Data quality

The comparability of data is an important supposition for the international cooperation. Thus, intercalibrations and intercomparisons were already performed very early in the Baltic Sea area. The IfM and the lOW participated in the adequate activities inside and outside of this area. The most important intercalibrations and intercomparisons for hydrographic parameters and nutrients are listed in Table 3.4. The adequate exercises for organic phosphorus, organic nitrogen, and organic carbon as well as for harmful substances are treated in the relevant chapters. 

Intercalibrations for hydrographic parameters and nutrients have also been organized between the Baltic countries belonging to the former East Block in the frame of the COMECON Programme World Ocean. They are only exceptionally published in scientific journals (e.g., Grasshoff, 1966). 

When research vessels met at sea or in harbors, intercalibrations of opportunity have been carried out (cf. Nehring, 2002). Their results were exchanged at the end of the respective meetings. They are not published. 

Instruments or Parameters Place or Name Year Comment Reference 

Aitsam, A., Talpsepp, L., 1982. Synoptic variability of currents in the Baltic Proper. In Hydrodynamics of Semi-Enclosed Seas. Elsevier, Amsterdam, pp. 469 88. 

A useful discussion of data accuracy is in Nordstrom and Munoz (1986). 

No one who creates a database and makes it available for general use will make any guarantee about the accuracy of the data, for obvious reasons, so the user is left in a minefield of conflicting data, because the commonly available databases are certainly not identical. 

The thermodynamic data for ordered dolomite are commonly agreed upon, and calculations based on the data show that seawater is greatly oversaturated with dolomite, yet it does not precipitate. This is widely accepted. Recently, Lafon et al. (1992) have 

The fact that basic thermodynamic data are imprecisely known means that model results such as p values, SI values, and so on, will all be to some extent imprecise as well. The imprecision of the input data is propagated through the calculation procedure and appears in the results. The nature of this propagation has not been extensively investigated, but it depends not only on uncertainties in the thermodynamic and analytical data, but also on the nature of the geochemical system involved. See Anderson (1976, 1977) and Criscenti el al. (1996) for discussions. 

Another problem is that of consistency among the data in a database. That is, data for A fS°, A /H°, and A/G° for compound X may be obtained from different sources, and each may be the best available, but they may not be consistent with A /G = A/H — TAfS. Or we may obtain the best possible A/G° data for each of lime (CaO), calcite, and carbon dioxide, but when put together, we find they are not consistent with equilibrium constant data for the reaction CaC03 = Ca0 + C02. There are several levels of such self consistency that should be satisfied (Engi, 1992, p. 276), and dealing with this problem is another job for specialists. It is unfortunately a very big job, and it has not been carried out to the fullest extent possible for any database commonly used for environmental problems. 

This spectrum presents an instructive case for the large uncertainties in atomic transition probabilities, obtained even with sophisticated multiconfiguration calculations. For this ion, three extensive and detailed atomic structure calculations have been undertaken in the last ten years [15-17]. 

These are R-matrix calculations, which are part of the international Opacity Project (OP) [15], theoretical results from the MCHF database collection by Tachiev and Froese Fischer [16], and calculations by Blackford and Hibbert with the CIV 3 code [17]. In Fig. 17.9 the ratios of the OP and CIV oscillator strengths to the MCHF results are plotted on a logarithmic scale versus the MCHF oscillator strength (/-value) data. 

---

Guidelines for Data Acquisition and Data Quality Control Evaluation in Environmental Chemistry, Ana/. Chem. 1980, 52, 2242-2249. 

Data quality assessment requirements are related to precision and accuracy. Precision control limits are established, i.e., 4-10% of span value, as calculated from Eq. (15-1). The actual results of the may be used to calculate an average deviation (Eq. 15-3) ... 

This chapter has only scratched the surface of the multitude of databases and data reviews that are now available. For instance, more than 100 materials databases of many kinds are listed by Wawrousek et al. (1989), in an article published by one of the major repositories of such databases. More and more of them are accessible via the internet. The most comprehensive recent overview of Electronic access to factual materials information the state of the art is by Westbrook et al. (1995), This highly informative essay includes a taxonomy of materials information , focusing on the many different property considerations and property types which an investigator can be concerned with. Special attention is paid to mechanical properties. The authors focus also on the quality and relutbility of data, quality of source, reproducibility, evaluation status, etc., all come into this, and alarmingly. 

If the data quality was acceptable, they were then evaluated for their relevance and fit to the CCPS Taxonomy. The data in the SAIC data base were fitted to taxonomy levels that best correlated with nuclear plant equipment and operational environments. CPI resources were reread thoroughly to understand the equipment subtypes, operating modes, and process severities represented by the data points and to identify as many relevant taxonomy levels as possible. SAIC data analysts made preliminary judgments on the applicability of data points to taxonomy levels and on the quality of the data. The majority of the data applied to high taxonomy levels (x.x) and a smaller amount was applicable to lower levels (x.x.x.x). The data were assigned to the lowest level possible. 

Documentation of data origin is essential. Each completed data collection form needs to contain a file reference number or code to connect it to the documentation sources. This provides an essential trail to audit data quality, to confirm risk or reliability estimates or to investigate data values that appear questionable. Procedures to control data during handling, processing, recording, and reviewing are also necessary to prevent loss of data and to assure that opportunities are not lost to check the content of a form, by... 

Blanks, H. S. The Generation and Use of Component Failure Rate Data. Quality Assurance, Vol. 

It is important for predictive maintenance programs using vibration analysis to have accurate, repeatable data. In addition to the type and quality of the transducer, three key parameters affect data quality the point of measurement, orientation, and transducer-mounting techniques. 

Predictive maintenance programs using vibration analysis must have accurate, repeatable data to determine the operating condition of plant machinery. In addition to the transducer, three factors will affect data quality measurement point, orientation and compressive load. 

Measuring HTS Output Data Quality and Validated Hits... 

X-Ray Data for the Native Fepr Protein Showing the Data Quality and Completeness to 1.71 A Resolution, A = 0.87 A... 

Data Assembly and Clean-Up Section 4.31 provides an example of how tables often look when data was compiled from a multitude of sources formats might differ, data quality is uneven, and comments in text format were smuggled in to further qualify the entries. Since vital background informa-... 

MacDougal, D., et al. Guidelines for Data Aquisition and Data Quality Evaluation in Environmental Chemistry, Anal. Chem. 52, 1980, 2240-2249. 

Berthelsen CL. Evaluation of coding data quality of the HCUP National Inpatient Sample. Top Health Inf Manage 2000 21 10-23. 

System Evaluation Subject Management Data Quality Assurance Treatment Dispensing Handling Unexpected Events Data Transformation... 

The use of wireless computer systems has gain popularity in data collection for clinical trials. They have been used as a substitute for normal paper-based patient diaries (Koop et al. [19]) to increase data quality and shorten the time needed to close the database. They have also been used for mobile interviewing [20] and for bedside data collection [21]. In patient-directed data entry, subjects are given handheld computers to answer the trial s questions (Clarke et al. [22]). 

The data are usually given a priori. Even when experimentation is tolerated, there exist very few cases where it is known how to construct good experiments to produce useful knowledge suitable for particular model forms. Such a case is the identification of linear systems and the related issue on data quality is known under the term persistency of excitation (Ljung, 1987). 

Holden, J.M., Bhagwat, S.A., and Patterson, K.Y., Development of a multi-nutrient data quality evaluation system, J. Food Compos. Anal, 15, 339, 2002. 

The steps outlined below are intended to guide the development of data quality objectives for the sampling effort. These have been discussed in part by others (1,2). 

Criteria 1) Relevance to human health endpoints. 2) Sensitivity to change in loadings. 3) Overall historical data quality. 4) Data collection infrastructure. 5) Feasibility of data collection and analysis. 6) Ability to adjust for confounding factors. 7) Understanding of linkages with rest of ecosystem. 8) Broad geographic distribution. 9) Well-known life history (for fauna). 10) Nonintrusive sampling. 

Ihnat M (1993) Reference materials for data quality. In Carter MR, ed. Soil Sampling and Methods of Analysis, Chap. 26, pp 247-262. Lewis Publishers, Boca Raton, FL. 

Applications of geological reference samples to mineral prospecting and economic evaluation of ore potential is the only application with a history dating back before the issuance of G-i and W-i in 1951. It is an area in which data quality or lack thereof has serious economic impacts, hence the very early development of certified reference materials mentioned previously. An extensive study of the state of ore analysis was undertaken by the Institute of Geological Sciences (now the British Geological Survey). Nineteen ores and concentrates, of varied matrix, were distributed to 38 laboratories more than 1532 results were received (Lister and Galagher 1970). 

Ihnat M (1998a) Reference materials for data quality control. In Kalra YP, ed. Handbook of Reference Methods for Plant Analysis, pp 209-220. CRC Press, Boca Raton. 

Laboratory Accreditation and Quality Systems" Together these make laboratory managers look for added security in assuring data quality and thus invoke a desire in them to fall back on the best available standard. The result is that a CRM is often used instead of a working standard. This is a tendency that is supported and encouraged by some RM providers but discouraged by others. 

---