "enabled". In this context, explicit means that it can be clearly observed and expressed (and also digitized), as opposed to implicit knowledge that cannot be directly formulated (skills, experiences, insight, intuition, judgment, etc.) When knowledge is explicit, it can be represented as declarative or procedural knowledge. We are aware that in the domain of cognitive sciences, the distinction between procedural and declarative models is related to the brain memory system (see for example [START_REF] Ullman | A Neurocognitive Perspective on Language: The Declarative/Procedural Model[END_REF], but in this paper we used these terms in a limited sense, as defined in the computer science and AI literature (see for exemple ):

-Declarative knowledge components represent domain knowledge (facts, events, etc.) in terms of concepts and relations.

-Procedural knowledge components describe actions to be taken in order to solve a problem step by step.

For cases where knowledge is implicit and cannot be formalized, we introduced the concept of distribution: knowledge can be individual or collective, and in both cases components identify who has this knowledge or where it can be found. Finally we added a set of metadata (know-where, know-when, know-who, etc.) describing these knowledge-components and making it possible to manage them. In order to represent processes, MIMIK uses standard UML collaboration and sequence diagrams, grouped under the name of interaction diagrams (Idiag), as well as UML activity diagrams. In UML an interaction is the specification of how messages are sent between objects or other instances, and interaction diagrams (sequence or collaboration diagrams) emphasize object interactions. We comply with this definition and use collaboration or sequence diagrams to specifically describe each interaction shown in knowledge-interaction matrices. In [START_REF] Glassey | Comparaison de trois techniques de modélisation de processus: ADONIS, OSSAD et UML[END_REF] we have shown these diagrams are equivalent to those used at the operational level by specialized process modeling techniques such as OSSAD or Adonis. For MIMIK we chose UML as it is a de facto standard, but other types of activity or workflow based diagrams would also be suitable. As we studied process modeling in detail in the aforementioned publication, we will not go into details here, but we will show one example of a collaboration diagram. In UML collaboration and sequence diagrams are isomorphic, meaning that they can be transformed from one to another without loss of information. Sequence diagrams have a temporal focus and collaboration diagrams a structural one. Finally knowledge packets and components (Kcomp) are integrated as objects (or instances of the Kcomp class) in interaction and activity diagrams, whereas the roles shown in collaboration or sequence diagrams are those who were defined in actor-role diagrams. At the operational level, activity diagrams represent processes with a focus on control and information flows. Each process is viewed as transforming as set of inputs, modeled by incoming flows, into outputs or outgoing flows (Lee, Winer, 2003): elementary activities or operations are performed in a chronological manner, swimlanes can be used to show which actors or roles are responsible for elementary activities or operations. Conditions, parallel operation and start/stop points are used to control the execution flow of the elementary activities or operations.

Prototype

The prototype of a knowledge-sharing system (KnowS) is based on RSS (Really Simple Syndication), a family of XML file formats for web syndication. There are two main branches in the RSS family: RSS 1.0 is based on RDF and RSS 2.0 uses an explicit extension mechanism based on XML namespaces. These technical subtleties are not taken into account in this paper, as there are tools that allow compatibility between RSS 1.0 and 2.0. What is relevant is that the RDF-based knowledge components presented in the previous section can be described in RSS. Indeed the XML files (or RSS feeds) provide "items" containing short descriptions of web content together with a link to the full version of the content. In order to access these feeds, users rely on applications called feed readers that check RSS-enabled Web pages and retrieve any updated content that it finds.

Websites featuring RSS feeds include The New York Times, The Wall Street Journal, BBC, news.com, Liberation, etc. RSS is widely implemented in the weblog community in order to share the latest weblog entries. According to a Pew Internet and American Life Project survey [START_REF] Rainie | The State of Blogging, Pew Internet & American Life Project[END_REF], there were 8 millions bloggers in the United States at the beginning of 2005 and 27% of Internet users say they read blogs. Furthermore [START_REF] Gordon | An Open, Scalable and Distributed Platform for Public Discourse[END_REF] showed that RSS can be used for public participation platforms, for example to facilitate public consultation, deliberation, and participation or "engagement" in policy-making processes such as urban planning. For more on RSS we recommend [START_REF] Winer | RSS 2.0 Specification, RSS at Harvard Law[END_REF] or wikipedia.org.

Using blog platforms, end users can publish new knowledge via either a Web interface, a simple email sent to a special address or a dedicated feed publishing client. This requires no specific knowledge (other than being able to send an email, at the most basic level of use), the input text is automatically transformed in an RSS feed by the system. A moderator or domain expert should validate this new content before it is made available to anyone, but it is not required. Furthermore, specific thematic RSS feeds can be defined: users can then choose precisely what knowledge they want to receive. Once new knowledge has been published, it can be used in very flexible ways. Users can simply visit the Web page of the blog, but they can also use Web aggregators such as Bloglines.com, their own email client or a specialized feed-reader that provides more advanced functionalities. However, the Internet and American Life Project survey on blogs [START_REF] Rainie | The State of Blogging, Pew Internet & American Life Project[END_REF] stated that only 5% of Internet users rely on dedicated aggregators to get RSS feeds. RSS aggregators and, to some extend, email clients offer powerful content management capabilities, such as filters to limit access to relevant content: a user can for example subscribe only to feeds that aggregate content on given issues and furthermore filter content. This is very useful to avoid information overload, that is to limit the risk that the users will not read the feeds anymore because they receive to much irrelevant information.

Finally RSS feeds support "enclosures", which allow the addition of any type of multimedia files, similar to an attachment in an email. Thus we added this functionality to our prototype: it can be used to share automatically new documents, files or any piece of digitalized information. With an advanced RSS reader, it becomes possible to check periodically (once a day, every week, etc.) selected feeds and to download relevant documents automatically.

The KnowS prototype comes in three "flavors", there are three technical architectures corresponding to different needs. The first one is based on existing services: Blogger.com, a weblog platform owned by Google, and Feedburner.com, a free post-processing service that allows publishers to enhance their feeds. It allowed us to create a simple proof of concept for what was presented in the previous paragraphs, without any material acquisition or software installation. However Blogger does not support categories for blog entries: we believed that this could prove very useful to organize and personalize knowledge. Indeed by matching categories and interactions such as defined in the knowledge-interaction matrices, we could implement a system corresponding to the knowledge models created with MIMIK. Moreover Blogger's user rights management is very limited. For these reasons, we built a second KnowS prototype (Fig. 12) operating on a dedicated blogging platform: WordPress offers good categories' management tools and 10 levels of users' rights (read, write, edit, validate, publish...) and is available at wordpress.org. We consider that this type of blog publishing platform, powerful and simple to use, would be sufficient in most cases in order to implement a knowledge-sharing system for public organizations. In some complex cases however, a complete content management system supporting RSS would probably be necessary. In order to illustrate this type of technical architecture, we created a third prototype based on Agora, a specialized Web content platform developed on top of the SPIP system (www.spip.net) at the initiative of the French government (www.agora.gouv.fr). To summarize the advantages of this system, it allowed us to integrate categories and keywords, thus to have a finer knowledge organization, and to assign the control over the content of single categories and keywords to given users. With these functionalities we were able to match not only the knowledge-interaction matrices in the system, but also the knowledge-actor matrices. Finally, let us mention that the two more complex versions of KnowS integrate directly most metadata defined for the knowledge components. RSS provides a description for content and integrates various tags (author/source of an RSS element, publication date, language). The KnowS prototype supports several temporal markers (published, updated, validity), it has advanced rights management functions and supports embedded files with MIME type description (format). Moreover it is possible to use permalinks (a type of URL designed to refer to a specific information item and to remain unchanged permanently) to identify the location of a knowledge element and to show relations between these knowledge elements with track-backs (system allowing bloggers to see who has written another entry concerning a given post).

Conclusions

As we mentioned in the introduction, the MIMIK framework is focused on knowledge representation and furthermore provides instruments for knowledge creation and transfer. Throughout the paper we presented MIMIK, its models, and the KnowS prototype. We will now summarize how they relate to the knowledge typology presented in section 3 [START_REF] Capurro | Skeptical Knowledge Management[END_REF]:

-Know-how is represented with process models, concept maps at the strategic level and interaction/activity diagrams at the operational level.

-Know-why is described with knowledge packets at the abstract level and knowledge component at the operational level.

-Know-what is represented by context diagrams at the abstract level and knowledge interaction matrices at the operational level. In section 2 we said that MIMIK method supports knowledge creation and transfer, but we did not explain that claim in detail, as we had not yet described the various MIMIK models. We will briefly recapitulate here how we think they support knowledge transfer types such as defined by [START_REF] Nonaka | The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Evolution[END_REF]:

-Externalization: the eight types of MIMIK diagrams (see Fig. 4) can be used to organize and formalize knowledge, thus to make implicit knowledge explicit.

-Combination: the use of MIMIK diagrams, and particularly knowledge matrices, and of the KnowS knowledge sharing prototype support creation and transfer of new explicit knowledge.

-Internalization: users of the KnowS prototype have facilitated access to relevant knowledge that they will be able to apply in their work.

In this concluding section, we should also state explicitly how MIMIK models are related to the KnowS prototype features:

-KnowS categories are used to describe MIMIK interactions.

-MIMIK activities can be linked to keywords or tags.

-Knowledge components are described with RSS posts and can (if they are digitized) be integrated to RSS feeds as enclosures.

-KnowS users should assign relevant categories to each post in order to reflect the knowledge interaction matrices.

-Categories and keywords can be assigned to KnowS users in order to reflect the knowledge actor matrices.

In the introduction we also discussed several types of knowledge visualization: concept maps can be used to create heuristic sketches (although they are conceptual diagrams); context diagrams, interaction diagrams and knowledge components diagrams are typical conceptual diagrams; knowledge matrices provide basic knowledge maps. MIMIK also provides the advantages of several knowledge representation approaches: description of organizational knowledge at the abstract level with concept maps; an overview of knowledge in context with knowledge-interactions matrices and identification of knowledge possessors with knowledgeactors matrices; a description of the core business of an organization with process models. This combination of knowledge representation categories is formalized in the metamodel of MIMK.

Finally, in the introduction we briefly explained some issues related to knowledge sharing within networks of practice, but we did not investigate the problems of control over knowledge quality and of reciprocity. We plan to do this in future work, by testing the KnowS prototype on a larger scale. At this point we only demonstrated that it was possible to define a technical architecture supporting knowledge creation and transfer. As the MIMIK models at the operational level rely on standards such as UML and RDF, they can be used to develop information systems: code generation in Java or any other programming language, creation of XML files that can be transferred between various applications, etc.

Fig. 2 .

 2 Fig. 2. The objectives of MIMIK are to model the strategic objectives of an organization, to describe processes and knowledge within the organization, to identify actors and roles, and to formalize the interactions between these elements.

Fig. 3 .

 3 Fig. 3. The MIMIK method is based on the life-cycle developed by Nissen et al.[START_REF] Nissen | A Framework for Integrating Knowledge Process and System Design[END_REF]. However we considered that creating and evolving knowledge belonged to the same phase: in most cases organizations do no create knowledge ex-nihilo and then work on its evolution; we would rather consider it as a continuous creation cycle. It is also important to note that the steps identified in MIMIK do not necessarily have to be taken in a predefined order.

Fig. 4 .

 4 Fig. 4. Metamodel showing formal relations between the different types of diagrams proposed by the MIMIK framework.

Fig. 5 .

 5 Fig. 5. Context diagrams are almost exactly the same as use cases in UML, with the addition of the concept of knowledge packet.

Fig. 6

 6 Fig. 6 demonstrates how diagrams are applied to reach given objectives within MIMIK. Concept maps (Cmap) and context diagrams (Cdiag) are used to model the strategic objectives of an organization. Cdiag model knowledge at the abstract level and they also integrate actors, thus showing the context in which knowledge is applied. Interaction diagrams (Idiag) provide descriptions for the processes. Knowledge component diagrams (Kcomp) provide a symbolic representation of knowledge. As their name implies, actors-roles diagrams (ARD) show actors and their roles. Finally the knowledge matrices (Kmax) provide a link between knowledge and processes, and knowledge and actors. Fig. 7 shows where MIMIK diagrams are used within the MIMIK methodology.

Fig. 7 .

 7 Fig. 7. Knowledge-interaction matrix formally linking MIMIK diagrams (represented as knowledge components) to MIMIK methodological steps. KnowS is the prototype of knowledge sharing we developed (see section 4).

Fig. 8 .

 8 Fig. 8. Actors-role diagrams showing administrative units, actors and their roles within the development of MIMIK.

Fig. 9 .

 9 Fig. 9. Knowledge-actor matrix showing who has knowledge of UML, OPRL (Office Process Redesign Language, an evolution of OSSAD), Legal Knowledge System (LKS) and RSS (Real Simple Syndication, based on XML and used for our prototype), and what level of knowledge they have. These were the main approaches (methodologies) that were used as a basis for the development of MIMIK.

Fig. 10 .

 10 Fig. 10. Knowledge component architecture shown as a class diagram, but it can also be formalized in RDF.

Fig. 11 .

 11 Fig. 11. Simplified collaboration diagram showing the process model for developing a research project and publishing it.

Fig. 12 .

 12 Fig. 12. Web interface to the Mimik demo blog.

-

  In addition MIMIK is able to represent who-does-what with actor-role diagrams and the who-knows-what with knowledge actor matrices.

Acknowledgement

This work was supported by a fellowship of the Swiss National Science Foundation (PA001-101413) during my stay at the Fraunhofer FOKUS Institute in Berlin. I also wish to thank Prof. Jean-Loup Chappelet (Swiss Graduate School of Public Administration) and Dr. Thomas Gordon (FOKUS), who helped and inspired me during this project.


Intrinsically motivated exploration as efficient active learning in unknown and unprepared spaces

Pierre-Yves Oudeyer and Adrien Baranès INRIA Bordeaux -Sud-Ouest pierre-yves.oudeyer@inria.fr, adrien.baranes@inria.fr Intrinsic motivations are mechanisms that guide curiosity-driven exploration (Berlyne, 1965). They have been proposed to be crucial for self-organizing developmental trajectories [START_REF] Oudeyer | Intrinsic Motivation Systems for Autonomous Mental Development[END_REF] as well as for guiding the learning of general and reusable skills (Barto et al., 2005). Here, we argue that they can be considered as "active learning" algorithms, and show that some of them also allow for very efficient learning in unprepared sensorimotor spaces, outperforming existing active learning algorithms.

One essential activity of epigenetic robots is to learn forward models of the world, which boils down to learning to predict the consequences of its actions in given contexts. This learning happens as the robot collects learning examples from its experiences. If the process of example collection is disconnected from the learning mechanism, this is called passive learning. In contrast, researchers in machine learning have proposed algorithms allowing the machine to choose and make experiments that maximize the expected information gain of the associated learning example [START_REF] Cohn | Active learning with statistical models[END_REF], which is called "active learning". This has been shown to dramatically decrease the number of required learning examples in order to reach a given performance in data mining experiments [START_REF] Hasenjager | Active Learning in Neural Networks[END_REF], which is essential for a robot since physical action takes time. The typical active learning heuristics consist in focusing the exploration in zones where unpredictability or uncertainty of the current internal model is maximal. In the following, we will implement a version of this heuristics which we will denote "MAX".

Unfortunately, it is not difficult to see that it will fail completely in unprepared robot sensorimotor spaces. Indeed, the spaces that epigenetic robots have to explore are typically composed of unlearnable subspaces, such as for example the relation between its joints values and the motion of unrelated objects that might be visually perceived. Classic active learning heuristics will push the robot to concentrate on these unlearnable zones, which is obviously undesirable.

Based on psychological theories proposing that exploration is focused on zones of optimal intermediate difficulty or novelty [START_REF] Berlyne | Conflict, Arousal, and Curiosity[END_REF], intrinsic motivation mechanisms have been proposed, pushing robots to focus on zones of maximal learning progress (see [START_REF] Oudeyer | Intrinsic Motivation Systems for Autonomous Mental Development[END_REF] for a review). As exploration is here closely coupled with learning, this can be considered as active learning. Through a number of systematic experiments on artificially generated mappings that include unlearnable and inhomogeneous zones, we argue that this kind of intrinsically motivated exploration actually permits organized and very efficient learning, vastly outperforming standard active learning methods. In the presented system, "interesting" experiments are defined as those where the predictions improve maximally fast, hence the term "learning progress". In order to compute and predict learning progress (this is in fact a meta-prediction), [START_REF] Oudeyer | Intrinsic Motivation Systems for Autonomous Mental Development[END_REF] introduced the concept of "regions" which are subspaces of the sensorimotor spaces, recursively and progressively defined, to each of which is attached a global interest value, which is the inverse of the global mean prediction error derivative in the past in the region. The algorithm starts from a single large region (the whole space), which it progressively subdivides in such a way that the dissimilarity of each sub-region in terms of learning progress is maximal. Here is an illustration about this recursive parsing system, over time:

Based on this partitioning and associated evaluation of interest, the following exploration policy is used when a new sensorimotor experiment has to be chosen:

 (Meta-exploitation) With a probability 0.7, a sensorimotor experiment is uniformely randomly chosen in the region which has the highest associated learning progress;  (Meta-exploration) With a probability 0.3, then: o With a probability 0.5, choose uniformly randomly an experiment; o With a probability 0.5, choose an experiment using the MAX heuristics;

The meta-exploration part is indeed necessary to allow the system to discover niches of learning progress: any region needs to be explored a little bit first in order to let the system know how much it is interesting or not.

We now compare the performance of this system, denoted IAC for Intelligent Adaptive Curiosity, when viewed as an active learning algorithm and compared to the MAX heuristics and to the naïve RANDOM heuristics (which consists in choosing uniformly randomly experiments). An experiment was conducted in an abstract space characterized by properties typical of the unprepared spaces that might be encountered by a developmental robot: simple zones, more complex zones, and unlearnable zones. This space is a 𝑅 1 → 𝑅 1 sensorimotor space which incorporates areas of different difficulty:

 The interval [0.25, 0.5] ∪ [0.9, 1] contains an unlearnable situation (pure noise)  [0.5, 0.8] is an increasing difficulty area  [0.15, 0.17] an intermediate complexity part  The rest is easy to learn for the algorithm The next figure (Graph a) shows the evolution of exploration focus of IAC over time, when the system is driven by intrinsic motivation. We see that it avoids unlearnable zones, yet focusing on the difficult parts of the learnable zones:

Graph (a): Exploration focus over time

We can notice, watching the previous graph in the startup phase, that the algorithm is interested in the noisy part [0.25, 0.5], but only during a brief period; then, it changes of area and decide to focus on the first complex one, [0.15, 0.17]. Finally, it focuses on the zone within [0.7, 0.8], beginning in its most simple sub-part, and progressively shifting to its more difficult part.

Thereby, we see that the system is not trapped in unlearnable zones, as opposed to traditional active learning methods, but still focuses on zones where effort is most needed, as for random exploration.

In graph (b), we compare the evolution of performance in generalization inside learnable zones using the error rate, among IAC, MAX and RANDOM. To remain fair, the MAX heuristics was implemented with the same 0.7 meta-exploitation/0.3 meta-exploration global scheme than IAC (the difference is thus in the metaexploitation part).

Graph (b): Evolution of performances in generalization

We obtain better performances in learning using the IAC algorithm. We observe that over time, error rate is always inferior to others. This shows that building an active learning system based on intrinsic motivation and developmental concepts coming from psychology, one can obtain better learning performances in unprepared sensorimotor spaces than traditional active learning techniques.

Figure 1 :

 1 Figure 1: The abstract sensorimotor space, an input/output mapping to be learnt


Olivier Glassey

A FRAMEWORK TO ANALYZE DATA GOVERNANCE OF SWISS POPULATION REGISTERS

Keywords: governance, data, identity, population registers, modelling, framework

In June 2006 the Swiss Parliament adopted a new law on population registers' harmonization in order to simplify statistical data collection and data exchange from around 4'000 decentralized registers. Besides there are more than 2'000 administrative services delivered to Swiss citizens and businesses, of which hundreds could potentially use data from population registers. The law is rather vague about the implementation of this harmonization and even though many projects are currently being undertaken in this domain, most of them are quite technical. We believe there is a need for analysis tools and therefore in this paper we propose a conceptual framework to analyse data governance of these populations registers, with a strong focus on information requirements and identity management. In order to develop this framework we built on existing approaches to define its building blocks: data consumers, data sources, identity in a given context, requirements, and data sets.

Introduction

In June 2006 the Swiss Parliament adopted a new law on population registers' harmonization in order to simplify statistical data collection and data exchange. Indeed public registers are very fragmented in Switzerland. Until 2004 vital records (births, deaths, weddings, and adoptions) were held on paper registers by 1'750 Cantonal offices throughout Switzerland. Since 2004 the Federal Department of Justice and Police provides Cantons with a centralized database called Infostar. Furthermore there are around 2'500 resident registers (localisation of citizens), generally maintained by the 2'700 Swiss communes with some exceptions such as Geneva where they are operated at the cantonal level. In the Canton of Bern alone, there are 396 communes that use 26 different software solutions to manage residents' data. In addition to these "stricto sensu" population registers, there are several other registers that store data on citizens: fiscal register, foreigners' register, building and housing register, and so on. There are furthermore several databases that are not directly considered as registers but that are connected to these registers and store records on military, scholarships, old age and survivors' insurance, etc. A Federal Census will take place in 2010 and it is planned that data should be provided by these various population registers. Previous censuses were based on questionnaires sent to Swiss households and interviews. In order to collect and aggregate data automatically, a personal identification number had to be created. A first project called EPID (Unique Federal Personal ID) was rejected, mainly for data protection issues. It was then planned to have six sector ID numbers (population, social security, tax, defence, justice, statistics) in order to insulate data and to protect citizen's privacy. However this has not come to realization yet, and in order to implement the harmonization law, Switzerland has chosen to use the existing old-age and survivors' insurance number. However this number was not unique and not anonymous, therefore a new one is being introduced, starting July 2008.

Theoretical Framework

Data Governance

Although there is currently no consensus on the definition of governance, there are two domains that are well defined and widely accepted: political governance (whether global, local or territorial) and corporate governance. Both share a common approach based on decision processes and stakeholders' participation (shareholders, executives, political leaders, citizens, interest groups or any other organisation). This paper is discussing the governance of population registers, so it is clearly not corporate governance we are studying. What we want to survey is the elaboration of rules and decision processes that govern the management of public registers' data. Before 2004 there was no clear need for such a governance approach, as with more than 4'000 disconnected or paper-based registers it was not such a big issue. However, information and communication technologies (ICTs) are currently transforming these processes and we want to analyse how they are impacting our society, under the umbrella of what has been called eGovernance or digital governance. [START_REF] Ba Aubert | Towards the Measurement of Process Integration[END_REF] believe that it is necessary to establish reference principles in order to measure these changes and their impacts. They mention accessibility, transparency and accountability. We agree with them but we thought some additional dimensions were needed. In its policy paper on governance for sustainable human development, [START_REF]Governance for Sustainable Human Development[END_REF] defines governance as the exercise of economic, political and administrative authority to manage a country's affairs at all levels and proposes the following characteristics for governance: Participation, Rule of law, Transparency, Responsiveness, Consensus orientation, Equity, Effectiveness and efficiency, Accountability, Strategic vision.

At this point and before going further on into our data governance model, we think it is useful to provide a quick reference model on eGovernment and eGovernance and we will summarize their definitions by [START_REF] Tb Riley | E-Governance: Examining the Difference in a Changing Public Sector Climate, The Commonwealth Secretariat and Government Telecommunications and Information Services[END_REF]:  eGovernment covers three main areas: electronic services provision, electronic workflow and electronic voting (in terms of infrastructure, security and trust).  eGovernance consists of electronic consultation (public administrations, citizens, businesses, interest groups, etc. give their input during the rule-creation process) and electronic participation (the afore-mentioned actors have not only the ability to give their opinion during decision processes but also to initiate them by using ICTs); the "Holy Grail" of eGovernance is a networked society where actors can follow decision processes (accessibility) and provide feedback and control (transparency) in order to make officials and elected responsible (accountability).

So far we have defined the general dimensions of governance and we have explained the particularities of eGovernance or digital governance, but we still need to define a specific set of requirements in terms of data governance. To that effect we will use the information criteria of CoBIT [START_REF][END_REF]. This framework for IT governance consists of a set of good practices ensuring that IT is aligned with the business and enables business processes. It also provides resources for risk and performance management. The data requirements (or information criteria) defined by CoBIT are:

 Effectiveness: relevant, correct, consistent, usable and timely information.

 Efficiency: provision of information through the optimal use of resources.

 Confidentiality: protection of sensitive information from unauthorised disclosure.

 Integrity: accuracy, validity and completeness of information.

 Availability: information is available when required.

 Compliance: information use is complying with the laws, regulations and internal policies.  Reliability: information can be trusted.

Identity Management

In section 2.1 we defined a set of requirements in terms of governance and data governance; we believe it is necessary to integrate them in our framework to study population registers' harmonization, but we also think that this is not sufficient and we argue that an identity layer must also be added to our framework. Indeed, citizens have multiple identities when dealing with different parts of the public sector: as an individual, as a family, as a taxpayer, as a soldier, as a patient, possibly even as a prisoner, and so on. [START_REF] Lips | Identity Management as Public Innovation: Looking Beyond ID Cards and Authentication systems[END_REF] write that personal identification resides at the heart of many forms of government service delivery and that historically and archetypically such identification was based on manual form filling and paper-based authentication processes (the citizen shows his identity card or passport to an official). For each administrative procedure a paper form had to be filled and it was then stored (and most of the time forgotten). Now, with registers being digitalized and used in order to provide the information required for an administrative procedure, these identification mechanisms are not sufficient anymore. We will cite to Canton of Geneva eGovernment strategy [START_REF] Genève | Projet de loi ouvrant un crédit d'investissement de 30 850 000 F pour le développement de l'administration en ligne[END_REF] to illustrate this: it is stated that no Cantonal office should ask citizens for information that the State of Geneva already has somewhere. However this paper is not about a technical approach of eIdentity management (user name, password, personal identification numbers, smart cards, PKI, fingerprint readers, mobile phone, and so on). We are interested in the legal-normative approach of identity management, answering to questions such as how does the law on public registers' harmonization fit together with data protection legislation? Furthermore the Swiss Confederation and many Cantons have a law on transparency stating that all public documents and information must be publicly available, with exceptions for national security, trade secrets and citizen's privacy. Our goal is not to provide legal answers to these questions; it is rather to develop a framework that allows its users to describe requirements in terms of data, processes and identities. [START_REF] Cameron | The Laws of Identity[END_REF] defines digital identity as a set of claims made by one digital subject about itself of another digital subject, with a digital subject being a person or a thing and a claim being an assertion of the truth of something, e.g. "I am Paul and I am over 18", "I am Mary and I am married to John". [START_REF] Cameron | The Laws of Identity[END_REF] furthermore defines seven laws of identity that are now widely used:

 User control and consent: digital ID systems must only reveal information identifying a user with the user's consent.  Minimal disclosure for a constrained use: the solution which discloses the least amount of identifying information and best limits its use is the most stable long term solution.

 Justifiable parties: digital ID systems must be designed so that the disclosure of identifying information is limited to parties having a necessary and justifiable place in a given identity relationship.  Directed identity: a universal ID system must support both "omnidirectional" identifiers for use by public entities and "unidirectional" identifiers for private entities, thus facilitating discovery while preventing unnecessary release of correlation handles.  Pluralism of operators: a universal ID system must channel and enable the interworking of multiple identity technologies run by multiple identity providers.  Human integration: the universal ID metasystem must define the human user as a component integrated through protected and unambiguous human-machine communications.  Consistent experience across borders: a unifying ID metasystem must guarantee its users a simple, consistent experience while enabling separation of contexts through multiple operators and technologies.

According to his own words, [START_REF] Cameron | The Laws of Identity[END_REF] defined these laws with the goal of "giving Internet users a deep sense of safety, privacy and certainty about who they are relating to in cyberspace". The context of population registers managed by the public sector is different, but these laws are still very relevant, even if they need to be adapted in some cases.

To conclude this section on identity management we will mention several other important issues: authenticity, trust, accountability, privacy, usability and data life-cycle [START_REF] Casassa Mont | Identity Management: a Key e-Business Enabler[END_REF], locality (identities are situated in particular contexts and one may have different or overlapping identities attached to given contexts), reciprocity, mutual understanding principles [START_REF] Roussos | Mobile Identity Management: An Enacted View[END_REF]. We will not deal with all of them neither integrate all the laws of identities in our framework (details will be given in section 3), but we think it was important to at least mention them to give readers a broader view on the topic.

Modelling Tools

Our goal is to use a conceptual framework to analyse governance processes of population registers' data, i.e. a set of methods, techniques and tools allowing us to model stakeholders and processes, and to formalise relationships between actors, processes and data. In previous work we developed a framework to model and share knowledge within large organizations or public administrations [START_REF] Glassey | Method and Instruments for Modeling Integrated Knowledge[END_REF]. Called MIMIK (Method and Instruments for Modelling Integrated Knowledge), it provides a method (a series of steps taken to reach a certain objective) and instruments in the sense of concrete or abstract tools intended to assist users in fulfilling a given objective. These instruments consist mainly of abstract models that represent reality symbolically, in terms of concepts and relationships, and that are implemented as diagrams, i.e. simplified and structured visual representations of concepts and relations. The starting point of MIMIK was the model theory approach developed by [START_REF] Wyssusek | Business Process Modeling as an Element of Knowledge Management -A Model Theory Approach[END_REF] who aimed at integrating process modelling and knowledge management, as well as the work of [START_REF] Mentzas | Modelling business processes with workflow systems: an evaluation of alternative approaches[END_REF] on process modelling and workflow models. We later analyzed several modelling techniques with very different backgrounds in order to provide a practical approach: commercial methods that are tightly integrated with a modelling environment, such as ARIS Toolset, MEGA Process / MEGA Designer or ADONIS; open and standard modelling methods such as OSSAD or OPEN; methods for knowledge-based engineering such as MOKA or CommonKADS; language and notation for object-oriented software-intensive systems such as UML.

MIMIK consists of 8 types of diagrams, most of them being inspired or directly taken from existing modelling techniques. Concept maps are the top-level diagrams and show the strategic goals of an organization in terms of functions or processes and their relationships.

Context diagrams are almost exactly the same as use cases in UML, with the addition of the concept of knowledge packet, i.e. an abstract representation of a set of knowledge components. These components encapsulate documents, databases, files, implicit knowledge, etc. Knowledge packets show at the abstract level what type of knowledge is necessary in order to complete a process and which knowledge is relevant in a given context. MIMIK also provides two knowledge matrices, in order to show formal links between knowledge and processes (Knowledge-interaction matrix) and knowledge and actors (Knowledge-actor matrix). Actor-role diagrams can be classical organizational charts, graphical actors-roles diagrams, or matrices that formally link actors and roles in cases where the organization is too complex to be shown graphically in an intelligible way. Finally MIMIK uses RDF schemas to represent know-why, know-what and know-how, as well as UML interaction and activity diagrams to describe processes and activities. We decided to adapt this framework for our needs in terms of data governance, notably by integrating the requirements defined in section 2.1 and 2.2.

Building a Conceptual Model

We adapted the MIMIK framework by adding the following concepts or building blocks to model identities and data used when accessing population registers:

 Data consumer: actor requiring data from a register.

 Data source: register or database containing information on citizens.

 Identity: digital identity of the citizen in a given context.

 Requirement: expression of consumer's needs in terms of data on citizens.

 Data set: digital data on citizens provided by a data source.

 Knowledge component: meta-data encapsulating the content of context diagrams (Fig. 1) and formalizing the context of data exchange with the above-mentioned building blocks.

analysis Use cases

Data Consumer

Requirement

Identity

Data Source From Access ID

Figure 1: Generic Context Diagram

In the following sections we describe our building blocks; however this is a generic representation of reality, as Cantons might have different operational modes.

Data Consumers

Data consumers are the stakeholders that have a potential access to population registers; apart from some exceptions all of them are public or para-public offices, at various administrative levels and functional positions. Fig. 2 shows the main ones but is not exhaustive. Let us mention that not all actors listed here currently use that access, but they could potentially do it once registers are harmonized and publish data. If we take the example of public kindergartens, where parents pay a fee that is proportional to their income, citizens bring a paper copy of their taxation decision and must justify their residence place. Although not all kindergartens have the same requirements, one could imagine that they could have a direct access to the fiscal register and the resident register in order to calculate fees.

Data Sources

As mentioned in the introduction there are official population registers as well as many other sources storing information on citizens. We list nine of them as potential data sources (Fig. 3), meaning that not all of them might currently be used as such, and even that some of them might never be opened to external access (e.g. military data).

analysis Data Sources

Vital Records Resident Register Tax Register

Statistics

Social Security Military

Scholarships

Foreigners

Buildings and Housings

Figure 3: Data Sources

Digital Identities

Citizens have many roles in regard to public administrations and to the public and para-public sector: they pay taxes, they elect their representatives, they are required to take a basic health insurance, and they might benefit from social help or even go to prison, and so on. Once again the purpose of our identity model (Fig. 4) is not to be exhaustive or to be completely accurate, it is rather to show the variety of situations in which a citizen might find himself and the vast amounts of personal data that could be stored or used during these interactions.

Requirements

In Switzerland there are more than 2'000 administrative services delivered to citizens and businesses, from fishing and hunting licences to insurance subsidies or work permits. Of course not all of them rely on the use of data from population registers, but one can estimate than dozens if not hundreds of them use some kind of personal data. In order to describe them and to identify needs and requirements, we suggest the utilization of diagrams inspired by UML use cases. Fig. 5 shows an example where the military affairs department accesses two different registers in order to calculate the military tax. Indeed all Swiss male citizens are required to serve 300 days in the army and those who do not must pay a tax. This annual tax is calculated on the basis of the numbers of days that a citizen spend in the army (from 0 to 300), on the numbers of days he should have done at a given age and on his income. In order to do so it is necessary to match one's identity as a citizen, a soldier and a tax-payer.

Fig. 6 shows another example that is interesting in terms of identity management. Students have the right to request a grant for their studies under given conditions, such as the income of their parents, their age, etc. Here the notion of identity claim is central, as it is necessary to link a student to his/her parents, with some complex implications (adopted children, divorced parents, and so on).

Data Sets and Knowledge Components

Fig. 7 shows simplified data sets provided by data sources according to contexts and for given identities. Knowledge components are described in RDF (Resource Description Framework), a W3C standard for metadata description and machine-readable semantics in XML. Data components integrate information on the context (data consumers and sources), on identities as well as the data sets themselves. They also contain elements of data qualification regarding security and confidentiality (e.g. high/medium/low security requirements; confidential, restricted or public data).

Figure 2 :

 2 Figure 2: Data Consumers

Figure 4 :

 4 Figure 4: Digital Identities

Figure 6 :

 6 Figure 5: Military Tax

Figure 7 :

 7 Figure 7: Selected Data Sets

Civ il Serv ice Property Manager Insurance Pension Fund Old Age, Surv iv ors and Disability Insurance

	analysis Data Consumers
	Canton	Commune	Federal Office	Courts	Police	Kindergarten
	Bankruptcy &	Hospital	Public Welfare		Military Affairs	School
	Nonpayment Claims

Swiss Public Administration Network (SPAN) and Swiss Graduate School of Public Administration (IDHEAP), Route de la Maladière

21, 1022 Lausanne, Switzerland, olivier.glassey@idheap.unil.ch

Future Work and Conclusions

We are currently in discussion with various stakeholders (Cantons, communes, Swiss Federal Statistics Office, and other research centres) in order to launch a broad study on population registers, as well as on trade and company registers. We will use this framework to analyse needs and requirements of these various stakeholders in terms of data exchange and of registers' harmonization. We believe this project will offer a very interesting field of experimentation and validation for the approach described in this paper.