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It can be noticed the more severity provided by the desirability approach with respect to the utility one. The second and third alternatives are judged as not desirable because of their low performance on the third and first criteria, respectively, no matter what their performances are on the other criteria. The dominance results are independent of the scale used, being based on a pair comparison approach. Table 13 Estimated values of alternatives for criteria computed on global scale Alternatives 1 2 3 Desirability Utility Dominance 0.

Todeschini 3. We reviewed a number of total-order ranking methods, which have been widely used to facilitate the structuring and understanding of the perceived decision problem. We presented here the simplest approaches, like the Pareto optimality and the SAR approach followed by the approaches belonging to the so-called multiattribute value theory, i. In these models, numerical scores are constructed to represent the degree to which an alternative may be preferred to another.

These scores are developed initially for each criterion and aggregated into a higher level of preference models. Several other methods have been proposed over the years. In these methods, alternatives are compared pairwise, initially in terms of each criterion and then the preference information is aggregated across all the criteria. These methods attempt to set up the strength of evidence in favor of one alternative over the others.

Another group of total-order ranking methods is the one of the so-called goal programming approach Charnes and Cooper, , which includes linear goal programming, interactive goal programming, STEM method, interactive multiple goal programming and the reference point method. These methods based on the establishment of desirable or satisfactory levels of achievement for each criterion search for the alternative that is closest to these desirable goals or aspirations.

Other methods are the analytic hierarchy process AHP method developed by Saaty , , which emphasizes the role of the weights of the criteria, the fuzzy set theory Zimmermann, which attempts to solve the main problem in MCDM field related to the inevitable ambiguity in defining human preferences.

Finally, Bayesian analysis is a widely used approach for knowledge representation and reasoning under uncertainty in intelligent systems Pearl, ; Russell and Norvig, A complete review of the theoretical background of each of these models has been recently published Pavan and Todeschini, In: Advances indecision Analysis Meskens, N.

Belton, V. Boer, J. Introduction of multi-criteria decision making in optimization procedures for pharmaceutical formulations, Eur. Bouyssou, D. Brans, J. In: Oper. Brans J. Charnes, A. Derringer, G. Simultaneous optimization of several response variables, J. Doornbos, D. Experimental design, response surface methodology and multicriteria decision making in the development of drug dosage forms. French, S. Geoffrion, A. An interactive approach for multicriterion optimization with an application to the operation of an academic department, Manage.

Harrington, E. The desirability function, Ind. Hendriks, M. Multicriteria decision making, Chemom. Hobbs, B. Power Syst. Keller, H. Program for Pareto-optimality in multicriteria problems, Trends Analyt. Multicriteria decision making: A case study, Chemom. Keeney, R. Decision with Multiple Objectives, J. Korhonen, P. Solving the discrete multiple criteria problem using convex cones, Manage. Lewi, P. Optimisation: Multicriteria decision making methods. In: Comprehensive Chemometrics, Elsevier. In press. Pearl, J.

Roberts, F. Roy, B. Rubens, M. Russell, S. Saaty, T. How to make decision: The analytic hierarchy process, Eur. Smilde, A. Introduction of multicriteria decision making in optimisation procedures for high-performance liquid chromatographic separations, J. Optimisation of the reversed-phase high-performance liquid chromatographic separation of synthetic estrogenic and progestogenic steroids using the multi-criteria decision making method, J. Stewart, T. Use of piecewise linear functions in interactive multicriteria decision support: A monte carlo study, Manage. Multi-Criteria Decis.

Todeschini von Winterfeldt, D. Watson, S. Decision Synthesis.

Scientific Data Ranking Methods: Volume 27 : Theory and Applications

Zimmermann, H. Multi-Criteria Analyse, Springer, Berlin. Zionts, S. An interactive programming method for solving the multiple criteria problem, Manage. Using fuzzy sets in Operational Research, Eur. An interactive multiple objective programming method for a class of underlying nonlinear utility functions, Manage.

Voigt, and S. Pudenz Contents 1. Partial-Order Theory 2. Software for Hasse Diagram Technique 4. Ranking of Chemicals as An Example 4. Summary, Outlook and Conclusion References 73 74 74 75 77 78 78 79 83 83 86 90 91 1. One of the main applications of graph theory in chemistry is the derivation of topological indices as graph theoretical invariants. Topological indices in turn are the basis for many quantitative structure—activity relationships QSAR.

For details see Todeschini and Consonni , Basak et al. However, graph theory in its application on chemistry is not restricted on QSAR. Reaction networks is another example where Data handling in Science and Technology, Vol. Glass, ; Nemes, et al. Another example of directed graphs arises from the comparison of vectorial quantities. For example, alkanes may be ordered by a list of modified Zagreb indices Vukicevic et al. In this chapter, we explain the nature of Hasse diagrams, give some examples from the area of environmental chemicals and their data availability.

Finally, we briefly describe the software, by which partial order from the point of view of applications can be analyzed and by which partial orders can be visualized—for example, by Hasse diagrams. Hasse diagrams got the name from the German mathematician H. Hasse, who lived from to and who used them to represent algebraic structures Hasse, As Hasse diagrams are the visualization of a mathematical concept, namely of partial order, one has to go back until the end of the nineteenth century, where Dedekind and Vogt see Rival, made the first important investigations.

Parallel to H. Hasse, the American mathematician G. From the pioneering work of E. Halfon, the concept of partial order was introduced in environmental sciences and chemistry Halfon, , , ; Halfon and Reggiani, The usefulness of partial order in evaluation problems was then recognized by the authors of this chapter and extended in several directions.

Since regularly workshops about partial order and its Hasse diagram take place, see e. They gave a first state of art of application of partial order in environmental sciences and chemistry. The charm of the visualization technique of partial order gives an additional attractiveness, so this chapter is specifically widowed graphical representations, especially the Hasse diagram. First step: We need a set of objects. Objects can be chemicals which are to be compared Bru et al. Second step: We need an operation between any two objects. As an evaluation is our aim, we must compare the objects.

It is practice to use the sign?

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The essential point is that we have to define, when we consider object a as better than b. Later we will relax this axiom. Transitivity: If a is better than b and at the same time b is better than c, then a is better than c. Sixth step: Why can a partially ordered set be represented by a directed graph? Consider the objects of a ground set as vertices. Then a Hasse diagram is a graph of cover relations with additional conventions of how to locate the objects in the drawing plane. Then the directed graph is shown in Figure 1.

One, but not necessarily the only one, definition is: 76 R. The qi are the attributes by which the objects should be characterized for their evaluation see below for examples. Nevertheless, a is not identical with b. Therefore, the evaluation based on qi does not necessarily lead to a partial order, but a quasi- or pre-order see for explanation De Loof et al. It is convenient to introduce the equivalence relation. By the equivalence relation the ground set can be partitioned into equivalence classes. If one takes one element out of any equivalence class the representative of an equivalence class and ignore the others, then we retain the partial orders for the representatives.

One has to take care that the conclusions that can be drawn for the representative due to the partial order are valid for all the other elements of that equivalence class, which is represented. The interplay between order and equivalence is described in a systematic manner in Voigt et al. If one applies this phase literally, one will not get any useful result!

The problem is that just those attributes qi that are relevant for the evaluation and clearly which are available should be selected.

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This, however, is not a specific problem of partial-order theory but of any multi-criteria evaluation. In order to express the important role of the selection of the attributes, the partial order in Hasse diagram technique HDT is often written as G, IB , where IB is the information base of evaluation and is the set of all attributes used in the evaluation. One of the main difficulties is to avoid crossings of lines and crossing of lines with the circles, denoting the objects. As an example of the rather sophisticated computational efforts, the publication of Halfon et al.

This software named WHasse has always been available for scientific purposes from the first author free of charge. A second software product based on the HDT background written in Java was developed for commercial use by the third author. The name of this software is ProRank—software for multi-criteria evaluation and decision support. It is planned to deliver a test version in As information base, we take attributes describing the exposure: PV classified the production volume and log Kow as measure for accumulation. See Table 1 for full information.

The indication of a second circle behind the full circle reminds us that there are equivalence classes, i. If there is only one maximal element, then it is called the greatest element. There is no greatest element. Minimal elements: elements that have no lower neighbour in a Hasse diagram are minimal elements. If there is only one minimal element, then it is called the least element.

Isolated elements: elements that are at the same time maximal and minimal elements, i. In Figure 2, there is no isolated element. Chain: subset of G where each element is comparable with each other.

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In Figure 2, CHl 80 R. They form the level Lmax By repeating this procedure, the level 1 is formed. Here the level 1 consists of CHL. The procedure can be performed as often as a maximal chain has elements only the representatives are counted. Therefore, in the case of Figure 2, the number of levels in 7. Antichain: a subset of G where no element is comparable. The presence of chains indicates a potential correlation among the elements of IB or the case that only one attribute is deciding the position; the presence of antichains can be considered as diversity of the hazard.

For example, the antichain, which is formed by the maximal elements, shows that these chemicals are hazardous but in a different way: CNB has the highest value of PV, DIA shows the highest value in the accumulation tendency expressed by log Kow , MAL has slightly higher and lower values but is still hazardous in both exposure aspects. The number of chains and the number of elements in the maximal antichain are related to each other: The famous Dilworth theorem states that the ground set can be partitioned into those numbers of chains that are equal to the number of elements in the largest antichain the width of a poset.

As the Hasse diagram in Figure 2 was obtained from two attributes, a scatter diagram of the 12 chemicals can be obtained, without information loss. Technically, the ability to be mapped onto a k-dimensional coordinate system is called a projection. Figure 3 shows the scatter plot. In a geometrical representation, elements comparable to x but worse in both aspects q1, q2 must be located in the shadow 1 see Figure 4 , whereas elements better in both aspects must be in the shadow 2. Elements in the remaining parts are incomparable.

In Figure 5, the Hasse diagram is shown where all four attributes are taken for the analysis.

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See Table 1. Partial Ordering and Hasse Diagrams 81 4. As discussed in step 2 in Section 2. In this case, high values stand for contribution to a high risk either just by the high production volume PV , or by a high toxicity LC or by a distinct accumulation tendency or finally by a high persistency. As the toxicity, for example, is expressed as LC50 value, we need the reverse orientation to let high values represent a high toxicity. The same is valid for biodegradation BD , the percentage per day degraded.

The maximal elements are the same as in Level 4. Isolated elements: Only one, namely MAL. There is a new feature in Figure 5. The directed graph contains three components, i. Certainly this Hasse diagram can be embedded into a space of real numbers of linear space dimension 4, because it is built from four attributes. There are many possibilities to do this; one model is shown in Figure 6. A systematic procedure, albeit accepting approximation, is provided by the approach partially ordered scalogram analysis with coordinates POSAC Shye, , Voigt et al.

Partial Ordering and Hasse Diagrams 83 us that the embedding must be possible without any approximations or neglecting of order relations. As the points in the four-dimensional space of the original attributes can be mapped onto a two-dimensional space of two latent variables, one may ask which of the original variables contributes to L1 or to L2.

This, however, is a difficult task and still an open problem in HDT. Approximately one may analyze the Spearman correlation or perform a correspondence analysis. Note that there are still many concepts, which could not be mentioned here, for example, linear extensions, which are a powerful albeit computationally almost intractable concept, to formulate the partial order in the setting of probability theory. Lerche et al. Besides the concept of linear extensions, new concepts of antagonism see Simon et al.

A recent development assumes that besides the partial order of objects, a classification exists, which is not necessarily derived from the attributes. Hence the partially ordered set of objects is additionally structured by equivalence relations. To perform the analysis, the dominance and separability degree was introduced and analyzed Restrepo et al. In Table 2, an excerpt of topics, the sizes of the data matrices as well as the references are given. You can read from the table that plenty of data analysis approaches have been performed during the past 7 years in the field of data availability on chemicals.

The size of the data matrices has to be commented. The matrices are all relatively small. For larger data matrices, multivariate statistical methods like cluster analysis have to be combined with the HDT. The chosen databases are all wellknown freely available Internet databases, which all comprise environmentally relevant chemicals. Note that we write q i instead of qi to facilitate the readability of the text.

Here, however, we restrict ourselves on aggregation schemes with freedom 1, i. Stability fields are subspaces of the G-space where a change of weights does not change the relative positions of any two incomparable objects. It is demonstrated that the number of incomparabilities is 88 R. The maximal objects and minimal objects in both diagrams remain more or less the same.

This means that we receive four stability fields. In both diagrams quotient sets , there is only one incomparability U. The crucial weights are calculated by one of the sub-modules of PyHasse see above , which actually contains 22 sub-modules and is as test version available from the first author. The crucial weights for g 1 is 0. We therefore calculate the Hasse diagrams for the stability fields, which are given in Figure 9. It can be demonstrated that all diagrams in the four stability fields are different from each other.

The maximal and minimal objects, however, are the same in all four Hasse diagrams. The equivalent objects are not listed for reasons of visibility. All conducted approaches show that the data situation on the chosen test set 17 publicly available in Internet databases concerning their data availability on four well-known and highly produced pharmaceuticals is far from being satisfactory.

The issue of 90 R. The graphical display by Hasse diagrams is very attractive as long as the number of objects is not too high. The resulting digraph allows many insights, which cannot be easily derived if other graphical methods are applied. Here we concentrated on the explanation of Partial Ordering and Hasse Diagrams 91 Hasse diagrams with the examples coming from the evaluation of chemicals and of databases.

What will be the development in the future? One of the most urgent deficits is the still missed field of statistical tests. Another direction is the further development of the concept of stability fields, where still many questions e.

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  • We conclude that partial order is a general applicable tool just because of its conceptual simplicity, and it seems that the concepts derived from partial order fit very well to chemical problems, as typical questions in chemistry are answered in the form of series, nephelauxetic series, soft and hardness series, series of electronegativity, etc. Here it seems as if the numerical value is not as important as just the position of a chemical entity within a series.

    Topological indices: Their nature and mutual relatedness, J. Basak, S. Birkhoff, G. Lattice theory. Application of the concept of partial order on comparative evaluation of environmental chemicals, Acta hydroch. Applying the concept of partially ordered sets on the ranking of near -shore sediments by a battery of tests, J. IV: Comparative regional analysis by Boolean arithmetics, Chemosphere 38, — Estimation of averaged ranks by a local partial order model, J.

    Stability of comparative evaluation, — example: Environmental databases, Chemosphere 33, — The concept of stability fields and hot spots in ranking of environmental chemicals. Partial order concepts in ranking environmental chemicals. Carlsen, L. Giving molecules an identity. De Baets, B. On rational cardinality — based inclusion measures, Fuzzy Set Syst. De Loof, K.

    On the random generation and counting of weak order extensions of a poset with given class cardinalities, Inf. Exploiting the lattice of ideals representation of a poset, Fundam. Informaticae 71, — Denoeux, T. Nonparametric rank-based statistics and significance tests for fuzzy data, Fuzzy set. Glass, L. Combinatorial and topological methods in nonlinear chemical kinetics, J. Hasse, H. Halfon, E. Computer-based development of large-scale ecological models: Problems and prospects. Is there a best model structure? I: Modelling the fate of a toxic substance in a lake, Ecol.

    Hasse diagrams and software development. An algorithm to plot Hasse diagrams on microcomputers and calcomp plotters, Ecol. On ranking chemicals for environmental hazard, Environ. Helm, D. O Helm, D. Evaluation of biomonitoring data. Lerche, D. A comparison of partial order technique with three methods of multicriteria analysis for ranking of chemical substances, J.

    Evaluation of the ranking probabilities for partial orders based on random linear extensions, Chemosphere 53, — Improved estimation of the ranking probabilities in partial orders using random linear extensions by approximation of the mutual probability, J. Luther, B. An approach to combine cluster analysis with order theoretical tools in problems of environmental pollution, MATCH Commun. Lutz, M. Naessens, H. Fuzzy Syst. Nemes, I. A possible construction of chemical reaction networks, Theor. Acta 46, — Todeschini, pp.

    Total ranking models by the genetic algorithm variable subset selection GA-VSS approach for environmental priority setting, Anal. Pudenz, S. Restrepo, G. Refrigerants ranked by partial order theory. Hryniewicz, O. Rival, I. The diagram. In: Graphs and Order Rival, I. Sabljic, A. Quantitative structure-activity relationships: The role of topological indices, Acta Pharm. Shye, S. Simon, U.

    Assessment of water management strategies by Hasse diagram technique. METEOR: a step-bystep procedure to explore effects of indicator aggregation in multi criteria decision aiding — application to water management in Berlin, Germany, Acta hydroch. Aspects of decision support in water management — example Berlin and Potsdam Germany I — spatially differentiated evaluation, Water Res.

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    Aspects of decision support in water management — example Berlin and Potsdam Germany II — improvement of management strategies, Water Res. Aspects of decision support in water management: Data based evaluation compared with expectations. Analysis of monitoring data of pesticide residues in surface waters using partial order ranking theory, Envir. Statistically approach for estimating the total set of linear orders. The influence on partial order ranking from input parameter uncertainty — Definition of a robustness parameter, Chemosphere 41, — Todeschini, R.

    Van der Walle, B. Fuzzy multi-criteria analysis of cutting techniques in a nuclear dismantling project, Fuzzy set. Voigt, K. In: The 94 R. Information systems and databases. Method of evaluation by order theory applied on the environmental topic of data-availability of pharmaceutically active substances. Chemical databases evaluated by order theoretical tools, Analytical and Bioanalytical Chemistry , — Application of computer-aided decision tools concerning environmental pollution with pharmaceuticals.

    Information quality of environmental and chemical databases exemplified by high production volume chemicals and pharmaceuticals, Online Inf. A multi-criteria evaluation of environmental databases using the Hasse diagram technique ProRank software, Environ. Softw 21, — Environmental contamination with endocrine disruptors and pharmaceuticals: An environmetrical evaluation approach.

    Comparative evaluation of chemical and environmental online databases, J. ProRank a software tool used for the evaluation of environmental databases. CD ROM. Chemical databases: An overview of selected databases and evaluation methods, Online Inf. Drinking water analysis systems in German cities: An evaluation approach combining Hasse diagram technique with multivariate statistics. Data availability on existing substances in publicly available databases — A data analysis approach. Data-analysis of environmental air pollutant monitoring systems in Europe, Environmetrics 15, — Hasse diagramm technique meets multivariate statistical methods meet search engines.

    Multivariate statistics applied to the evaluation of environmental and chemical data sources, Online Inf. Vukicevic, D. A graph theoretical method for partial ordering of Alkanes, Croatica Chemica Acta 80, — Weckert, M. Hasse diagram technique — a useful tool for life cycle assessments of refrigerants. Wilf, H. The Redheffer matrix of a partially ordered set, Electron. Zeigarnik, A. Application of graph theory to chemical kinetics. Topological specificity of multiroute reaction mechanisms, J.

    Carlsen Contents 1. Methodology 2. Applications 3. Conclusions Acknowledgments References 97 98 98 99 99 1. Both of these groups are obviously sub-divided into various rather different topics. Thus, the environmental factors to be taken into account may be the impact of the polluted site on the surrounding areas due to various dimensions, e. The socio-economic factors include direct cost of cleaning up and a cost-benefit analysis of doing something or doing nothing.

    In practice, this means that we have to take a wide range of factors into account that obviously a priori are incommensurable. Data handling in Science and Technology, Vol. Carlsen The possible assessment consequently turns into a multicriteria evaluation scheme. To reduce the number of parameters to be taken into account, primary analyses of specific dimensions leading to latent variables, meta-descriptors, are conducted, the idea being similar to that of the well-established of principal component analyses.

    Thus, a primary assessment of the objects under investigation based on connected parameters will lead to a set of meta-parameters that can be subsequently used for an analysis of the meta-dimension for the final assessment. The studies take its onset in the partial-order theory. Hence, the new methodology, hierarchical partial-order ranking HPOR Carlsen, , takes into account a range of otherwise incomparable parameters disclosing those polluted sites that on a cumulative basis appear to constitute the major risk towards both human and environmental health and thus potentially being those sites that a priori should be subject to appropriate confinement, remediation or cleanup.

    In the following sections, partial-order ranking POR including linear extensions LE and average rank as well as QSARs, as applied for the studies included in the present paper, will be shortly presented. If a system is considered, which can be described by a series of descriptors pi, a given site A, characterized by the descriptors pi A , can be compared to another site B, characterized by the descriptors pi B , through comparison of the single descriptors.

    Thus, site A will be ranked higher than site B, i. If no rank can be established between A and B, then these sites are denoted as incomparable, i. Therefore, POR is an ideal tool to handle incommensurable attributes. In POR—in contrast to standard multidimensional statistical analysis— neither any assumptions about linearity nor any assumptions about distribution properties are made. A "Semantic Web", which makes this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The " intelligent agents " people have touted for ages will finally materialize.

    In the following example, the text 'Paul Schuster was born in Dresden' on a Website will be annotated, connecting a person with their place of birth. The example defines the following five triples shown in Turtle Syntax. Each triple represents one edge in the resulting graph: the first element of the triple the subject is the name of the node where the edge starts, the second element the predicate the type of the edge, and the last and third element the object either the name of the node where the edge ends or a literal value e.

    In this example, all URIs, both for edges and nodes e. Additionally to the edges given in the involved documents explicitly, edges can be automatically inferred : the triple.

    Scientific Data Ranking Methods, Volume 27 - 1st Edition

    The concept of the semantic network model was formed in the early s by researchers such as the cognitive scientist Allan M. Collins , linguist M. Ross Quillian and psychologist Elizabeth F. Loftus as a form to represent semantically structured knowledge. When applied in the context of the modern internet, it extends the network of hyperlinked human-readable web pages by inserting machine-readable metadata about pages and how they are related to each other. This enables automated agents to access the Web more intelligently and perform more tasks on behalf of users.

    He defines the Semantic Web as "a web of data that can be processed directly and indirectly by machines". Many of the technologies proposed by the W3C already existed before they were positioned under the W3C umbrella. These are used in various contexts, particularly those dealing with information that encompasses a limited and defined domain, and where sharing data is a common necessity, such as scientific research or data exchange among businesses.

    In addition, other technologies with similar goals have emerged, such as microformats. Many files on a typical computer can also be loosely divided into human-readable documents and machine-readable data. Documents like mail messages, reports, and brochures are read by humans. Data, such as calendars, addressbooks, playlists, and spreadsheets are presented using an application program that lets them be viewed, searched and combined. Currently, the World Wide Web is based mainly on documents written in Hypertext Markup Language HTML , a markup convention that is used for coding a body of text interspersed with multimedia objects such as images and interactive forms.

    Metadata tags provide a method by which computers can categorize the content of web pages. In the examples below, the field names "keywords", "description" and "author" are assigned values such as "computing", and "cheap widgets for sale" and "John Doe". Because of this metadata tagging and categorization, other computer systems that want to access and share this data can easily identify the relevant values.

    With HTML and a tool to render it perhaps web browser software, perhaps another user agent , one can create and present a page that lists items for sale. There is also no way to express that these pieces of information are bound together in describing a discrete item, distinct from other items perhaps listed on the page. Layout details are left up to the browser, in combination with Cascading Style Sheets. But this practice falls short of specifying the semantics of objects such as items for sale or prices.

    Microformats extend HTML syntax to create machine-readable semantic markup about objects including people, organisations, events and products. The Semantic Web takes the solution further. HTML describes documents and the links between them. These technologies are combined in order to provide descriptions that supplement or replace the content of Web documents.

    The machine-readable descriptions enable content managers to add meaning to the content, i. In this way, a machine can process knowledge itself, instead of text, using processes similar to human deductive reasoning and inference , thereby obtaining more meaningful results and helping computers to perform automated information gathering and research. Berners-Lee posits that if the past was document sharing, the future is data sharing. His answer to the question of "how" provides three points of instruction. One, a URL should point to the data.

    Two, anyone accessing the URL should get data back. Three, relationships in the data should point to additional URLs with data. Tim Berners-Lee has described the semantic web as a component of "Web 3. People keep asking what Web 3. Web 3. Guardian journalist John Harris reviewed the Web 3. Some of the challenges for the Semantic Web include vastness, vagueness, uncertainty, inconsistency, and deceit. Automated reasoning systems will have to deal with all of these issues in order to deliver on the promise of the Semantic Web. This list of challenges is illustrative rather than exhaustive, and it focuses on the challenges to the "unifying logic" and "proof" layers of the Semantic Web.

    This is an area of active research. Standardization for Semantic Web in the context of Web 3. The term "Semantic Web" is often used more specifically to refer to the formats and technologies that enable it. These technologies are specified as W3C standards and include:. The functions and relationships of the components can be summarized as follows: [21].

    The intent is to enhance the usability and usefulness of the Web and its interconnected resources by creating Semantic Web Services , such as:. Such services could be useful to public search engines, or could be used for knowledge management within an organization. When no matches are found, the partial scoring for the given drug-event pair is 0 zero. In the opposite, with 3 or more publications found, the signal is scored with 1 one. Between 0 and 3 exclusive publications, the partial score will be of 0. Positive scores imply that scientific literature has been published on the association between the drug and the event.

    In these cases, the knowledge provider annotates the output with PubMed ID links of the discovered publications. The second strategy, involves a signal filtering co-occurrence process, evaluating the relationships between drugs and side effects that might have been reported previously in Medline literature, DailyMed [48] or DrugBank [49]. Data from these resources are previously indexed, including titles and abstracts from Medline, summary product characteristics from DailyMed, and ATC codes with potential adverse events from DrugBank.

    The algorithm then performs a chi-square test to determine if the co-occurrence of the given drug-event pair is different than what would be expected by chance. Similarly to the first algorithm, when interactions are found in the indexed knowledge base, the signal gets a scoring of 1 one. The annotation section of the output will include identifiers and connections to the relevant resources Medline, DailyMed or DrugBank. The third algorithm, signal substantiation, generates a network based on the drug-event pair containing the interactions with proteins targeted by the drug and associated events, and with biological pathways [50].

    This results in drug-target and event-target profiles that are searched for common sets of proteins, the intersecting portion of the graph. The output of this algorithm, a comprehensive list of proteins and pathways related to the drug-event pair, is annotated to the knowledge provider output along with the partial signal classification score.

    Once the data are processed through these algorithms, the results must be combined to better assess the plausibility of a given drug-event relationship. The fourth algorithm, evidence combination, uses the scores from the other knowledge providers to arrive at a degree of belief that takes available evidence into account. The algorithm uses the Dempster—Shafer theory [51] to evaluate the initial data combined with algorithm results to reach a measurable belief level that a particular drug-event pair has a low, medium or high risk. Algorithms weight and relevance in the final measurement can be customized to better fit the research context.

    This final risk measurement is the most important outcome of the performed pharmacovigilance research as it summarizes the relative risk for each drug-event pair in context of available knowledge. These algorithms have been deployed independently by EU-ADR project partners, which reinforce the proposed platform suitability to environments requiring software interoperability. Researchers upload and investigate drug-event datasets, create targeted drug studies and work with their peers through the available collaboration features. Each researcher has its own personal workspace, where they can browse existing datasets personal or shared ; upload custom drug-event pair datasets; or create drug-specific datasets, based on the overall platform data.

    A researcher interested in studying potential adverse reactions of patients treated with a given drug, XYZ for the purpose of this discussion, begins its study by automatically generating a dataset focused on the targeted drug. Signals classified as moderately or highly risky should be further investigated by analysing presented evidence and following hyperlinks to biomedical literature, as well as to external drug and biological data resources. Workflow results are labelled with Y in case sufficient evidence is found to support a potential drug-event relationship, or N otherwise. Despite the thorough research and development standards, post-market pharmacovigilance plays a key role in the assessment of existing medicines and creation of new drugs.

    Nevertheless, research over the last decades has focused on identifying and measuring specific adverse drug reactions in a post-marketing stage []. The holistic assessment of widespread electronic medical records empowers valuable insights over adverse drug events. Notwithstanding the value of these data per se , the development of new strategies to fully exploit the scientific background regarding reported events is vital. This manuscript details the creation of such strategy, proposing a pharmacovigilance-focused distributed platform and introducing an open framework for the better exploration of the wealth of available pharmacovigilance data by all pharmacogenomics stakeholders.

    The EU-ADR Web Platform is a unique tool that allows researchers to exploit the wealth of data from a European cohort, combined with independent drug-event datasets. In addition to being a step forward relative to existing solutions [55], the designed strategy accurately tackles multiple challenges behind the development of state-of-the-art software within the pharmacovigilance domain: scalability, interoperability, management, reproducibility, accessibility and security.

    A prototype implementation of this strategy is in place in the context of the European EU-ADR project, extending the interoperability amongst project partners. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Pharmacovigilance plays a key role in the healthcare domain through the assessment, monitoring and discovery of interactions amongst drugs and their effects in the human organism.

    Introduction Pharmacovigilance plays an essential role in the post-market analysis of newly developed drugs [1, 2]. Controlling a flexible amount of algorithms, each providing independent access to knowledge, with its independent set of features and offering access to closed functionalities.

    The integration of multiple knowledge providers requires that a solution akin to a "common language" must be setup so that the various tools and algorithms can interact with each other and with a central software choreographer. This brings two challengers: 1 how to store and make the collected data available to all researchers, and 2 how to organise and coordinate the set of available knowledge providers. The replication of all research steps, including data and used knowledge providers must be available for other researchers and for further auditing.

    All the data and features must be presented in a unified workspace, publicly available to all interested stakeholders. At last, interactions between knowledge providers, implemented software and researchers must be established through secure channels. Download: PPT. A Distributed Pharmacovigilance Platform The architecture of a distributed platform in the context of pharmacovigilance must tackle the six mentioned challenges - scalability, interoperability, management, reproducibility, accessibility and security.

    Figure 2. General architecture for the distributed pharmacovigilance platform. Knowledge base Internal Cloud-based The knowledge base stores all relevant data from the integrated and imported pharmacovigilance datasets. Data are stored in a cloud-based environment, moving the inherent complexities associated with secure data storage to en efficient cloud provider.

    Provider registry Internal Java The provider registry acts as the main knowledge provider controller. This is where new knowledge providers must register their interfaces and endpoints so that they can be made available for future use. Knowledge Providers External Independent XML-based standard The knowledge providers deliver independent access to various pharmacovigilance data analysis and exploration algorithms.

    Access to knowledge providers is service-based. Platform engine Internal Java The platform engine is the architecture core component, where all the tasks are executed and the interactions controlled. Web engine Internal Google Web Toolkit The web engine powers the distributed platform user interactions through an innovative web-based workspace.

    Real-world use of knowledge providers can result in an assorted amount of errors: general communication errors, such as failure to connect to a database, or domain-specific errors, such as invalid data. Each of the signals in the ranked list has a score that determines its relevant risk within the dataset. When the data are being assessed by the knowledge providers, the scoring attributes will provide each evaluated signal with a numeric value, between 0 zero and 1 one , measuring the relative relevance and impact according to the scientific evidence found to explain the interactions of a given drug-event pair.

    When a scientific explanation is found for a given set of drug-event pairs, the output is annotated with reliable evidence for the interaction, providing researchers with valuable knowledge and allowing them to evaluate the signal, share the results and reproduce their research in the future. These annotations appear in the form of connections to relevant resources, such as literature PubMed links , proteins UniProt links , chemical compounds SMILE codes or pathways Reactome links , among others.

    Knowledge Providers. Figure 3. From user input to system output the platform engine controls the execution of workflows as follows:. Knowledge Management. Dataset containing the complete list of ATC codes and respective drug names. Dataset listing the adverse events mined from the project's pharmacovigilance data.

    Researcher-submitted datasets containing statistical data regarding specific drug-event mapping conditions. Datasets with the results from the knowledge providers' algorithms. Results The pharmacovigilance context opens various opportunities to build new data analysis and exploration ecosystems. Pharmacovigilance Algorithms The initial service-oriented architecture implementation includes four knowledge providers, each with its own pharmacovigilance algorithm and made available as a Taverna workflow using secure services.

    Figure 5. EU-ADR Web Platform workspace interface for an undisclosed drug XYZ exploration scenario containing the signal list that results from distributed knowledge provider algorithm outputs and evidence combination statistical analysis. Conclusions Despite the thorough research and development standards, post-market pharmacovigilance plays a key role in the assessment of existing medicines and creation of new drugs. This step is further improved through the use of a cloud-based knowledge base, storing all gathered and submitted data, and ensuring availability, reliability and an eased access for all the architecture components.

    References 1. Pharmaceutical Medicine View Article Google Scholar 2. Shibata A, Hauben M Pharmacovigilance, signal detection and signal intelligence overview. Chicago, IL. View Article Google Scholar 3. Ema Ema Annual Report. European Medicines Agency. Pharmacoepidemiol Drug Saf PubMed: View Article Google Scholar 5. Xu L, Anchordoquy T Drug delivery trends in clinical trials and translational medicine: Challenges and opportunities in the delivery of nucleic acid-based therapeutics.