Databases save time and improve the quality of the design, management and processing of ecopathological surveys

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1 Databases save time and improve the quality of the design, management and processing of ecopathological surveys P Sulpice, F Bugnard, D Calavas To cite this version: P Sulpice, F Bugnard, D Calavas. Databases save time and improve the quality of the design, management and processing of ecopathological surveys. Veterinary Research, BioMed Central, 1994, 25 (2-3), pp <hal > HAL Id: hal Submitted on 1 Jan 1994 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

2 Databases save time and improve the quality of the design, management and processing of ecopathological surveys P Sulpice F Bugnard, D Calavas Centre d Écopathologie Animale, 26, rue de la Baisse, Villeurbanne, France Summary &horbar; The example of an ecopathological survey on nursing ewe mastitis shows that data bases have 4 complementary functions: assistance during the conception of surveys; follow-up of surveys; management and quality control of data; and data organization for statistical analysis. This is made possible by the simultaneous conception of both the data base and the survey, and by the integration of computer science into the work of the task group that conducts the survey. This methodology helps save time and improve the quality of data in ecopathological surveys. ecopathology / survey / data processing / data base / sheep Résumé &horbar; Les base de données : gain de temps et de qualité dans la conception, la gestion et le traitement des enquêtes d écopathologie. En prenant l exemple d une enquête d écopathologie sur les mammites des brebis aitaitantes, on montre que les bases de données ont 4 fonctions complémentaires : aide à la conception des enquêtes, suivi des enquêtes, gestion et contrôle de qualité des données, organisation des données pour l analyse statistique. Cela est rendu possible par une conception simultanée de la base de données et de l enquête, et l intégration de la matière informatique au groupe de travail qui élabore l enquête. Cette méthodologie concourt à gagner du temps et à améliorer la qualité des données dans les enquêtes d écopathologie. écopathologie l enquête l informatique / base de données / ovins INTRODUCTION Data bases become necessary in ecopathological surveys because of the volume of the collected data and the structure of the information (Lescourret et al, 1992). At first, data bases were used at the Centre d Écopathologie Animale after the phase of data collection. This late use proved to be expensive in conception time, particularly for the semantic modelling of data. Further- more, the use of the data base after all the information has been collected allows only a late verification of the data without the possibility of returning to its origin to improve data quality. In order not to limit the definition of the function of the data base to the organization of data prior to statistical analysis, its conception and construction must be carried out at the same time as the survey. Thus, the data bases conceived, generated and used by the Centre d Ecopatholo- * Correspondence and reprints

3 gie Animale have 4 complementary functions: assistance during the conception of surveys by a computer-oriented approach; follow-up of the survey in the farm; management and control of the data quality; and organization of data prior to statistical analysis. The example of the survey on nursing ewe mastitis (Calavas, 1992) illustrates these 4 functions and gives a general idea of how this approach can help save time and improve the quality of the ecopathological surveys. FUNCTIONS OF DATA BASES AT THE CENTRE D ECOPATHOLOGIE ANIMALE Assistance during conception of surveys A survey and its data base are developed simultaneously and interactively. From the very beginning, the computer scientist participates in the work of the task group in charge of the survey (Calavas, 1992). This allows the development of a synergy and an interaction between the survey and the database, as well as the distribution of conceptual elements, such as a hypothesis scheme (path analysis), a project of the protocol, models of questionnaires, and a conceptual data model (fig 1 ). The conceptual approach previous to the generation of data bases (Tardieu et al, 1983) has a large impact on the conception of the survey. In some cases, the conceptual data model built from the hypothesis scheme, the projects of questionnaires and the data collection protocol all shed light upon a non-functional organization of the survey (data coding, identification of individuals, and coherence of questionnaires). Furthermore, peculiarities that make the progress of the survey easier in the field, must be taken into account in the data base. For example, in this survey, the ewes were identified by a collar number (to facilitate pinpointing a sample of ewes monitored during the entire survey) and/or by a perennial identification number, an ear tag, or tattooing (for animals affected by mastitis and added to the sample in the course of the survey), which necessitated taking into account 2 different identifying attributes (fig 2). Follow-up of surveys The study of the information flow allows computerization of certain operations of the survey management, for example, letters sent to different participants of the survey (reminders to return questionnaires and survey agreements) and tools of the protocol follow-up (identification labels for the biological samples and lists of the ewes examined during the first visit in order to facilitate the follow-up of these animals during subsequent visits). This also allows the automation of the return of information to the breeders and the interviewers in the course of the survey, eg results of serological analysis and preliminary statistical analyses. Management and control of data quality The fact that the data base is operational when the survey starts in the field allows a continuous operation of rereading/correction and data entry as soon as the first survey documents return to the Centre d fcopathologie Animale. Information control at different levels (identification, intrinsic coherence, and coherence between variables) allows the detection of errors and inconsistencies unnoticed during the rereading of questionnaires (Sulpice, 1992). This also makes it possible to go immediately back to the source of information in the case of error, or incoherent or missing data.

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6 Organization of data The data base constitutes the protected and autonomous primary layer of the survey data, ie includes all collected data, as well as an exhaustive data dictionary. The data base management system becomes a server for the data to be exported to the statistical analysis software (eg, SAS and SPADN). On their way back, the synthetic data generated by the statistical analysis (eg, calculated data and risk factors) are integrated in a secondary layer. In the end, these 2 layers of information constitute the referential data base built from the survey. SAVING TIME AND IMPROVING THE QUALITY OF SURVEY DATA Saving time The synergy implemented in the conception of the survey is aimed at sharing the feasibility constraints of the survey (eg, the way the visits progress, the special organization of a notation document in the form of a table, or the necessity of a double identification of the ewes) and the data base (eg, division into entities and associations to be implemented). There are no head losses insofar as data processing is integrated in the task group that conducts the survey, computerized data processing being one of the disciplines of the task group and the computer scientist representing one of the professions (Rosner, 1984). Sharing conceptual elements during the conception stage of the survey helps valorize the work of preparing the analysis documents. For example, a diagram of the physical data model is used to give a synthetic view of the collected data and can be used as a work document during the conception phase and as an element of the study report (fig 2). The automation of the data management tasks allows a reduction in the time spent on the administrative management of the survey (eg, movements of the documents, survey progress, and mail) and thus, greater importance can be given to the follow-up of the data collection (eg, rereading the documents, respecting the deadlines of the protocol, and making inquiries). The opportunity to continuously carry out operations of rereading/correction and data entry allows the statistical analysis to be started at the return of the final document and sometimes even in the course of the survey when the documents are split up. It is therefore possible to considerably reduce the time between the arrival of the information at the Centre d!copathologie Animale and the beginning of the statistical analysis, thus helping to obtain results much quicker (fig 1 ). Improving the quality of the survey data First, due to the computer-oriented approach preceding its generation, the data base helps improve the quality of the data collection during the conception stage of the survey: feasibility of protocols; coherence of the questionnaires; study of the information flow. The data base then helps collections of data by using the follow-up tools which it generates (owing to the generated lists, it is possible to reduce the number of ewes lost during the survey because of identification errors). Its main mission at the level of the data collection is to provide control of the data reliability at the time of their entry and allow a quick return to the source of the information in the case of an error. For example, 4 questionnaires about the breeding level (flock, breeding management,

7 weaning, flock contacts) and individual forms filled out during the first visit of the survey were verified and entered into the data base immediately after being received at the Centre d Ecopathologie Animale. Concerning the questionnaires, it was found out that 2.82% of the data was missing (176 out of 6 235). Reminders were sent immediately and 169 missing data items were recovered (to reach the level of 1 per missing data). In what concerns the ewes, each animal was described by 20 variables, totalling data items (4 598 x 20). The rate of the missing data in all filled-out forms was less than 1 per (89 out of ). Finally, during statistical analysis, the data base allows a transfer to the statistical software, both files containing the survey data and a data dictionary (with the name, label and description of the classes of variables). The data dictionary provides, in an univocal way, a reference to each variable based on the precise wording of the questions; this excludes all risk of ambiguity in the analyzed variables (no errors possible in the wording or in the value of each class). Moreover, all editing necessary for the analysis is documented. This provides security and comfort, especially taking into account the difficulty of giving only 8-character names to variables (in the survey there were, for example, 119 individual variables relative to the ewes, of which 59 characterized the mammary glands, with notation of lesions on each quarter of the mammary gland twice during the survey; thus it was difficult to have 59 explicit names based on a 8-character label). of the data base with the data base management system Dataflex (Data Access Corporation, 1991) required 15 working days for a computer scientist. The database was operational at the time of the data collection (fig 1 the statistical analysis started in July 1993 on the data collected during the first visit, that is to say 34 d after the return of the last questionnaire, and immediately after the return of the last reminder. The quality of the collected data can be evaluated by the final rate of the missing data after the reminders (less than 1 per 1 000). CONCLUSION The synergetic and simultaneous organization between the ecopathological survey and the data base reinforces the role of the data bases. This determines the 4 complementary functions of the databases: assistance in the conception of surveys; technical management of surveys; management and control of the data quality; and organization of data for statistical analysis. Thus, the data bases set up by the Centre d tcopathologie Animale for each of its surveys conform with: (i) its guidelines, as they reduce the time of processing the ecopathological surveys and generate a referential data base built from the survey; and (ii) the chosen methology of data processing integrated into the work of a pluridisciplinary and pluriprofessional task group that conducts the surveys and their follow-up. REFERENCES Illustrative figures on the survey of nursing ewe mastitis Some indicators will help appreciate the time saved and the quality improved in this survey. The conception and the generation Calavas D (1992) Conception de 1 enqu6te. In: Mammites des brebis allaitantes. Centre d Écopathologie Animale, Villeurbanne, 11, l,pp143 Data Access Corporation (1991) Dataflex User s Guide. Miami, USA, pp 732

8 Lescourret F, Perochon L, Coulon JB, Faye B, Landais E (1992) Modelling and information system using the MERISE method for agricultural research: the example of a database for a study on performances in dairy cows. Agric Syst 38, Rosner G (1984) Rapport relatif a I etude de faisabiiite du projet de creation d un centre regional d 6copathologie muiti-especes. GIE Lait Viande Rhone Alpes, Lyon, pp 74 Sulpice P (1992) Appropriation de l outil informatique par des enqu6teurs au cours d une experimentation de saisie sur site. Actes 2! Coll Eur Agrimatica Informatique et t6l6matique agricoles. Methodes et conduites de projets Charbonnibres-les-Bains, France, 2-3 juillet, Tele Promotion Rurale Rh6ne-Alpes, Tardieu H, Rochfeld A, Colleti R (1983) La methode MERISE. Tome I. Principes et outils. Les Editions d Organisation, Paris, France, pp 320 Vet Res (1994) 25, Elsevier/INRA Deer-herd health and production profiling in New Zealand. I. Study design L Audigé PR Wilson, RS Morris Department of Veterinary Clinical Sciences, Massey University, Palmerston North, New Zealand Summary &horbar; A 2-year observational study was conducted on 15 commercial reddeer farms in the North Island of New Zealand, to provide health and production data, and identify risk factors for outcomes in-cluding health, reproduction, venison and velvet antler production. About hinds, weaner deer and stags were monitored. Daily management practices, deer performance and health problems were recorded. At 3-monthly visits, samples were collected from deer, pastures and soils. Data were processed by multivariable statistical techniques to identify the most important factors affecting production and health. epidemiology / observational study / farmed deer / New Zealand / multivariable statistical analysis Résumé &horbar; Profil de santé et de production dans les élevages de cerfs élaphe en Nouvelle- Zélande. 1. Protocole d enquête. Une enquête d observation de 2 années était en cours dans 15 élevages de cerfs élaphe dans l ile du Nord en Nouvelle-Zélande afin d en connaître les profils de santé et de production, et les facteurs de risques associés aux paramètres de santé, de reproduction, et de production de venaison et de bois en velours. Environ biches, jeunes cerfs sevrés et i 500 cerfs étaient individuellement suivis. Les pratiques d élevage, les performances zootechniques et les problèmes de santé étaient enregistrés quotidiennement. Cerfs, patures et sols étaient prélevés au cours de visites trimestrielles. Les données étaient analysées par méthodes statistiques multivariées. épidémiologie lenquête d observationlcervidéslnouvelle-zélandelanalyse statistique muttivariée * Correspondence and reprints