Knowledge Management in Research Projects: An Approach Through the Management of Scientific Concepts

KNOWLEDGE MANAGEMENT IN RESEARCH PROJECTS: AN APPROACH THROUGH THE MANAGEMENT OF SCIENTIFIC CONCEPTS Astrid JAIME1 and Mickaël GARDONI1 and Joël MOSCA1 and Dominique VINCK2 Abstract. Innovation and thus the production of knowledge becomes a factor of competitiveness. The research activities aim, in particular, the production of new knowledge. Researchers could profit from approaches and methods such as quality management and knowledge management. In this communication, we study the approaches used while implementing a quality management system within various research organizations. We are particularly interested in the existing possibilities for implementing knowledge management at research organizations. Our assumption is that quality management could be complemented by knowledge management as a way of improving the process followed when realizing research activities. For this reason, we propose an approach integrating quality management and knowledge management as a way to support the scientific activity. Additionally, we analyze the realization of research projects and propose an approach based on the capitalization of the bibliographical work done by researchers. We propose to focus on supporting the concepts management as a way to assist the knowledge production process. We finish by giving the basis of the definition of a software tool that should help to accomplish this activity. 1 INTRODUCTION The research activity implies managing information and knowledge. From these resources, new knowledge is produced, to become, itself, the resource of new researches. In France, reflections on the possibility of applying the quality concepts and methodologies to the research process were carried out and documented in "Experimental Guide for Quality in Research" written by the French Work Group "Quality in Research" [8]. This document was taken by the AFNOR as the base of the Documentation Booklet FD X 50 - 550 “Quality Management in Research - General principles and recommendations" [2], in which quality management is proposed as a possibility to face the multiple issues of the research activities. Moreover, during the last years, some research organizations have been interested in quality management as a mean to improve their activities. Indeed, the research activity requires rigueur in the knowledge production process. However, it presents specificities in terms of goals, resources, practices and organization which make this activity very different from the industrial activity, where quality management has been traditionally used. Thus, the introduction of quality management, step by step, as used by the industry is not possible in the scientific environment. One AFNOR document recommends the utilization of quality management by the scientific actors. In fact, research organizations do set up quality management systems within their organizations. 1 2 GILCO Laboratory, National Polytechnic Institute of Grenoble CRISTO Laboratory, University Pierre Mendes France Therefore, we have started a research process that aims at clarifying the problems that the research organizations face when implementing a quality management system. We wonder in particular about the role that quality management could play in the transmission of knowledge. Our objective is concretely to check the hypothesis according to which quality management can be used to support the knowledge production process, by providing methods that improve the total performances of the research processes. In the first part, we describe the observed functioning of a few research units trying to implement a quality management system. In the second part, we will look into some knowledge management aspects at these research units. In the third part, we propose a representation of a methodology that incorporates quality management and knowledge management as a way of supporting the knowledge production process. Finally, we present an approach for addressing knowledge management in research projects and we present the basis for the definition of a tool that aims at supporting this approach. 2 QUALITY MANAGEMENT IN THE CONTEXT OF RESEARCH The AFNOR [2] proposes, to the research organizations wishing to engage in quality management, to establish practices to maintain the quality of the research activity during all the scientific production process. It leaves the precise definition of these practices to each research organization. For that reason, we have studied the various approaches used by some research entities setting up a quality management system. We paid special attention to the management of information (data, documents, etc), considering the support it offers to the capitalization of knowledge. This work has been completed in several phases: ● Collection of information (direct observations and interviews) on the current operation of a research laboratory, over a four months period. ● Interviews with the people responsible for quality management in seven research laboratories where formal efforts of introduction of this methodology are being done. ● Follow-up of the implementation process of quality management at a research laboratory. This work is undertaken via the participation in work meetings (this work is still in process. It is not included in this communication). Hereafter, we will present the results of this field work. 2.1 The reality observed at a laboratory The observation has allowed us to note that several characteristics of the research activity make difficult its management: the diversity of activities within a laboratory, the great quantity of records (digital reports and files in particular) to manage, the freedom granted to the researchers for the register or the traceability of their production, the multiplicity of working methods, the great turn-over of researchers, the multiplicity of activities that must be developed in parallel, with various time delays, and that should be coordinated to lead to valid results, the difficulty to establish, from the beginning of a project, the precise characteristics of the product of research (which could be a physical product or a conceptual product), etc. which explains the interest of having support practices during the research process, of capitalizing the history of a project, of setting up procedures for the validation of results, etc. All these characteristics make difficult the knowledge management and the definition of a standardized instrumentation. Therefore, the question that arises is how to capitalize the knowledge produced, and how to rationalize and instrument the activity. 2.2 Some experiences of implementation of quality management We have carried out several interviews at seven research entities 3 attached to the CNRS , already engaged in quality management. These organizations combine activities of industrial research and basic research, except a unit that works for the research laboratories as supplier of special equipments required in research projects. However, we noted that nowadays, quality management is primarily applied to the administrative and/or the technical activities and very little to the basic research activities. The implementations observed are inspired on the ISO 9001 standard [1] and the result is often the establishment of information systems, which aim at facilitating the realization of the repetitive processes. We have observed that the type of activity carried out causes divergences in the way quality systems are established. Thus, two of the organizations followed a traditional process for the establishment of a quality system according to the standard ISO 9001. Though, those working mainly in basic research were challenged by the way in which quality management could be applied to research. The field work carried out has been of key importance to support our research. For this reason, we will continue this observation and interviewing work all along our project. We will now relate our observations to some major elements of the theory of knowledge management. 3 KNOWLEDGE MANAGEMENT AT RESEARCH ORGANIZATIONS Our interest is centered on quality management at research organizations as establishments devoted to the production of knowledge. This activity, according to the results of researches in sociology of sciences and our own observations, is usually developed in the form of more or less structured research projects4. Moreover, knowing that the constitution of a phenomenon, the establishment of a fact or of a statement is closely associated to a history of contingencies of the research process, the documentation issue becomes a concern for the researchers themselves when they try to reconstruct a former stage or to take in hand a project engaged by a colleague. That is why it is important to study the issues of knowledge management while being based on the management of information and to try to find ways of improvement. Within this framework, we will present, hereafter, some elements that show the way in which knowledge management is present at the surveyed research organizations. 3.1 The current knowledge management practices at research organizations Grundstein [9] says that there is a “logic of capitalization that proceeds according to two axes: ● an axis oriented to the management of knowledge (management of technical data, document management, management of configurations); ● an axis oriented to the formalization of know-how (acquisition/representation of the fields of knowledge and of the reasoning relating to this knowledge).” The quality management implementation at the research organizations observed until this day is oriented towards the first axis (management of knowledge). It has started with an objective of taking into account the organizational aspects, mainly through the writing out of documents (operational procedures and documents). For the management of these documents, this methodology has been translated into information processing systems, often an Intranet that sometimes manages other documents of the organism. This verifies the situation described by Gandon [6] about the use of Intranets and the Web as means to manage documentation. However, the information processing systems that we have observed do not seek “the management and the circulation of distributed knowledge” as projects like CoMMA (see [6]) aim. For the surveyed laboratories, the approach selected is to facilitate the realization of the activities by providing a tool that makes it possible to find documents or information and to organize those produced. In general, the documents resulting from the research process are not managed by these systems. Moreover, the second axis (the formalization of know-how) has not been yet addressed for the research activity. Within this framework, we believe that there is an important place for the utilization of knowledge capitalization methodologies. 3.2 Why quality management without knowledge management? We have seen that the quality management implementation at the surveyed organizations does not directly address the management of the knowledge resulting from the research activity. The origin of this situation seems to be double: On one hand, there exists a known methodology to address documentary organizational management. In other words, traditionally, quality management has been used for this kind of management, which is easily adaptable to the organizational aspects of laboratories. Conversely, a defined methodology to 3 National Centre of Scientific Research of France Vinck, [14] wrote: "the activities at the laboratory are structured in projects. The project is a sequential unit of which the completion is the writing of a research report or of a publication. The project sees to be the unity of organisation that allows affecting tasks to the members of the laboratory, to order supplies, to prepare equipment, to propose phenomena 4 to be studied and to orient the library searches… There is a discrepancy between formal descriptions of the procedures, methods and work schemes and the effective realization of the activities. […] The methods and research protocols do not account for the effective sequence of the activities." (p. 154). make knowledge management in scientific organizations does not exist to apply quality management to scientific research activities. On the other hand, the results obtained by document management are easily perceived, in the short run, by the personnel, who justify the utilization of the developed systems. Nevertheless, it is observed that the lack of real experiences of implementation of quality management complemented by knowledge management is a factor that affects the eventual implementations. There is an effort of formalization and capitalization of the organizational memory of the support activities, which is not accompanied by a similar effort for the scientific activities. However, we believe that in research activities, there are elements that could be formalized and handled, keeping the flexibility of the research process. The objective would be that the generated knowledge could be located, preserved, developed and brought up to date (see [9]) for the benefit of the research activity. Figure 1. Implementation organizations 3.3 5.1 The difficulties of knowledge capitalization Mahé [11] shows the "barriers that oppose to the re-use of a knowledge created on a precedent project on a project in progress". These barriers are mainly the personnel turn-over (either because people leave, or because the person who holds knowledge is not the one who is responsible for the project) and the lack of information (either because this one has not been produced or formalized, or because it has not been capitalized). At research organisms, these same difficulties exist and are increased partly because they relate to knowledge within the organism and also to knowledge held by the scientific network of the field to which the organism belongs. For that reason, we intend to use methodologies that would make possible to partially overcome these difficulties, by taking into account the characteristics of research. 4 PROPOSAL OF IMPLEMENTATION OF QUALITY MANAGEMENT AT RESEARCH ORGANIZATIONS Our proposal is to use quality management to introduce the principles of knowledge management, making it possible to capitalize the knowledge produced when realizing research projects. Our objective is to seek the improvement of the knowledge production process. Thus, by inspiring on the recommendations given by the AFNOR (see [2]), we propose a representation of the method as shown in Figure 1. This diagram emphasizes the importance of documentation throughout research process and thus of its management to support the process of knowledge creation. The subjacent idea is that there is knowledge produced throughout the research process, so it could be profitable to exploit this richness. 5 AN APPROACH FOR ADDRESSING THE IMPLEMENTATION OF KNOWLEDGE MANAGEMENT AT RESEARCH ORGANIZATIONS We are interested in finding ways to profit from the knowledge produced throughout the realization of research projects. However, Wunram [17] indicates that "the approaches that start with the goal of capturing all the knowledge of the employees are predetermined to fail". It is thus necessary to define the knowledge that can be more beneficial to research activities. Pragmatism Documentation of objectives 1. Definition of the Objectif Documentation of results 3. Valorization of Results 2. Realization of the Research Integration Pedago gy Pedagogy Documentation of the evolution Process Form alization Knowledge Managem ent Knowl edge of quality management at research Which knowledge to capitalize? Given our intention to improve the knowledge production process, we carried out an analysis of the research projects activities. Moreover, since “knowledge is based on the data and the information” [17], we analyzed the information used and generated during the realization of this kind of projects. Thus, we have been able to identify the most critical aspects in terms of unexploited possibilities of knowledge capitalization. With this aim, we have represented the research activities in the form of a matrix which crosses two points of view: activities carried out, and information used and generated5. From this matrix, we extracted the aspects where the principles of knowledge management could be used to ease the realization of the research activity by improving the management of information. These aspects were selected by taking into account the practices currently used in research, where the activity leans very strongly on the capitalization of the final results. Though, at least for the observed laboratories, it is common to grant great freedom to the researchers for the management of the recordings resulting from the realization of the research projects. Thus, the result of this study is that there is a very important potential of capitalization of the knowledge produced during the realization of research projects. By reusing the representation of quality management (Figure 1), we note that knowledge, resulting from research projects, is already capitalized thanks to the existing valorization mechanisms existing in scientific research. However, a great amount of the knowledge produced during the research process remains barely capitalized. In this context, the concept of artifact seems useful to us. Groleau [7] presents the definition given by Hutchins who says that “artifacts are repositories of knowledge constructed in durable material form”. Michaux and Rowe [13] add that “Two elements seem important to retain in the design of artifacts. On one hand, distributed cognition considers that artifacts contain a part of the knowledge necessary to conclude a daily action with effectiveness: the other part being held in a complementary way by men... On the other hand, the intervention mode of these artifacts is the representation that they are able to convey. Indeed, the artifacts are often similar to objects (speed chart, paper-board, indicator on a data-processing screen or a measuring apparatus…).” In the research context, the daily action, which we are interested in, is related to research projects. Thus, we observed that within 5 The matrix mentioned is not included in this paper, because its size makes it impossible to show it in a legible way. the realization of research projects there is a great quantity of artifacts produced. Given that those convey knowledge, we will focus on artifacts capitalization, as a means of capitalizing at least part of the knowledge resulting from the realization of research projects. It is important to precise that for us, an artifact is an element having a material form (or a virtual form, as it can exist only in a computer system) which can convey a part of the knowledge held by its author, provided that its receiver knows the context in which it was conceived and has the necessary knowledge for its interpretation. In this sense, artifacts are ways of translating a part of their authors’ knowledge in order to give a representation that can be stored and potentially, shared and re-used. Another aspect to note is that this decision expresses our intention to follow the principle of pragmatism recommended by the AFNOR, (see [2]) and by Weber (see [15]). The latter indicates us that "a strong argument for a pragmatic knowledge management is the fact that anyway we cannot control all knowledge". The question is now: how to capitalize these artifacts like means to facilitate the realization of other research projects? In order to try to find ways for responding to this question, we started by analyzing the means by which artifacts are produced during the realization of a research project. This analysis is shown in the next paragraphs. Phénomène Déciso i n de réail ser unproe jt Ab Ac Productionde connaissances (faiteàtraversdes proe j tsderecherche) ConnaissancesAa existantes Ad Ae Nouvel es con naissances : Publ ci atio ns, rapports, etc. Art efacts: Logiciesl développés, doc. état de a ’l rt, donnéesde a l bo., etc. Documentati onde a l réal si ation du projet: com ptes-r endus, pa l nni ng,etc. Système: Laboratori edee r cherche A: ProcessusdeRecherche Point devue: Connaissancesetinformationsutilisées etgénérées. Decision of realizing a project Ab 1 . Project Definition Existing Knowledge Aa . Follow-up and 6 Validation . . . A0h . A0h A0h . A0g/A33f A0a . . Art state Definition . . A 2d . A 0b . 7 A0f Valorization A 7f . A 0d A 0c / A 0e A0c A0 : Research Project Data gathering / A2f A2g A2h Data treatment . 4 Ad 5 Results 5 A0e Ae New knowledge: Publications, reports, etc. - Ac Analysis – Propositions . A 43f A0j A0g A0i A0h 3 2 Déci sio n e d réalsi er unproe jt Connais sance s exis tantes A0g Défi nirl e1 phénomène àétude ir 1a A Déf n i ri l es domaines, 2 mét ho des, etc . ( u qi A1 b peuve nt aider àétudier e l p hénomèn e) Définir obe j ctives,3 personne ,l budget, etc . Doc umentd’ téa t de l’ rat r( a pport) A2e Défn i ti o i ne d mé to hdo lo ge is et o c ncepts su s ce pti b le s d’êtr etuil sés.A2f 2b A 1 Défi init ondu 1c A 1e A Proj te–A1g Obtenti on de docum ents Lectureet extraction2 deconceptsj ugés util es A2a Défi niti on 2 Choix d e 1 A3 i str uments a d’ n m éthodologie à utli si er A1 d Défi nir 4 di sponb i i til é deressources 2c A A 2f Rédacto in synthèse 1f A 3 A 2g A 2h dum atér e il écessaire n . nnotati on A s 3e A Dive r s : Lis tes d’auteu r s, revus, o cnfér en c es,etc. A3 f 1 Choix de mét hod ol ogie A3c Obt ento in D éfi n i ti on A4 a 4 A4 b Dé fn i ti o i nde méthod oo l gies t conceptssusceptb e il e s prépar ati onou dé vel oppe m ent ’ être u d t il sés. A2 f desout sli A4 d A4e A3 d Uti sil at o in 2 1 Analysede donné es Do nnées rt a i tées A4e A4c d’ échant li on ( s) A5 a Comparaison avecétat de a ’l rt 4 A5 e A5d d’out sli . Trai tement 5 d’ échant li o n A3 :Obtentio nde données A2 : Déf ini it onde ’l état d el a ’ rt Déterm i nato in desdi f érences Réal si a ti on De Tests 3 A6c 4 Anal yse de Résul tats de Tests 1 Défi nit o i ndu ty pede A rte f ca ts /r é su tl a t s In te rm é d a i ri e s/ p ro p o s ti o i n s V a l d i é s Recher che Dn i’ f orm ati on 7 a A valor si at o in A - 0 i 2 4 A6a (publ ci ati ons, et c.) A 7 c S oumsi sion 4 de proposit o i ns Réal si a ti on 2 de réuni ons de dsi cu ssion A 7 d A6d A7 e Récepti onde 5 A c ept ato i n / Ref su depr oposit o i ns A 7 e r o P p o si to i n s N ou v e e l s c o n a si sa n c e s : P ub l ci a t o i n s , ra p p o r ts , te .c - Ac Art ef a ct s/r ésult ats I t erm édiai res n A4 : Trait em ent dedon nées Vali désour ef usé s A6: Su v i i etValidation A5: Analyse der ésult at s Prépar ati on3 de proposit o i ns A 7 b (r e v us, conf. ) A6b A5 c Développement des prop ositi ons Proposit ionsà Valider –A0h Donn éesbrus t sur le s ystèmeen étude- A0 d Déf inti iondu rpojet I nter m é d a i ir es 3 A5 b R e fu s é e s – A 7 f Do nnée s tr a ié t es –A0 e m i portants 1 Ana yl se d’ artéfacts A rt efact s/ Résul tat s Acquis i to i n, 3 2 d’ outli s nécessair es àut li si er Donné es bruts sur e l sys tm è en eét u deA3g Acquisti o i n, 3 prépar ato i n ou dé v el o ppem e nt Do cument d’état del’ art Dé fn i ti iondem éthodo l ogies t conc e ept ssu scepti lbes ’ êtr eutil s d i és. A1g A1 :Dé fi nti io ndu projet Défi n i to i nde mét o hdo l og ie s et o c nce ptssusceptb ie ls d’êtr eutli si é s . A2 f d’ o bt ento in ’ éch d ant li ons A3 b Do cuments u j gés onpert n n i en ts A2 d A 2e 5 Définri viabil ti é de réali sation Ecrir edocument 6 dedéfiniti on du proe jt A7 : Valor s i at ion A0h/ A0i A7e 2 1 Déf n ii r i st e L dis poni bil tié ’n d i struments / i nter ne Matéri e l –A3b Parti cipationaux conférences A33 a Réser ver 2 33f A dis po nb i i til édumatéri e l Lis ted’outi sl –A4b mat éri el A21 c A21 a Défi n i ti ond’auteur s, 1 o j urnaux, co nf érences, équipes de recherche, etc . Co nnaissance s xesi tantes A21 d A2 1b er ti n p ent s pour a l t hé m atq i ue der ech er che Consult ato in d e ba ses dedonné es, bibl o i thèques A33 b 3 Déf n iir 3 disponi biil té A33 c exter ne A33 d et d’autr es sourc es développem ent 21e A (i nter ne/ext erne) Dem an de de 4 4 Comm ander m atér e il 1 D éfn ii r di sponi bil ti é i nter ne 33g A A4 3 b 33f A A4 3 a Réser ver out li 2 3 Déf n iir disponi bil ti é I f romati o n n u sr a l datede dis po ni b i til éde s u oti sl 4 3f A pr oposi ti ons Val d i és - A 0i l si t e d’ opt i ons de va o l ri sat o i n 2 A71a Ré cupér er , co mp é l m en ter 1 A nal yser ou r édi ger il ste de s Choixdut p y ede valori sat o i n- A7a op ti ons 2 Ana yl se r A72a m oye n( s) spé cif q i ue( s) opt o i ns de val or si at o i n A72b 3 3 Cho si i r m oye n( s) C ho si i r t ype d ev alo r si at i on 43 f A A4 3 f sp écif q i ue( s) d e val or si at o i n Outli s Dis pon ib le s A4c Choix dut p ye d e v l orsi ati on- A7a a A 4 3 g A33 g 1 43 g A out li A 4 3 e Déf n i i r mode de5A 4 e3 D évelopper6 développem ent out li (i nter ne/ext erne) Matéri el / n i str u ments Dis po ni b le s 33f A3c A R écu pér er ou r édi ger A71b Com mander4 A 43 c exter ne A 4 3d mat éri el Documen ts àétudi re– A2a documents A3 3e 6 Déf n i i r mode de5 A33 e D évelopper d’i nform ato i n (I nternet ) Ar e t f acts / é r sult ats Int er médiai res/ Inf romato i nsur a l Dé fn i ti o i ndes moyen(s) spécifi qu e( s)de vao l r si ato i n- A7b Instructi o nsd’ut il sati on Mo ded’emploi A3 3 : Acqu si i tio n, pré paratio n ou dé vel opp ement du matéri el A7 1 : Dé fi ni tio n du ty pe d e va loris ati on A43 : Acqui si ti on, prépa rati on o u déve o l p peme nt d es outil s A7 2 : Re c he rc he d ’infor ma tion A21: O btent o i n dedocum ents . Consultation 2 Bb i o il thèque (s) Choixdutypede valorsi ati o n- A7a A213 a A2 1c Consu tl ati on 1 . . Li ste deSources .. d’i nformati on dsi poni be l s 2 A721a Récup ére r il ste A213 f A213 c . A21 3g Rédigerl si te Lis t ededocu m en ts qui pe uvent têe r utli e s 4 3 Me t e r l si teà j our dis ponibe l s danschaq ue Sour ce –A21e Consultation Internet 4 Consultation Col è l g ues 5 Lis tedesmoyen(s ) sp écif q iu e( s) deva lo r si ato i n- A72a A2 13h . A721b A721 c Consultation 3 base sde données A213 b 213d A A213: Consul a t t ion desour cesd’ n i f orm ati on Défin ri ex si tence 1 del si te de M SVpour l etype choisi 213e A . A2 1b A72 1 : Mo y en(s) s pé c if ique(s ) de v alorisa tion (MSV) 1 In scri pti on au il ste( s) de di f usio n L si te d e M S V- A 72 1 b dud oma n i e( s) A7 2 1 3a A 72 1 3 e 2 C onsul tat o in bases de données Consu tl ati on List e de Sour ces A7 2 1 3b d’i nfor m at o in dispon b i l es A 72 1 3 f A7 2 1 3c A 7 21 3 g C onsul tat o in I ncor por er i nfor m ati on àl si t e L si te d e s m o ye n (s ) s p é c fi q i u e ( s) d e v la o r si a to i n - A 7 2 a 3 Int er net A7 2 1 3d A21 3b A21 b A21 c C onsul tat o in 4 A 72 1 3 h Col è l gu es 2 Look for instructions 1 A 2133a Look for work for accessing station for accessing data bases data bases A7 21 3 : Mise à jour d e liste de MSV A2133b Open data base accessing page 3 A2133c A 2133f Fill out the information4 for starting the the research A2133d Start the research 5 A2133e 6 Analyze consultation results List of documents (references) potentially useful – A213f A2133 : Data base consultation 5.2 How are artifacts produced? We wanted to deepen the analysis of research projects for studying the context in which the artifacts are produced. Thus, we proposed a representation of research projects that is inspired on the SADT (Structured Analysis Design Technique) modeling (Figure 2). We added some additional formalisms that allow us to differentiate, regarding the activities performed, between routine activities, semi-routine activities and intellectual activities and, regarding the outcomes obtained, between main results, secondary results and un-used documents. The model is purposely general and not centered in a specific research domain. We hope that this approach help us identify the artifacts produced more that the exact activities carried out during the realization of a research project, as the latter will vary from a scientific domain to another and even from a project to another. This implies that we are interested in the arrows and not in the boxes contained in the model, as the first ones show the artifacts produced during a research project. Anyhow, this model shows some aspects related to the realization of research projects. For starters, it highlights the nonlinear character of this kind of projects. Indeed, even if we have identified some usual aspects present during their realization, reality shows us that these projects are carried out with constant alternations among the various activities. These alternations allow improving problem definition; seeking new ways to explore, and producing research products. It is during this exploration that artifacts are produced. They can result from all the activities done and its exact nature is difficult to foresee. However, thanks to the model, we where able to identify 102 artifacts that we classified into three categories: ● Artifacts related to the bibliography: Some examples are: Publications, research reports, books, researchers’ notes to documents, concepts found in documents, etc. ● Artifacts related to the management of the project: Some examples are: Project plan, meeting reports, etc. ● Artifacts related to the intermediate results: Some examples are: Software and hardware developed for a project, data gathered and treated, etc. Figure. 2. Representation of research projects (inspired on SADT Modeling) This leaves us with the problem of finding ways to capitalize these three kinds of artifacts, which is the subject we will present hereafter. 5.3 How to capitalize the artifacts? In our quest for means to capitalize the artifacts, we identified mainly two possibilities: methodological tools and software tools. Regarding the methodological tools, we centered our attention on the methods of capitalization of project memory present in the literature (as we are interested in the knowledge produced during the realization of research projects). We have identified many works regarding the knowledge related to decision-making, in particular, Bekhti and Matta [3]. However, for the capitalization of the artifacts produced when realizing research projects, we have noted that in spite of the existence of several methods for the capitalization of project memory, those are not adapted to the characteristics of research projects, especially because of the dynamic environment and the non repetitiveness of the projects. That is why we were interested in the possibilities offered by information technology to capitalize artifacts as a mean to facilitate the realization of other research projects. 5.3.1 The existing management software tools for knowledge Groleau [7] says that “the possibility of increasing the effectiveness of work within organizations greatly depends on the configuration of information sources offered to workers in that environment, the vision they offer and the competence of workers to act upon it”. For that reason, we were interested in finding ways to structure artifacts in a way researchers can benefit from them. In this sense, we started by looking at the tools actually available, particularly those classed as being knowledge management tools. Baroni de Carvalho R and Araújo Tavares M. ([4]) have defined knowledge management (KM) software as “a kind of software that supports any of the three basic KM processes (Davenport & Prusak, 1998): generation, codification and transfer.” That is why we have tried to identify the most important knowledge management software tools currently available on the market in order to analyze their functionalities and their capacity to facilitate the capitalization of the artifacts or intermediate results issued from research projects.6 For doing so, we used an automated search and web intelligence solution7 during a two month period (July – August, 2003). This allowed us to identify 53 enterprises, offering 224 KM tools, which we classified according to their main functionalities. The result of this classification is presented as follows: first the type of functionality regrouping some tools, then the number of tools found under this functionality and finally, some examples of tools available on the market. 1. Document Management: (38) iManage WorkDocs™, Hummingbird DM 2. Collaboration, Groupware: (29) Hummingbird CollaborationTM 3. Search Engines: (28) Nexidia’s NEXminer, Open Text’s BRS/Search™ 4. Content Aggregator, Portals: (27) IBM’s DB2® Information Integrator for Content, Computer Associates’ CleverPath Portal 5. Content Management : (17) IBM® DB2® Content 6. Business Process Management, Workflow: (12) IXOSeCONprocess, Staffware Process Suite, AppianWorkflow 7. Knowledge Agents: (8) Autonomy’s Active Knowledge™ 8. Project Management: (6) Accelrys’ DS ProjectKM, Kinematik’s eNovator. 9. E-Learning: (6) LongView’s LRALTM, Eedo’s ForceTen. 10. Graphical Visualization, Knowledge Maps Systems: (5) IBM’s DB2 Intelligent Miner Visualization, Lotus Discovery Server, Inxight’s Star Tree™ SDK 11. Data Integration tools: (5) Hummingbird ETL, Newgen’s OmniExtract 12. Document Routing: (4) iManage WorkRoute, ISYS:rdu 13. Text Base: (2) Inmagic’s DB/TextWorks 14. Linkage of documents by hypertext: (2) Tikit Document Link 15. Others: (35) Open Text’s Livelink Review Manager for Acrobat, Serviceware’s Cognitive Processor This classification shows that the offer is very rich and varied. We where even forced to allow a category for all the tools that did not fit into the others or that responded to several functionalities. Therefore, our conclusion is that the data-processing developments offer many possibilities for knowledge management at research organizations. Nevertheless, we are inclined to think that it still lacks a tool adapted to the basic research activity, focused on the capitalization of artifacts. However, we now know that there are already several tools that could help research organizations manage part of the artifacts they use and produce during the realization of their activity. Concretely speaking, we see that the situation could be schematically presented as follows: ● There are a number of interesting tools offering functionalities for project management, ● there are a few tools offering functionalities for data management, which could support the management of the 6 This information is not included in this paper, because the size of the table that contains it makes it impossible to show it in a legible way. 7 The solution used was Google Alert. artifacts related to the intermediate results, concretely those related to the data gathered and treated; ● finally, some tools manage particular aspects of the management of the bibliography: o Management of references o Visualization of references Given this situation, we have decided to concentrate on the management and the capitalization of the bibliographical work done within research projects. The reason is mainly the absence of a tool that allows managing and capitalizing the knowledge acquired through the realization of a bibliographical research. This, together with the fact that this kind of research has a transversal character, since it is present in virtually all research processes at different levels of importance, has convinced us of the importance of working towards the definition of a tool focused on the capitalization of the artifacts produced when carrying out bibliographical research. It is important to clarify, that by bibliographical work we mean all the relation a researcher, a project team and even a laboratory as a whole, has with bibliographical sources. That is, from the moment he/she starts looking for the available knowledge probably useful for treating a scientific question, to the moment he/she produces new documents (notably publications), containing his/her findings. The idea is to support the researcher in the realization of this work, and by this way to capitalize, at least, part of the knowledge acquired and produced. 5.4 The capitalization of bibliographical research In order to start our search for a way of capitalizing the artifacts produced when carrying out bibliographical research, we carried out a functional analysis (Figure 3). This allowed us to identify three actors: ● The researcher performing bibliographical work on an individual basis ● The project team, where the researchers interact and use the bibliographical work in order to produce research results (by using this work together with the other research activities) ● The laboratory as a whole, where the different project teams interact and share the knowledge acquired. These three actors interact mainly with two entities for doing the bibliographical work: ● The external sources of information that are enriched on a continuous basis with the research results achieved by external research bodies. ● The internal sources of information that should also be continually enriched with the research results achieved by the project teams inside the laboratory for allowing its sharing. We have then identified the following functions: ● F1: To locate and analyze interesting information in the external information sources. The system has to facilitate the activities of research of information and of analysis of the information found. ● F2: To choose and to analyze interesting information available in the internal information sources.. ● F3: To bring relevant information to a project in progress ● F4: To allow the enrichment of the information available in the internal information sources. ● F5: To share the bibliographical information collected and produced. ● F6: To support the writing of publications. Project Team Researcher Laboratory 5.5 F4 F1 F3 Management and capitalization of bibliographical work F5 F6 External Information Sources F2 Internal Information Sources - ISS Figure 3. Functional Analysis of a tool for managing and capitalizing bibliographical work within research projects These functions have been declined in a further level of detail, by taking into account the bibliographical artifacts already identified and the current practices used for this kind of research and the uses researchers do of the bibliographical work done. This means that we want to support the researcher during all the interaction he or she does with bibliographical sources until the production of new bibliographical material. This implies managing not only the references, as objects, but also the contents they try to transmit. With this specification of the functions the system should respond to, we performed an analysis of the technical options available to answer to them. For doing so, we leaned onto the work we had previously done for identifying the knowledge management software tools available on the market and we complemented it with a new identification work, focused on the bibliographic management tools available. The conclusion of this work was that the tools already available on the market support some of the functions identified as being fundamental for managing in a comprehensive way the bibliographic work. However, they only offer a partial support to all the interaction of a researcher with the bibliographical sources and there is not a tool offering a support to all the identified functions. In other words, every tool offers some useful functions for the management of the bibliographical work, but there is not a single tool that manages them all. Moreover, there is a very important function for which we have not been able to identify any tool. We refer to the management of the scientific concepts8 that appear in the bibliographical sources. Concretely speaking, we were not able to identify solutions concerned with the location and extraction of definitions and descriptions of concepts contained in documents resulting from process of research. This aspect can be very useful for the research activity in general and for practical aspects like the writing of scientific documents. In fact, according to Dunbar [5] “many researchers have noted that an important component of science is the generation of new concepts and modifications of existing concepts. Starting with Bruner, Goodnow, and Austing (1956) many researchers focused on the idea that scientists must formulate new concepts and theories”. That is why we intend to support this process by supporting the bibliographical work linked to it. 8 By scientific concepts we mean the constructions based on previous scientific knowledge and supporting data, that undergo an evaluation procedure to verify their ability to explore, explain, describe, predict or influence a phenomenon. Supporting the bibliographical work related to the manipulation of scientific concepts In order to find ways for supporting researchers through the realization of the bibliographical work related to the manipulation of scientific concepts, we carried out a modeling of the system with UML (Unified Modeling Language). What we intend to do is to build a proposition of a functional specification of a system that would accomplish such a task. We started by identifying the users as follow: ● Individual Researcher: locates the contents containing a concept ● Researcher member of a project team: uses the concept ● Administrator: Incorporates the concept in a global structure to allow its re-use. For each user identified we constructed its corresponding use case diagram. This allowed us to stablish the different classes interacting in the system. The identified classes are: ● Researcher: represents the categories of user previously described ● Document: represents the documents that can contain concepts ● Document zone: represents a zone of a document containing a concept or any information considered interesting for the researcher. ● Concept: Definition or description of a concept. ● Annotation: represents an annotation about a document or about the contents or about another annotation ● Project: represents spaces where the concepts are used to produce new concepts. The interactions among these classes are represented in the diagram shown in the figure 4. This model allows us to establish the basis for the specifications of a software tool for supporting researchers in their work with bibliographical sources. These are seen as artifacts representing a part of the knowledge produced as a result of previous scientific work. They function is to transfer concepts that other researchers will be able to use for producing new concepts. The idea is to support this process in order to allow researchers to concentrate more on the intellectual activities and less on the routine activities. The perspective is now to arrive to a greater degree of detail in the specifications of the tool, which would allow us to proceed with its development and testing. 6 CONCLUSIONS AND PROSPECTS Our research starts with the reflections carried out in France by organisms that recommend quality management as a mean to support the research process. For that reason, we wanted to study the situation of the research organizations when they implement a quality management system. To this end, we completed a field work in order to know their reality and to collect information on the difficulties encountered when implementing this kind of system. The first step of this work allowed us to observe several characteristics of the research activities. They imply major differences between this type of activities and the industrial activities where the quality management has been traditionally used. Moreover, we have noted that the fundamental problem of the surveyed organizations is the improvement of the process of their activities. The quality management of the organizations we observed does not directly address the research activities. Indeed, the field work allowed us to note that even if the main activity of the analyzed organizations is the production of knowledge, the systems are centered on the formalization of certain activities, mainly the activities that support the research activity, and on the management of part of the documents, primarily the final documents (and not the intermediate results or the artifacts). Is composed of 0..* Document / Document zone Identification Name Contents Type * Creator 0..* Associates Lier concepts() Lier projet() Eliminer concept() 1 Project Identification Date Title_Project Type_Project Description_Project Domaine_Project Responsable_Project Activity_Project 0..* 1 Associates 1 1.. * 1 Creates 0..* 1..* 0..* 1..* Concept Identification Date Name Domaine_concept Type_concept Description_concept Creator_concept Associates +Identifies Uses 0..* 0..* Associates 1.. * 1..* 1 Identifies Creates Writes 0.. * 1 Annotation Identificat ion Date Tit le_annot ation Text_annotation Creat or_annotation Rédiger 1.. * 0..* 1..* 1..* 1..* Researcher 0..* Writes 0..* Name Domaines of interest Status : Identifies, uses, administers Projects 0.. * Figure. 4. Class Diagram for a support system for the realization of bibliographical work related to the manipulation of scientific concepts On the other hand, we have exemplified that the quality management systems observed do not really address the knowledge management aspect in research, and that document management does not address the artifacts of research. The cause seems to be the lack of methodologies and of real experiences that would formulate a way to set up a quality management system focused on knowledge management. That is why we propose a representation that takes into account the importance of addressing the management of knowledge when implementing a quality management system at a research organization. The idea is to profit from quality management techniques and from knowledge management techniques in order to address the issue of quality at research organizations. Then, in order to look for ways of establishing the concrete methods of implementing our proposition, we carried out an analysis of the activities realized during the research process and of the information used and generated by these activities. This analysis enabled us to define that a very important aspect for the capitalization of knowledge resulting from research projects is the capitalization of the knowledge produced and acquired during the realization of a project. That is, the capitalization of the artifacts produced during this stage of a project. Our next step was to analyze the way in which these artifacts were indeed produced. For this purpose, we schematized the way in which research projects are realized by inspiring ourselves in the SADT modeling technique. This work allowed us to identify more than a hundred artifacts produced during the realization of research projects. We then classified them in three categories: Artifacts related to the bibliography, artifacts related to the management of the project and artifacts related to the intermediate results. The problem was now to find ways to allow the capitalization of these three kinds of artifacts. For this reason, we studied two main ways: methodological tools and software tools. Regarding the methodological tools, we did not find any tool we considered adapted to the research activity. This leaded us to the study of the existing knowledge management tools. We assessed the current richness of the offer: We found tools that offered functionalities for managing projects, others that could be used for managing data and others that offer a very diverse sample of functionalities for managing knowledge in organizations. However, and in spite of the great possibilities for knowledge management, there is a lack of tools that could facilitate the capitalization of intermediate results issued from research projects. Given the transversal character of the bibliographical work for the research activities performed in different research domains, we decided to work towards the definition of a tool focused on the capitalization of the artifacts produced when carrying out bibliographical research. For this purpose, we realized a functional analysis that let us identify the main functions we should respond to. We then analyzed the technical options that existed to respond to these functions. We found some tools that address specific aspects of the management of the bibliography, but none that offers a comprehensive support for the development of this activity. This means that there are fundamental aspects for which we have not been able to identify any tool. We refer to the work related to the management of scientific concepts done by researchers when dealing with bibliography in the context of research projects. In fact, we noted that the tools address mainly the management of the container and not the management of the contents. For that reason, we decided to concentrate on the definition of a tool that should provide a support to researchers through the realization of the bibliographical work related to the manipulation of scientific concepts. That is why we carried out a modeling of the system with UML that establishes the basis for the specification of a software tool we intend to develop during the months that follow. Once the development of such a tool is finished, we will have to test it to analyze its capacity to effectively improve the knowledge capitalization. Moreover, it is necessary to study the way in which quality management could be used to introduce the knowledge management principles and how the tool could support these approaches. We think that quality management could be established at research organizations in a more beneficial way by contributing to the improvement of their knowledge management. The next phase of our research is thus the definition of the specifications of a tool for the capitalization of the bibliographical work done in the framework of a research project, as a way of capitalizing part of the knowledge acquired and produced during its realization. We will then start the development of a prototype, which we will later on test to verify the benefits it could offer to the research activities. REFERENCES [1] [2] [3] AFNOR (2000) NF EN ISO 9001 – 2000 « Système de management de la qualité – Exigences ». AFNOR. Paris. 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