Glossary

From Opasnet
Jump to: navigation, search

Glossary contains a list of terms that have a particular meaning in the context of environmental health assessment.

If you want to contribute by writing a glossary term please see Help:Writing glossary terms.

Many of these terms can also be found in the Intarese project glossary (restricted access).

The glossary is divided into two parts: a shorter list of "official" terms used in open assessment; and a longer list of terms that each have a dedicated page. These list overlap.

Terms in open policy practice

Finnish terms are in parenthesis.

assess (arvioida)
to estimate a real or hypothetical situation and combine that to value judgements by stakeholders; to make an assessment.
assessment (arviointi)
knowledge support for practical needs
capability (kykenevyys)
together with rights, one of the four moral philosophical approaches used in open assessment. Capability is a measure of what people can do in their own living environment, e.g. whether they have access to basic needs such as education, housing, and freedom of speech (human rights), and also whether they can pursue their own interests. See also fairness, utility, and virtue.
causality (syysuhteet)
A principle of open policy practice that policy support should be based on causal understanding about the impacts of policy options on the outcomes desired. Impact assessments are practical implementations of this principle.
critique (kritiikki)
A principle of open policy practice that all information must be available for critique and that all statements not consistent with observations or not relevant in their context are invalidated and not used for making conclusions.
effectiveness (vaikuttavuus)
capability (or likelihood) of achieving intended outcomes
estimate (estimoida)
to make a prediction about a property (typically a variable) that has an unknown value and that can, at least in theory, be observed in the future.
evaluate (arvostella)
to make a judgement about the goodness of an assessment (or another information product) in a practical sense as compared to its use purpose.
evaluation (seuranta)
analysis of the capability (or likelihood) of achieving intended outcomes
fairness (reiluus)
one of the four moral philosophical approaches used in open assessment. Fairness is about whether the utilities or restrictions are distributed in a fair way in the society. See also capabilities and rights, fairness, utility, and virtue.
impact (vaikutus)
Impacts are estimates about what would happen due to a decision or action; outcomes are what actually happens. In an impact model, impacts are variables that describe phenomena of interest (as compared to other variables that are just needed to estimate impacts). Sometimes also called indicator.
intentionality (tavoitteellisuus)
A principle of open policy practice that the management of work should be based on understanding of the intentions of the person for whom the work is done.
method (metodi)
Typically, a method is a "how-to-do" instruction to calculate a variable. It has a similar structure as a variable except that not all upstream dependencies are known, so that the answer cannot be estimated (until method is used within the context of an assessment, where all case-specific dependencies are known).
openness (avoimuus)
A principle of open policy practice that all information work is constantly open for anyone to read, contribute, and criticise.
output (tuotos)
the product of an assessment (typically a report).
outcome (lopputulos)
things that actually happen, especially changes and effects caused or stimulated by an action. See also impact.
ovariable (ovariable)
the name of a variable in the context of R tools, technically an S4 object. A different name is used, because "variable" has also other meanings in the context of R language.
policy (yhteiskunnallinen päätös)
decisions and actions with societal relevance
practices (käytäntö)
(common) ways of dealing with things
reuse (uusiokäyttö)
A principle of open policy practice that information objects should be produced in such a way and format that they are as easily as possible reusable for new purposes.
rights (oikeudet)
together with capabilities, one of the four moral philosophical approaches used in open assessment. See also fairness, utility, and virtue.
shared information objects (kohteellisuus)
A principle of open policy practice that information work should be performed by producing a shared information object, for example a wiki page.
utility (hyöty)
one of the four moral philosophical approaches used in open assessment. It is about how much something is needed or wanted by someone. Utility can often be measured by money. See also capabilities and rights, fairness, and virtue.
valuate (arvottaa)
to make value judgement about the goodness of a variable or action in a moral sense. --# : How to use terms value judgement, valuation, value variable? Do we need all, wouldn't one verb and one noun be enough? --Jouni 08:29, 11 August 2012 (EEST)
variable (muuttuja)
A standardised piece of information in an open assessment. It has an own wiki page.
virtue (hyve)
one of the four moral philosophical approaches used in open assessment. It looks at the actions and their intentions, not outcomes, as the basis for moral statements. See also capabilities and rights, fairness, and utility.


  • Terms that do not have an 'official' use in open policy practice (although they may have previously had): endpoint, other variable, indicator, key variable, step, phase, tool, parent & child --> use (upstream) dependencies and reverse dependencies instead.

Main glossary

Acceptable daily intake

Acceptable daily intake (ADI) is the estimated maximum amount of an agent, expressed on a body mass basis, to which an individual in a (sub)population may be exposed daily over its lifetime without appreciable health risk. Also known as tolerable daily intake (TDI) or reference dose.

Acceptable risk

Acceptable risk is a risk management term. The acceptability of risk depends on scientific data, social, economic, and political factors, and on the perceived benefits arising from exposure to an agent.[1]

Acknowledgements

Acknowledgements is a particular discussion on the Discussion page of an object. It describes the contributions of each contributor of the object until the time when the acknowledgement is written. It also describes the resource contributors (such as research grants).

Additional risk

Additional risk the additional proportion of total animals that respond in the presence of the dose, or the probability of esponse at dose d, P(d), minus the probability of response in the absence of exposure, P(0). Also known as extra risk.[1]

Adverse effect

Adverse effect is a change in the morphology, physiology, growth, development, reproduction or life span of an organism, system, or (sub) population that results in an impairment of functional capacity, an impairment of the capacity to compensate for additional stress, or an increase in susceptibility to other influences.[1]

Agent

Agent is a chemical, biological, or physical entity that contacts a target.

Akaike information criteria

Akaike information criteria is a statistical procedure that provides a measure of the goodness-of-fit of a dose-response model to a set of data.[1]

Analysis

Analysis is viewed here in a sense of examination of something, together with thoughts and judgments about it for the purpose of a risk assessment and its variable definition (refers not to chemical analysis, i.e. separation of substance into parts). It may include optimizing scenarios.

Answer

Answer answers this question: What is the answer to the research question?

It is an expression of the state of the part of reality that the object describes. It is the outcome of the contents under the definition attribute. In open assessment it is an attribute of information objects. Assessment

Assessment is a process for describing a particular piece of reality in aim to fulfill a certain information need in a decision-making situation. The word assessment can also mean the end product of this process, i.e. an assessment report of some kind. Often it is clear from the context whether the term assessment refers to the making of the report or the report itself. Methodologically, these are two different objects, called the assessment process and the assessment product, respectively.

Assessment factor

Assessment factor is a numerical adjustment to extrapolate from experimentally determined (dose-response) relationships to estimate the agent exposure below which an adverse effect is not likely to occur.[1]

Asymptotic test

Asymptotic test is a statistical tests that approach known properties as sample sizes increase.[1]

Attribute

Attribute is a property, an abstraction of a characteristic of an entity or substance. In open assessment in particular a characteristic of an assessment product (assessment, variable or class), and assessment process (method). In open assessment all these objects have the same set of attributes:

Bayes' theorem

Bayes' theorem (also known as Bayes' rule or Bayes' law) is a result in probability theory that relates conditional probabilities. If A and B denote two events, P(A|B) denotes the conditional probability of A occurring, given that B occurs. The two conditional probabilities P(A|B) and P(B|A) are in general different. Bayes theorem gives a relation between P(A|B) and P(B|A).
An important application of Bayes' theorem is that it gives a rule how to update or revise the strengths of evidence-based beliefs in light of new evidence a posteriori.
As a formal theorem, Bayes' theorem is valid in all interpretations of probability. However, it plays a central role in the debate around the foundations of statistics: frequentist and Bayesian interpretations disagree about the kinds of things to which probabilities should be assigned in applications. Whereas frequentists assign probabilities to random events according to their frequencies of occurrence or to subsets of populations as proportions of the whole, Bayesians assign probabilities to propositions that are uncertain. A consequence is that Bayesians have more frequent occasion to use Bayes' theorem. The articles on Bayesian probability and frequentist probability discuss these debates at greater length.

Bayesian network

Bayesian network (or a Bayesian belief network, BBN) is a probabilistic graphical model that represents a set of variables and their probabilistic independencies. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. The term "Bayesian networks" was coined by Pearl (1985) to emphasize three aspects:
  1. The often subjective nature of the input information.
  2. The reliance on Bayes's conditioning as the basis for updating information.
  3. The distinction between causal and evidential modes of reasoning, which underscores Thomas Bayes's posthumous paper of 1763.[2]
Formally, Bayesian networks are directed acyclic graphs whose nodes represent variables, and whose arcs encode conditional independencies between the variables. Nodes can represent any kind of variable, be it a measured parameter, a latent variable or a hypothesis. They are not restricted to representing random variables, which represents another "Bayesian" aspect of a Bayesian network. Efficient algorithms exist that perform inference and learning in Bayesian networks. Bayesian networks that model sequences of variables (such as for example speech signals or protein sequences) are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams.

Benchmark concentration

Benchmark concentration (BMC) is the concentration of a substance that is associated with a specified low incidence of risk of a health effect, or the concentration associated with a specified measure or change of a biological effect.[1]

Benchmark dose

Benchmark dose (BMD) is an exposure due to a dose of a substance associated with a specified low incidence of risk, generally in the range of 1% to 10%, of a health effect; or the dose associated with a specified measure or change of a biological effect.[1]

Benchmark dose lower confidence limit

Benchmark dose lower confidence limit (BMDL) is a lower one-sided confidence limit on the BMD.[1]

Benchmark response

Benchmark response (BMR) is the response, generally expressed as in excess of background, at which a benchmark dose or concentration is desired.[1]

Bernoulli distribution

Bernoulli distribution is a theoretical distribution of the number of successes in a finite set of independent trials with a constant probability of success. It is discrete distribution having two possible outcomes labelled by n = 0 and n = 1in which n = 1 ("success") occurs with probability p and n = 0 ("failure") occurs with probability q ≡ 1 - p, where 0 < p < 1.[1]

Beta-binomial distribution

Beta-binomial distribution is a statistical distribution of clustered values, e.g., measures on offspring in a litter, where the average proportions of an event for clusters are described by a beta distribution and the proportions of events in a cluster are described by a binomial distribution.[1]

Binomial distribution

Binomial distribution is the statistical distribution of the probabilities of observing 0,1,2,- - - ,n events in a sample of n independent trials each with the same individual probability that the event occurs.[1]

Bootstrap

Bootstrap is a statistical technique based on multiple re-sampling with replacement of the sample values or re-sampling of estimated distributions of the sample values that is used to calculate confidence limits or perform statistical tests for complex situations or where the distribution of an estimate or test statistic cannot be assumed.[1]

Boundary

The term boundary refers to the assessment and variable boundaries, i.e. the outer limits of anything.

Cancer potency

Cancer potency a number that estimates the cancer risk (incidence) for a lifetime exposure to a substance per unit of dose which is generally expressed as mg / kg body wt / day. Also known as cancer slope factor.[1]

Categorical data

Categorical data is a results obtained where observations or measurements on individuals or samples are stratified according to degree or severity of an effect, e.g., none, mild, moderate, or severe.[1]

Categorical default factor

Categorical default factor is a factor based on common characteristics of a group of compounds, e.g., physical/chemical properties or pathways of metabolism.[1]

Data

Data are e.g. population data, mortality background data, biomonitoring data. Data are needed for defining and calculating variables but stem from outside the risk assessment process. Input for a variable derived by a causal linkage to another variable is not called data but is the result of the other variable. Data can be "raw" data or accumulated to different degrees including e.g. the mean and the standard deviation or a distribution.

Causal diagram

During the scoping phase a causal diagram should be drawn that describes all variables of the assessment including their causal relationships. It consists of the variables of the assessment. At first all variables are taken into account that seem relevant. While checking for causality it may turn out that more variables are needed and the pictures becomes more complex. Then a simplification process starts and only the relevant links and variables are kept.
The process can be started on a quite general level (e.g. from the viewpoint of a certain stressor or health outcome) or it can be started on a quite detailed level (e.g. from the viewpoint of PM2.5 concentration and its effects on health in Copenhagen).

Causality

Causality means that there is a causal influence between two variables (or objects): if the value of the one upstream is changed, the object downstream changes as well. Causal relationships are represented as arrows in causal diagrams. However, the lack of a causal relationship, i.e. a lack of an arrow between two variables is a stronger statement than an arrow. One operationalization of causality is a Bayesian belief network. Causality is also called dependency.
A risk assessment method based on the full-chain approach utilises causality as a major concept. This implies that the assessment products produced in the assessments should be causal network descriptions that cover the relevant phenomena from emissions to exposures to health effects and their impacts in accordance with the chosen endpoints and purpose. However, it should be emphasized that the method does not only describe issues that are associated with the full chain. It describes those issues that cause effects along the full chain, and it describes how the causes and effects are related. This, of course, makes risk assessment a challenging, or even difficult, process. Strict emphasis on causality, however, should be the way to e.g. estimate the impacts of policies on emissions and consequently to health effects. For further details, see Guidance and methods for indicator selection and specification.

Chemical specific adjustment factor

Chemical specific adjustment factor is a factor based on quantitative chemical-specific toxicokinetic or toxicodynamic data, which replaces some or all of the default uncertainty factor.[1]

Chi-square test

Chi-square test is a statistical test used to examine the deviation of an observed number of events from an expected number of events.[1]

Class

Class is a set of items (objects) that share the same property or properties. The membership in a class is determined by an inclusion criterion. The property is utilised as a part of all objects that fulfill the criterion. Classes can be used in describing general information that is shared by more than one object. Class efficiently reduces the redundancy of information in the open assessment system. This improves the inter-assessment efficiency of the assessment work.

Clustered data

Clustered data are measurements collected on some grouping of individuals, e.g., litters in reproductive and developmental studies.[1]

Conclusion

Conclusion of a risk assessment refers to an arrangement or agreement that introduces either a changed state of affairs or verifies business as usual (BAU) as a best option for the assessment scope. The (new) verified state of affairs is likely to last for some time.[3]

Confidence interval

Confidence interval (Two-Sided) is an estimated interval from the lower to upper confidence limit of an estimate of a parameter. This interval is expected to include the true value of the parameter with a specified confidence percentage, e.g., 95% of such intervals are expected to include the true values of the estimated parameters.[1]
Confidence interval (One-Sided) is an interval below the estimated upper confidence limit, or interval above the estimated lower confidence limit, that is expected to include the true value of an estimated parameter with a specified confidence ( percent of the time).[1]

Confidence limit

Confidence limit is an estimated value below (or above) which the true value of an estimated parameter is expected to lie for a specified percentage of such estimated limits. [1]

Constrained dose-response model

Constrained dose-response model estimates of one or more parameters of the model restricted to a specified range, e.g., equal to or greater than zero.[1]

Continuous data

Continuous data effects Measured on a continuum, e.g., organ weight or enzyme concentration, as opposed to quantal or categorical data where effects are classified by assignment to a class.[1]

Convergence

Convergence estimates of a parameter approach a single value with increasing sample size or increasing number of computer iterations.[1]

Convex

Convex is region of a dose-response relationship that curves upward, i.e., the slope becomes steeper with increasing dose.[1]

Correlated binomial distribution

Correlated binomial distribution is a clustered data where the individual values in a cluster, e.g., a litter, each have the same probability of expressing an effect.[1]

Covariate

Covariate is an independent variable other than dose that may influence the outcome of an effect, e.g., age, body weight, or polymorphism.[1]

Critical effect

Critical effect the adverse effect, or its known precursor, that is relevant to human risk assessment and that occurs in the dose/concentration scale in the most sensitive animal species.[1]

Cubic

Cubic is an effect is a function of a measure raised to the third power.[1]

Data

Data are e.g. population data, mortality background data, biomonitoring data. Data are needed for defining and calculating variables but stem from outside the risk assessment process. Input for a variable derived by a causal linkage to another variable is not called data but is the result of the other variable. Data can be "raw" data or accumulated to different degrees including e.g. the mean and the standard deviation or a distribution.

Decision

Decision is a special kind of variable: it answer a question like this: "What are different decisions that decision maker X can make in situation Y, and what are different options of each decision?" Decision maker X may be a single individual, a decision making body with several individuals, or a set of separate decision makers, who each can decide about some but not all decisions. In such a situation, an especially interesting part of the related assessment is to look at the interactions of the decisions by different decision makers, none of which can fully control the decision situation.
The decisions have a special role in causal diagrams, as they list such specific structural parts of variables in a causal diagrams that can be modified by a decision maker. Without a decision, the causal diagram describes the business-as-usual (BAU) situation. A decision variable describes how the situation changes if a decision maker chooses an option over another options of a decision.

Decision theory

Decision theory is an area of study of discrete mathematics that models human decision-making in science, engineering and indeed all human social activities. It is concerned with how real or ideal decision-makers make or should make decisions, and how optimal decisions can be reached.
Most of decision theory is normative or prescriptive, i.e. it is concerned with identifying the best decision to take, assuming an ideal decision maker who is fully informed, able to compute with perfect accuracy, and fully rational. The practical application of this prescriptive approach (how people should make decisions) is called decision analysis, and aimed at finding tools, methodologies and software to help people make better decisions. The most systematic and comprehensive software tools developed in this way are called decision support systems.
Since it is obvious that people do not typically behave in optimal ways, there is also a related area of study, which is a positive or descriptive discipline, attempting to describe what people will actually do. Since the normative, optimal decision often creates hypotheses for testing against actual behaviour, the two fields are closely linked. Furthermore it is possible to relax the assumptions of perfect information, rationality and so forth in various ways, and produce a series of different prescriptions or predictions about behaviour, allowing for further tests of the kind of decision-making that occurs in practice.

Default value

Default value is a pragmatic, fixed or standard value used in the absence of relevant data.[1]

Degrees of freedom

Degrees of freedom is for dose-response model fitting, the number of data points minus the number of model parameters estimated from the data.[1]

Delta method

Delta method is a variance of a function of random variables approximated from the derivatives of the function with respect to the random variables and the variances of the random variables.[1]

Dichotomous data

Dichotomous data is a quantal data where an effect for an individual may be classified by one of two possibilities, e.g., dead or alive, with or without a specific type of tumour.[1]

Discussion

Discussion is a method to organise information about a topic into a form of hierarchical thread of arguments trying to resolve whether a statement is true or not. In discussion, anyone can raise any relevant points about the topic. Discussion is organised using the pragma-dialectical argumentation theory[4]. A discussion usually consists of three parts: 1) the statement(s); 2) the actual discussion, organised as hierarchical threads of arguments; and 3) the resolution of discussion. Once a discussion reaches a resolution, the resolution should be accordingly portrayed within the object description.

Dispersion

Dispersion is a variation (differences) from a central (mean or median) value.[1]

Dose

A dose is the amount of agent that enters a target after crossing an exposure surface. If the exposure surface is an absorption barrier, the dose is an absorbed dose/uptake dose (see uptake); otherwise, it is an intake dose. See also intake.[5]

Dose-response

Dose-response is a relationship between the amount of an agent administered to, taken up or absorbed by an organism, system or (sub) population and the change developed in that organism, system or (sub) population in reaction to the agent. [1]

Dose-response assessment

Dose-response assessment is an analysis of the relationship between the total amount of an agent administered to, taken up or absorbed by an organism, system or (sub)population and the changes developed in that organism, system or (sub)population in reaction to that agent, and inferences derived from such an analysis with respect to the entire population.[1]

Dose-response model

Dose-response model is a mathematical relationship (function) that relates (predicts) a measure of an effect to a dose.[1]

Dose-response trend

Dose-response trend is a relationship between incidence or severity of a biological effect and a function of dose. Simply the slope for a linear dose-response.[1]

EDx

EDx is an effective dose associated with a biological effect in x% of the individuals. Dose may be the external exposure often expressed in mg per day of the substance per kg body weight raised to a power (generally 1, 3/4, or 2/3) or area under the curve (AUC) in blood or target tissue 20 where the substance remains in the body over a period of time.[1]

Encyclopedia article

Encyclopedia article is a descriptive page about a topic in Opasnet. These articles are useful for describing general topics or background information. It has a free structure unlike e.g. variables or assessments. The recommendations of Wikipedia also apply to encyclopedia articles in Opasnet. Articles are categorised into a category called Encyclopedia article.

Endpoint variable

Endpoint variables are variables that describe phenomena which are outcomes of the assessed causal diagram or network, i.e. there is no variables downstream from an endpoint variable according to the scope of the assessment. In practice endpoint variables are most often also chosen as indicators. See also causality and assessment.

Estimate

Estimate is an empirical value derived from data for a parameter.[1]

Excess risk

Excess risk is a proportion of individuals or animals observed or estimated to possess an effect in addition to the spontaneous background risk. [1]

Exposure

Contact between an agent and a target. Mainly used for air pollution. Exposure is usually described as concentration of the agent in the medium around the target during a defined duration (exposure duration).[5]

Exposure-response function

Exposure-response function (ERF) (or exposure-response relationship) is the relationship between the exposure of a given organism, system, or (sub)population to an agent in a specific pattern during a given time and the magnitude of a continuously graded effect to that organism, system, or (sub)population.
This term has several related terms that may have slightly different meaning. Effect and response are interchangeable words. Also the word function is used instead of relationship. In Opasnet, we use the term exposure-response function (or ERF) as the generic term for different kinds of relationships. Often the exposure metric is more specifically defined in an alternative term. Two common examples:
Concentration-effect relationship
Relationship between the exposure, expressed in concentration, of a given organism, system, or (sub)population to an agent in a specific pattern during a given time and the magnitude of a continuously graded effect to that organism, system, or (sub)population. The concentration is measured at a defined site. [5]
Dose-response relationship
Relationship between the amount of an agent administered to, taken up by, or absorbed by an organism, system, or (sub)population and the change developed in that organism, system,or (sub)population in reaction to the agent. [5]

Fact

Fact is a statement that has previously been extensively attacked without success and currently could be attacked by anyone but nobody does. Also, new facts can be deduced from existing facts, if the deduction rules are themselves facts.

Falsification

Falsification is an attempt to falsify a statement. Falsifiability (or refutability or testability) is the logical possibility that an assertion can be shown false by an observation or a physical experiment. That something is "falsifiable" does not mean it is false; rather, it means that it is capable of being criticized by observational reports. Falsifiability is an important concept in science and the philosophy of science.
Some philosophers and scientists, most notably Karl Popper, have asserted that a hypothesis, proposition or theory is scientific only if it is falsifiable.
For example, "all men are mortal" is unfalsifiable, since no finite amount of observation could ever demonstrate its falsehood: that one or more men can live forever. "All men are immortal," by contrast, is falsifiable, by the presentation of just one dead man. However, the unfalsifiable "all men are mortal" can be the logical consequence of a falsifiable theory, such as "all men die before they reach the age of 150 years". Thus, unfalsifiable statements can almost always be put into a falsifiable framework. The falsifiable does not exclude the unfalsifiable, it embraces and exceeds it.
Not all statements that are falsifiable in principle are so in practice. For example, "it will be raining here in one million years" is theoretically falsifiable, but not practically.

Flipism

  1. Flipism is a method to remove the mental block related to the act of decision-making, so that the post-decision preferences can be revealed before the decision is actually made.
  2. Flipism is an imaginary philosophy, originally published in the Walt Disney cartoon Flip Decision[6] by Carl Barks. In flipism, all decisions are made by flipping a coin. This can be seen as a normative decision theory, although it does not fulfil the criteria of rationality. Flipism can be seen as a sarcastic metaphor about how rational decision-making is overwhelmed by anchoring to religious beliefs.

Gamma distribution

Gamma distribution is a unimodal statistical distribution ( relative proportion of responders as a function of some measure ) that is restricted to effects greater than or equal to zero that can describe a wide variety of shapes, e.g., flat, peaked, asymmetrical.[1]

Gaussian (normal) distribution

Gaussian (normal) distribution is a unimodal symmetrical (bell-shaped) distribution where the most prevalent value is the mean (average) and the spread is measured by the standard deviation. Mathematically, the distribution varies from minus infinity with zero probability to plus infinity with zero probability.[1]

Generalized estimating equation

Generalized estimating equation (GEE) is a statistical technique used for estimating parameters that requires only specification of the first two moments of the distribution of the estimator as opposed to a complete specification of the distribution.[1]

Goodness-of-fit

Goodness-of-fit is a statistic that measures the dispersion of data about a dose-response curve in order to provide a test for rejection of a model due to lack of an adequate fit, e.g., a P-value < 0.1.[1]

Group

A group in open assessment means one or more individuals who participate in some activity, e.g. performing or reading an assessment. All information objects have a research question about an issue X. Groups are crucial because all research questions are actually implicitly in this format: "What can we as a group know about issue X?" The group considering a particular issue may be explicitly described, but it may also be implicit. In the latter case, it typically means anyone who wants to participate, or alternatively, the whole mankind.

Hatchery

Hatchery is a page type in Opasnet. On a hatchery page, new ideas are being developed before creating formal objects out of them. The aim is to facilitate the process of creating and throwing ideas before they clearly belong to or form a formal object.

Hazard

Hazard is an inherent property of an agent or situation having the potential to cause adverse effects when an organism, system, or (sub)population is exposed to that agent.[5]

Hazard identification

Hazard identification is the identification of the type and nature of adverse effects that an agent has as inherent capacity to cause in an organism, system or (sub) population. [1]

Health impact

Health impact is the overall effect, direct or indirect, of a policy, strategy, programme or project on the health of a population.[7]

Health impact assessment

Health impact assessment is an assessment method that is used to estimate the health impacts of a particular event or policy. In Europe, it is most widely used in UK, Finland, and the Netherlands.

Health technology assessment

Health technology assessment is activity for evaluating and promoting good, evidence-based methodologies and practices in health care systems and clinical practice. The aim is to improve effectiveness and efficacy of health care systems.

Heande

Heande is a password-protected website for scientific mass collaboration. Technically, it is a wiki workspace that consists of descriptive pages about scientific questions, attempts to answer the questions, and current hypotheses about the answers. The current answers are also stored in a quantitative form into a database called Opasnet Base. Opasnet Base is also used to store, analyse, distribute, and archive original research data. The methods and information structures in Heande are identical to those in Opasnet. The main difference is that while the participation and usage of information in Opasnet is free, the users of Heande must accept its basic rule: the usage of information within Heande is free, but if you want to publish anything that is found in Heande outside Heande, you must make an explicit agreement about publishing with the original producers of that information. Heande is maintained and developed by the National Institute for Health and Welfare (the Department of Environmental Health, located in Kuopio, Finland).

Editing Hill equation

Hill equation is a dose-response curve, frequently used for enzyme kinetics, that monotonically approaches an asymptote (maximum value) as a function of dose raised to a power. [1]

Hybrid model

Hybrid model is for continuous data establishes abnormal values based on the extremes in controls (unexposed individuals or animals) and estimates the risk of abnormal levels as a function of dose.[1]

Impact assessment

Impact assessment is a combination of procedures, methods and tools by which a policy, program or project may be judged as to its potential effects on the health of a population, and the distribution of those effects within the population. Includes benefits in addition to risks. Contrary to risk assessment impact assessment includes damages which are certain, i.e. have a probability of 1.[7]

Incidence

Incidence is a proportion or probability of individuals or animals exhibiting an effect that varies from zero to one, sometimes expressed as a percent from 0% to 100%.

Inclusion principle

Inclusion principle is a normative rule for handling contributions of an open assessment or other information work. It says that any contribution must not be ignored during the work but all relevant points from the contributions must be included into the information object. The only situation where there is no need to include anything is a situation where it can be shown that the contribution is totally irrelevant, i.e. there are zero relevant points that should be included. (Even in this case, the contribution is archived together with a comment that shows its irrelevance.) In a case where the contribution is relevant but can be shown to be false, the information about the falseness of the contribution should be included in the information object.
The result of the information object must not be in conflict with any of the contributions. For example, let's think of an object that has a current result A. Someone brings up a hypothesis B that is in conflict with A. If B is relevant, it must be included. If B cannot be shown to be wrong, and if B does not show A to be wrong, the result must be updated into a form "A or B". This procedure does not depend on how many people are supporting the original hypothesis A or the alternative hypothesis B.

Independence

Independence is the result in one animal or individual does not influence the result in another animal or individual.[1]

Index

Index is a set of locations that logically belong together based on their similar nature. For example, "time" is an index with locations like "2007" and "9.6.2008". Other typical indices include year, sex, diagnosis, and age. Indices are used to operationalise variables and assessments. In Opasnet Base, indices are used to explain results stored in the database. Indices and locations are also used to connect cells with the same locations from different variables.

Index conversion function

Index conversion function (ICF) is a method describing how one index can be converted to another in a particular context. To this aim, a weight variable is needed. It is indexed by the two indices, and the values in cells represent the fraction of the total amount of substance (e.g., area, population) in the intersection determined by the two indices. For example, a country may be treated as a whole, or it may be divided into (i.e., indexed by) counties or municipalities. In this case, the three indices are "crisp" in the sense that a municipality belongs to exactly one county, and a county belongs to exactly one country. There can also be "overlapping" indices. For example, for a given population, a certain fraction of (not all) men or women belong to a particular age group. If the result domains of the two indices are not the same, the fraction of substance that goes beyond the second index must be specified.

Indicator

An indicator comprises a characteristic or condition which can be described or measured in a way which provides information about some other characteristic or condition which is, itself, not amenable to direct observation or measurement. Environmental Health Indicators are usually numbers that represent a certain state of the environment, exposure, health state and/ or policy actions. An indicator is a variable that is of a particular interest, for example those that are reported in the risk assessment report. See also variable.

Intake

Intake is the amount (mass) of an agent crossing an outer exposure surface of a target without passing an absorption barrier, i.e., through ingestion or inhalation. See also dose.[5]

Intake fraction

Intake fraction (also iF) is the fraction of emission that is eventually inhaled or ingested by someone in the target population (population of interest) - integrated over time and space.
Intake fraction can be estimated with different methods, such as
  1. iF based on measured concentration fields
  2. iF based on exposure monitoring
  3. iF based on shortcuts

Intake rate

Intake rate is the rate (mass / time unit) at which an argent crosses the outer exposure surface of a target (humans) during ingestion or inhalation.[5]

Intarese framework

The INTARESE framework comprises all relevant aspects and builds on all relevant methods to provide guidance for a comprehensive integrated environmental health impact assessment.[8] It recognised the concept of the DPSIR, DPSEEA and MEME frameworks but provides a more flexible and comprehensive framework. The key attributes are:
  • the full chain approach, including variables and causal relationships linking the different steps in the chain from source to impact
  • the logical process of assessment (steps involved in the execution of the assessment, tasks and responsibilities of the parties involved)
  • information input and models (data input and processing, applying models, transforming intermediate variables into meaningful indicators and summary indices)
  • appraisal of the information from multiple perspectives

Integrated assessment

Integrated assessment is a multidisciplinary process of synthesizing knowledge across scientific disciplines with the purpose of providing all relevant information to decision makers to help to make decisions.
The integration takes place:
  • integration across causal chains
  • integration of aggregated indicators
  • integration of outcomes: disease, money perception
  • integration of many pollutants
  • integration across many risk assessments
  • integration across policy studies/areas
  • integration across scientific disciplines
  • integration across sources
  • integration across pollutants/stressors
  • integration across impacts/receptors
  • integration across environmental media
  • integration across scales [8]

Integrated risk assessment

Integrated risk assessment is the assessment of risks to human health from environmental stressors based on a whole system approach. It thus endeavours to take account of all the main factors, links, effects and impacts relating to a defined issue or problem.[9]

Intended user

Intended user is a potential user of an assessment belonging to a key target group, as defined by the participants of the assessment.

Intercept term

Intercept term is the estimated value at zero dose or the dose corresponding to a zero effect.[1]

Issue framing

Issue farming is the process of defining the issue that will be assessed. Its aim is to specify the scope and key elements and boundaries of the issue to be considered, and to provide the explicit rationale for the assessment. Issue framing should specify:
  • the purpose of the assessment (why it is being done, for whom)
  • the scope and boundaries of the issue (what is included and what is not)
  • the main factors and links to be considered in the assessment, variables, indicators and causality
  • the target area, time period and population (including specific age, gender or social groups)
  • key assumptions (e.g. value judgements and stakeholder interests that have shaped the specification of the issue
  • the process by which the issue was defined and agreed (who was involved, what consultation methods were used).

Least squares

Least squares is a statistical procedure that estimates the values of dose-response parameters such that the sum of squares of deviations of data points from their estimated values is minimized, i.e., minimizes the estimated variance.[1]

Lecture

Lecture is a universal object. It contains a piece of information that is to be mediated to a defined audience and with a defined learning objective. It can also be seen as a process during which the audience learns, instead of being a passive recipient of information.

Likelihood function

Likelihood function is a relative probabilities that various values of population parameters would arise from the sample observations.[1]

Likelihood ratio

Likelihood ratio is a ratio of the probability that the observed data arise from a set of model parameters relative to the maximum probability that arises from the set of maximum likelihood estimates.[1]

Linear dose-response model

Linear dose-response model the amount of change in a response is proportional to the amount of change in some function of dose.[1]

Linearized multistage model

Linearized multistage model is a dose-response model based on the multistage model of carcinogenesis that is restricted to a form that is approximately linear at low doses.[1]

Local maximum

Local maximum is a mathematical solution that maximizes a function in a region that may not be the overall global maximum.[1]

Location

Location is a particular point or range of points on a specified Dimension. For example: Dimension is like "time", location is like "2007" or "9.6.2008". Index is a list of locations, like "2001, 2002, 2003, 2004". Indexes are used to operationalise variables and other objects.

Log transformation

Log transformation is a logarithm of raw data. [1]

Logistic model

Logistic model is a sigmoid (S-shaped) function that relates the proportion of individuals with a specified characteristic to an independent variable.. random variable has a normal distribution.[1]

Lognormal distribution

Lognormal Distribution is a mathematical description where the natural logarithm of a random variable has a normal distribution.[1]

Lowest-observed-adverse-effect level

Lowest-observed-adverse-effect level (LOAEL) is the lowest concentration or amount of a substance, found by experiment or observation, that causes an adverse alteration of morphology, functional capacity, growth, development or life span of the target organisms distinguishable from normal (control) organisms of the same species and strain under the same defined conditions of exposure.[1]

Lowest-observed-effect level

Lowest-observed-effect level (LOEL) is a the lowest concentration or amount of a substance, found by experiment or observation, that causes any alteration of morphology, functional capacity, growth, development or life span of the target organisms distinguishable from normal (control) organisms of the same species and strain under the same defined conditions of exposure.[1]

Margin of exposure

Margin of exposure (MOE) is a ratio of the no-observed-adverse-effect level (NOAEL) for the critical effect to the theoretical, predicted or estimated exposure dose or concentration.[1]

Margin of safety

Margin of safety (MOS) is a margin between the reference dose and the actual exposure dose or concentration.[1]

Maximum likelihood estimate

Maximum likelihood estimate (MLE) is an estimate of a population parameter most likely to have produced the sample observations.[1]

Mechanism of action

Mechanism of action is a detailed description of the precise chain of events from the molecular level to gross macroscopic or histopathological toxicity.[1]

Medium

Medium is a material (e.g., air, water, soil, food, consumer products) surrounding or containing an agent. The place for events to occur and and manifest themselves.[5]

Method

Method is a systematic procedure for a particular information manipulation process that is needed as a part of an assessment work. Typically, a method is a "how-to-do" instruction to calculate a variable; it is used if the dependencies of the variable are unknown until an assessment is executed. In other words, methods can be used to calculate variables within assessments in situations where it is not practical or possible to calculate variables outside an assessment. In these cases, the method page is used within an assessment (e.g. in the dependencies slot) as if it was the variable that it is used to calculate. Method is the basic building block for describing the assessment work (not reality, like the other universal objects). Some methods can be about managing other methods.

Michaelis-menten equation

Michaelis-menten equation is a dose-response curve, frequently used for enzyme kinetics, with maximum slope at zero dose that approaches a maximum asymptote at increasing dose.[1]

Minimal publishable unit

Minimal publishable unit is the smallest amount of new scientific information that can be published using the traditional peer-reviewed scientific journals. It is typically a single experiment, study, or review that has a research question, original scientific work, at least descriptive hypothesis testing, and conclusions. It has to have an aspect of novelty, since e.g. a simple repetition of a published study by a new group is rarely considered publishable. Also, a separate part of a study, such as a novel research question, a study design without execution, or a new hypothesis without any related practical work are rarely considered publishable.

Mode of action

Mode of action is a series of events that may lead to induction of the relevant end-point of toxicity for which the weight of evidence supports plausibility.[1]

Model

  • A model is, according to open assessment, a method that has its management operationalised into a software so that the method can be performed with minimal human work. A model can be automatically run by a computer after the input parameters have been entered. The output of the computation is optimally the result of a variable. A model can also refer to a freely structured object, see a definition below. D↷
  • A model is, according to Intarese, a representation or description designed to show the structure or workings of an object, system or concept. In relation to the toolbox a model is a tool that is applied for calculating something, e.g. propagation model of stressors, dose-response-relationships. [10]

Moderator

Moderator is a person who takes the responsibility of a page in Opasnet. Usually, the moderator is someone who needs the page for his own purposes, e.g. it is a part of an assessment he is conducting. The moderator may also be someone who wants the information to be correct, because other people are using it in their own assessments. Moderator keeps an eye on the page and its edits, and improves the structure and content. He also removes any vandalism from the page. The moderator does not have any formal position or higher rights than any contributor; his respect grows from a hard-working attitude. Therefore, anyone can become a moderator simply by acting as one. The Opasnet maintenance team tries to make sure that all active pages have a moderator. The moderator is typically mentioned in the metadata box of the page.

Monetarization

Monetarization is a transformation of results of risk assessments for all risk categories (e.g. mortality, morbidity, acidification, global warming, ...) into monetary values, allowing to compare and add all kinds of risks. The monetary values per unit risk are in principle derived from stated or revealed preferences of the affected population.[11]

Monotonic dose-response

Monotonic dose-response is a dose-response that never decreases as dose increases. A monotonic function may be flat (constant) up to a threshold dose or may be flat at high doses if a biological limit, e.g., saturation, is attained.[1]

Multinomial

Multinomial are animals or individuals may be classified by more than two (binomial) categories, e.g., in a reproductive study fetuses may be: dead, alive normal, or alive abnormal.[1]

Name

Name attribute is the identifier of a variable or an assessment. The variable names should be chosen so that they are descriptive, unambiguous and not easily confused with other variables. An example of a good variable name is: daily average of PM2.5 concentration in Helsinki. See main articles variable and assessment.

National Institute of Public Health and Welfare

National Institute of Public Health and Welfare (NIPHW) is a prototype of a national institute. The purpose of the institute is to maintain and promote the health, well-being, and social welfare of the citizens of a nation and also internationally. The institute is a national research and expert institute. It is not directly responsible for maintaining the national health care system or providing health care services, unless some specific tasks are given to the institute on a national level. It is not designed for any particular country, but it should reflect a general organisational approach that can be applied in and modified for any country.

Negligible risk

Negligible risk is a risk management term. In cases where a quantitative risk estimate has been made, it is any risk less than an upper-bound incremental lifetime risk calculated using conservative risk assessment techniques such as the BMD.[1]

No-observed-adverse-effect level

No-observed-adverse-effect level (NOAEL) are the highest concentration or amount of a substance, found by experiment or observation, that causes no detectable adverse alteration of morphology, functional capacity, growth, development or life span of the target organisms under defined conditions of exposure.[1]

Nonlinear dose-response model

Nonlinear dose-response model is a mathematical relationship that cannot be expressed simply as the change in response being proportional to the amount of change of some function of dose.[1]

Normal context of use

Normal context of use describes the context where a particular information object (e.g. an assessment or a variable) is typically used, or where it can be assumed to be used. For example, a variable is typically used as a part of an assessment by a researcher or another academic person who speaks English fluently and has good knowledge about the topic but is not necessarily an expert in the field. Normal context of use is an important concept, because it gives guidance on what information an object should contain and how it should be presented. In addition, it is crucial for the evaluation of some performance criteria such as usability, applicability, or inter-assessment efficiency. E.g. estimates about usability are meaningless unless we first answer questions like "used by whom" or "used for what purpose". For an assessment, the context of use should be clearly described under the sub-attribute Intended use and users; then, that context is used for guiding work and evaluating performance, and normal context of use is less important.

Normal distribution

Normal distribution is a mathematical description where a continuous random variable x with a mean μ and a variance σ2 has a probability density function.[1]

Nugget

A nugget is a piece of information that is meant to be maintained in the original form and has distinguished authors. This is unlike other pages like variables, assessments, or encyclopedia articles, which evolve in time and can be improved by anyone. In addition, like encyclopedia articles, strict attribute structure and strict scientific method is NOT applied to nuggets.

Objective function

Objective function is a choice of function that is optimized for maximum likelihood estimation.[1]

Opasnet

Opasnet [1] is a website and workspace for a mass collaboration project that aims to improve societal decision-making. The original motivation was to improve environmental and health assessments and thus decisions related to environment and health. However, as the methods have developed and the project has grown, the scope has been widened to policy-making in any field. One of the major topics in Opasnet is climate change, which is clearly a multi-disciplinary field. Opasnet is based on open participation by anyone interested, free distribution of information, and strict application of the scientific method.

Opasnet Base (2008-2011)

Opasnet Base is a part of Opasnet and a storage and retrieval system for results of variables and data from studies. It is designed to be flexible enough to store information in almost any format: probability distributions or deterministic point estimates; spatially or temporally distributed data; or data with multiple dimensions. It can be used as a direct source of model input data, thus making it possible to use shared input information sources such as population data, climate scenarios, or dose-responses of pollutants. Opasnet Base can be accessed via links on variable and study pages (e.g. the metadata box), via a web interface and via the model Opasnet base connection.ANA.

Opasnet Journal

Opasnet Journal is a hypothetical, international, scientific journal. It is an open access journal that is published on the Opasnet website. It is based on the principle "publish first, review later" in a similar way as Arxiv in physics. It publishes articles on any field of science, if the article is written according to the open assessment method. Each article is an object in Opasnet (typically a nugget, variable, or assessment). Each article is given a URN (instead of a DOI) number. Articles are freely available in PDF format.

Opastopia

Opastopia is an imaginary society that actively promotes and applies the open assessment method in its societal decision-making. The society has taken the role to actively remove hindrances preventing the use of open assessment, and also to study these hindrances.

Open Assessors' Network

The Open Assessors' Network is a mass collaboration project for open assessors, that is people who are willing to promote the open assessment practices in the aim to improve societal decision-making. The major part of the collaboration happens on Opasnet, the website and workspace of this network: http://en.opasnet.org. In addition, there is a plan that Open Assessors' Network should be developed into a registered society for people interested in open assessment; the current plan is called Avary (description in Finnish). The society could maintain the Opasnet website and publish the Journal of Open Assessment.

Open assessment

Open assessment is a method that attempts to answer the following research question and to apply the answer in practical assessments: how can scientific information and value judgements be organised for improving societal decision-making in a situation where open participation is allowed?
In practice, the assessment processes are performed using Internet tools (notably Opasnet) along with more traditional tools. Stakeholders and other interested people are able to participate, comment, and edit the content as it develops, from an early phase of the process. Open assessments explicitly include value judgements, thereby extending its application beyond the traditional realm of risk assessment into the risk management arena. It is based, however, on a clear information structure and scientific methodolgy in order to provide clear rules for dealing with disputes. value judgements thus go through the same open criticism as scientific claims; the main difference is that scientific claims are based on observations, while value judgement are based on opinions of individuals.

Like other terms in the field of assessment 'open assessment' is subject to some confusion. It is therefore useful to distinguish clearly between:

  • the open assesment methodology;
  • the open assessment process - i.e. the actual mechanism of carrying out an open assessment, and
  • the open assessment product or report - i.e. the end product of the process.

To ensure clarity, open assessment also attempts to apply terms in a very strict way. In the summary below, therefore, links are given to further information on, and definitions of, many of the terms and concepts used. Open assessor

Open assessor is a person who works in a mass collaboration project about an open assessment in aim to improve societal decision-making about the topic of the assessment. Generally, open assessors think that a major hindrance to good decision-making is the lack of truthful information, specifically designed to the particular needs of that decision process, in an easily accessible form. In addition, they realise that decision-making processes are distracted by strong forces that are irrelevant or harmful to the achievement of the actual societal objectives. These forces are those that create the difference between policy-making and politics. Open assessors see the deleterious impact of these forces on the actual decisions made, and they fight the forces by promoting explicit expression of values, combined with truthful descriptions of reality. Open assessors think that this work benefits any honest political movement, and therefore the Open Assessors' Network is independent of and open to all political movements that accept the rules of open assessment.

Open participation

Open participation is a principle that anyone is allowed to raise any points related to an open assessment at any point during the making of the assessment. It is one of the key principles of open assessment.

Ordinal data

Ordinal data is a integers designating the rank, order, or counts.[1]

Other variable

Other variable is a variable other than endpoint variable, key variable, indicator variable or decision variable. See also assessment.

P-value

P-value in testing a hypothesis, the probability of a type I error (false positive). The probability that the sample (experimental) results are compatible with a specific hypothesis.[1]

PSSP

PSSP is a general methodology for organising information and process descriptions. It offers a uniform and systematic information structure for all systems, whether small details or large integrated models. The four attributes of PSSP (Purpose, Structure, State, Performance) enable hierarchical descriptions where the same attributes are used in all levels.

Parent Parent is a variable directly upstream in the causal chain, i.e. a variable that affects this variable (which is called a child); there is always a causal arrow pointing from the parent to the child. Participant

A person that participates in an assessment. Participants are defined as a subattribute of the assessment. See also Defining the users of an assessment.

Peer review

Peer review is a method for evaluating the scientific quality of a piece of information. In peer review a number of people that can be considered as reasonably acquainted with the topic that the piece of information addresses give their statement whether or not the piece of information is of good enough quality for publication in a scientific journal.

Performance

Performance is the measure of how well an object fulfills its purpose. In this context, we talk about objects that are used in assessments for describing reality or methods to produce these descriptions.

Perspective levels of decision making

Perspective levels of decision making describe essential perspectives that are all present in a decision-making process, either implicitly or explicitly. The currently identified levels are (from more to less fundamental) physical, psychological, cultural, organisational, and individual. The levels provide a practical means to clarify argumentation related to decision making and also identify problems that prevent progress towards desired outcomes.

Phase

A phase is a certain stage in an assessment process.

Plausibility test

Plausibility tests are procedures that clarify the goodness of variables in respect to some important properties, such as measurability, coherence, and clarity. The four plausibility tests are clairvoyant test, causality test, unit test, and Feynman test.

Point of departure

Point of departure (POD) is a the point on a dose-response curve established from experimental data, e.g., the benchmark dose, generally corresponding to an estimated low effect level (e.g., 1% to 10% incidence of an effect). Depending on the mode of action and available data, some form of extrapolation below the POD may be employed for low-dose risk assessment or the POD may be divided by a series of uncertainty factors to arrive at a reference dose.[1]

Poll

Poll in Opasnet is a way to get feedback from users. Some pages have user polls about specific issues, and you can simply click options that reflect your opinions. You don't need to be logged in to do this. The results of polls are stored in the Opasnet base as studies.

Polynomial

Polynomial is a mathematical function of the sum of a constant, linear term, quadratic term, cubic term, etc.[1]

Precautionary principle

The precautionary principle states that if an action or policy might cause severe or irreversible harm to the public, in the absence of a scientific consensus that harm would not ensue, the burden of proof falls on those who would advocate taking the action. The precautionary principle is most often applied in the context of the impact of human development or new technology on the environment and human health, as both involve complex systems where the consequences of actions may be unpredictable. There are several ways to apply this principle, such as
  1. Precautionary principle based on expected value
  2. Precautionary principle based on worst-case or another 'conservative' scenario.

Probability

Probability is the proportion (on a scale of 0 to 1) of cases for which a particular event occurs. Zero indicates the event never occurs and one indicates the event always occurs.[1]

Probability distribution

Probability distribution is a mathematical description of the relative probabilities of all possible outcomes of a measurement.[1]

Probit function

Probit function are assumes that the relative probabilities of effects as a function of dose are described by a Normal distribution. The cumulative probability as a function of dose has a sigmoid shape.[1]

Process

Process is a change of substance in time (according to the PSSP ontology). It is one of the fundamental objects of PSSP. In the open assessment context, the information manipulation processes related to the doing of an assessment are described as processes; they are called methods. In contrast, the processes that occur in the nature are described as variables.

Profile likelihood

Profile likelihood is a plot of the likelihood function versus the estimated value of a parameter.[1]

Purpose

Risk assessments should always be done for a purpose. When the purpose is identified and kept clear in mind and preferably explicated and made public, it helps to guide the process in producing a desired kind of assessment product. The primary purpose is to improve societal decision making by providing good descriptions of chosen parts of reality for the use of the decision-makers. Proper identification of the purpose of risk assessment crucially affects the assessment process and the content and essence of the final product. See also Purpose and properties of good assessments and Purpose determines the structure of environmental health assessments. The purpose of a variable is to describe a particular piece of reality.

Pyrkilo

Pyrkilo is a name by which the collaborative assessment method-tool compound, currently known as open assessment method and Opasnet workspace, used to be called in early phases of its development. See open assessment and Opasnet.

Quadratic term

Quadratic term is a quantity in a mathematical formula that is raised to the second power (squared).[1]

Quantal data

Quantal data is a dichotomous (Binomial) classification where an individual or animal is placed in one of two categories, e.g., dead or alive, with or without a particular type of tumour, normal or abnormal level of a hormone.[1]

Quantile

Quantile is a percentile (cumulative probability) of a distribution that ranges from zero to the 100th percentile.[1]

Quasi-likelihood

Quasi-likelihood is a likelihood function that is not totally defined and generally based on only an expression including the mean and variance.[1]

Question

Question answers this question: What is the research question that this object attempts to answer?

It contains a description of the physical and abstract boundaries of the object. For assessment and variable objects, scope is an expression of what part of reality the object is intended to describe. Scope does not have a true counterpart in reality, it is always referential to the instrumental use purpose of the object it relates to. Question is an attribute of a variable or an assessment describing the research question (including the boundaries) that the object attempts to answer. In open assessment also an attribute of other information objects. For a process, the respective attribute is called purpose. Rationale

Rationale answers this question: How can you find out the answer to the research question?

It attempts to describe the internal structure of the part of reality that the object is intended to describe and the relations of the interior with reality outside the scope. For assessment objects, definition appears in practice as a list of contents. For variables, it is a description of how the result of the variable can be derived or calculated. Rectangular hyperbola

Rectangular hyperbola is a mathematical function of the form y squared equals x squared plus c squared, where x and y are variables and c is a constant.[1]

Regression analysis

Regression analysis is a statistical process that produces a mathematical function (regression equation) that relates a dependent variable (biological effect) to independent variable, e.g., dose rate, duration of exposure, age.[1]

Repeated measures

Repeated measures is a biological endpoint is measured for the same individual or animal at different times (ages).[1]

Residual variance

Residual variance is the variance in experimental measurements remaining after accounting for the variance due to the independent variables, e.g., dose rate, duration of exposure, age. Typically referred to as the inherent unaccountable experimental variation.[1]

Residuals

Residuals are the numerical differences between observed and estimated effects.[1]

Respect theory

Respect theory is a theory about how people perceive respect and distribute their respect to other people based on their deeds or properties. It also studies implementations of the respect within a society (descriptive), and properties of a theoretically optimal implementation (normative). Respect theory claims to be a major solution to the dilemma of economic growth and sustainability of resources: It is a method to redistribute resources based on the intrinsic value of things. In contrast, economics measures utility, individual's preferences, income, and intrinsic cognitive processes of opportunity costs among other things. Particularly, economics gives higher value to scarce than abundant utilities. It is therefore insensitive to things that are abundant but still highly respected, such as being good to other people. Thus, respect theory captures the most important things better than the economic theory in a wealthy world where most people have already fulfilled their basic needs.

Response

Response is a change developed in the state or dynamics of an organism, system or (sub) population in reaction to exposure to an agent.[1]

Result range

The result range of a variable contains all possible values that the result of the variable may get with probability P>0. The result range is restricted by logical (the number of actual individuals must be an integer), rational (concentration cannot be negative or above 1000 g/kg), and observational (TCDD concentration in humans has never been observed to be above 144000 ng/kg fat) statements. The utility of result range comes from the dependencies to other variables. Child variables are probability distributions conditional on their parents. If the result range of the parents is defined and more or less unchanged, it facilitates the definition process of the children. The conditional probability distribution of a child is only defined for the parent values within its result range.

Risk

Risk is the probability of an adverse effect in an organism, system or (sub)population caused under specified circumstances by exposure to an agent.[1]

Risk assessment

Risk assessment is a systematic process for describing and quantifying the risks associated with processes, projects, policies, actions or events. In the context of environmental public health risks, risk assessment is the process of quantifying the probability of a harmful effect to individuals or the frequency of a harmful event to the population caused by exposure to one or several agents, which is again caused by projects, processes a.s.o. (causal chain). Risk assessment includes an uncertainty estimate.[12]

Risk characterisation

Risk characterization is the qualitative and, wherever possible, quantitative determination, including attendant uncertainties, of the probability of occurrence of known and potential adverse effects of an agent in a given organism, system or (sub)population, under defined exposure conditions.[1] Typically, risk characterisation is a transformation of risks for the same risk category (e.g. mortality, morbidity, acidification, global warming, ...) into values with a common unit, so that results can be directly compared. Example: transformation of health risks into DALY's (disability adjusted life years).[11]

Safety factor

Safety factor is a composite (reductive) factor by which an observed or estimated no-observedadverse effect level (NOAEL) is divided to arrive at a criterion or standard that is considered safe or without appreciable risk. See also uncertainty factor.[1]

Scenario

Scenario is a set of assessment-specific deliberate deviations from the results of one or more variables in the assessment. It is noteworthy that the result of a variable is the current best estimate of the truth; therefore, scenarios are deliberate deviations from the truth because they serve the functionality of learning what would happen if this was the situation (compared with a baseline, business-as-usual, or other scenarios). There are also alternative definitions that are slightly different from the one used in the Intarese framework or in open assessment:
  1. Archetypal descriptions of alternative images of the future, created from mental maps or models that reflect different perspectives on past, present and future developments. [13]
  2. A coherent, internally consistent and plausible description of a possible future state of the world. [14]
  3. Variation in the assumptions used to create models. [15]
  4. A synthetic description of an event or series of actions and events. [16]

Science-policy revolution

Science-policy revolution is a collateral paradigm shift in both science and policy. It is based on systematic and open sharing of information that is
  • scientifically criticizable and
  • usable in policy-making.
Science-policy revolution builds on open assessment.

Scoping

Scoping represents the planning phase of integrated risk assessment. Its purpose is to define the issue to be assessed and the ‘rules’ to be followed in the assessment process. By the same token, scoping provides a checklist on the assessment process, and helps to ensure that all the key factors have been considered during that process. It also provides a framework for discussion with the stakeholders during the assessment process and for reporting results of the risk assessment.
Key elements:
  • issue framing (developing a ‘model’ of the issue to assess)
  • indicator selection and specification (identifying the indicators to be used for the assessment)
  • definition of variables (structuring the assessment in variables and defining a causal diagram/scoping diagram)
  • protocol development (delimiting the assessment methods and data to be used in the assessment process).

Sensitivity analysis

Sensitivity analysis is a study performed to find out how the variation in the output of a model (numerical or otherwise) can be apportioned, qualitatively or quantitatively, to different sources of variation.[17]

Service

Service, in the context of assessments, is an action to provide a piece of information that is important for performing an assessment where the piece is not owned or possessed by the assessor without the help of a service provider. The concept of service explicates
  • the description of content and format of the information that is needed by an assessor,
  • the work needed to transform the information for the assessor to be used,
  • the intellectual property right issues related to the information,
  • the interface between the original location and format of the information and the location and format that is utilised by the assessor.

The concept of services is based on service-oriented architecture[18].

Severity

Severity is the degree to which an effect changes and impairs the functional capacity of an organ system.[1]

Shape parameter

Shape parameter is the exponent on dose in a dose-response function that dictates the curvature of the function.[1]

Shared understanding

Shared understanding between two individuals about a particular topic means a situation where each individual is able to correctly explain what the other thinks about the topic and why. This definition can be extended also to a larger group. Here shared understanding is a written description of the topic that covers the thinking and reasoning on the topic of all members. In this group setting, not everyone needs to be able to describe everyone else's thinking, but everyone should agree that the written description correctly contains their thinking about the topic. In this way, although not everything is known by everyone in the group, the written description effectively represents the shared understanding of the group. Importantly, online tools such as wikis can be used to develop shared understanding even about complex topics among large groups.
It is important to notice that shared understanding is not the same as consensus or agreement. In shared understanding people can still disagree on the topic, but they agree on what opinions there are about it. While the purpose of agreement in decision-making is to conclude about the best option and act based on it, the purpose of shared understanding is to identify one or more poor decision option that should be rejected. This is analogous to the scientific method. Instead of attempting to find the truth directly, it critically evaluates hypotheses and rejects all that are not plausible in the light of observations. As the scientific method has proved to be the best method known for developing knowledge about the world, shared understanding may prove to be an effective way to make public policy.

Statement

Statement is a presentation of opinion or position about something that is (ie., a scientific statement) or something that should be (ie., a moral statement). Open assessment is based on statements whose validity and coherence is evaluated by a group. All statements considered valid by a group form the shared belief system of that group. It is important to understand that different groups may consider a statement valid even if some other group considers it invalid. This is because the rules that are used to evaluate validity may be different in different groups. The set of rules that all groups must use in open assessment to evaluate validity are called inference rules. In addition to inference rules, a group may agree upon other rules applied in the shared belief system of that group.


Step

Step is a certain stage in the assessment causal chain.[19]

Study

Study is an information object that describes a research study and its results, i.e. observational or other data obtained. The study methods are described as the definition of the object. Unlike traditional research articles, there is little or no discussion, because the interpretation of the results happens in other objects, typically in variables for which the study contains useful information. Another major difference to a variable is that the definition of the study is fixed after the research plan has been fixed and work done, and also the result is fixed after the data has been obtained and analysed. The scope of a study reflects the generalisability of the study results, and it is open to discussion and subject to change also after the study has been finished. In contrast, in a variable the scope is fixed, and the definition and result change as new information comes up.

Sustainable development

Sustainable development is a pattern of resource use that aims to meet human needs while preserving the environment so that these needs can be met not only in the present, but also for future generations. The term was used by the Brundtland Commission which coined what has become the most often-quoted definition of sustainable development as development that "meets the needs of the present without compromising the ability of future generations to meet their own needs."[20][21][22]

Task

Task is a process that is an intentional action with a defined purpose but that is not a method (i.e. a process of manipulating information about descriptions of the reality, typically variables). The difference between a task and a method is that a method is about the topic itself and it is implicit who actually applies the method (it can be a person or even a computer). In contrast, a task is about a particular person and a deed he should do (related to some piece of information). In a sense, a task is an object related to the traditional project management view, in contrast to the other formal objects that focus on the information and not on the people working on it.

Threshold

Threshold is a dose or an exposure concentration of an agent below which a stated effect is not observed or expected to occur.[1]

Threshold of toxicological concern

Threshold of toxicological concern is an exposure threshold value below which there is a very low probability of an appreciable risk to human health.[1]

Tool

A tool is an entity that helps in the assessment process and includes some kind of calculation or representation, e.g. a visualisation tool, an assessment design guidance tool, a tool for defining and categorising uncertainties, a tool for calculating emissions or for applying dose-response-relationships.

Toxic equivalency factor TEF (TCDD equivalency factor, toxic equivalency factor): a relative toxicity factor of a PCDD/F or PCB congener as related to TCDD. TEF values vary from 1 to 0.00003 (see also TEq). Various TEF values have been developed, e.g. WHO-TEF, Nordic TEF and international TEF or I-TEF. WHO-TEF values are based on the most recent scientific consensus. The differences between the respective TEFs are not great. The latest re-evaluation of TEF values was that by WHO in 2005, and these TEF values are often called WHO-TEF for PCDD/Fs and PCB-TEF for PCBs. TEq = ΣTEFi*Ci, where Ci is the amount (or concentration) of congener i. (Further details in Van den Berg et al, Toxicol. Sci 2006:93: 223-241, http://pubmed.gov/16829543). [23] Toxicodynamics

Toxicodynamics is the process of interaction of chemical substances with target sites and the subsequent reactions leading to adverse effects.[1]

Toxicokinetics

Toxicokinetics is the process of the uptake of potentially toxic substances by the body, the biotransformation they undergo, the distribution of the substances and their metabolites in the tissues, and the elimination of the substances and their metabolites from the body. Both the amounts and the concentrations of the substances and their metabolites are studied. The term has essentially the same meaning as pharmacokinetics, but the latter term should be restricted to the study of pharmaceutical substances.[1]

Trialogue

Trialogue is a process where people develop and create some concrete things together. Individuals observe reality and/or communicate their observations and descriptions of reality to others, and develop a shared artefact based on own and communicated observations, shared belief systems, reasoning, and existing artefacts. The name trialogue is an extension of dialogue where interaction typically happens through words, that is, two individuals discuss a topic, and communicate with each other. In trialogue, an information artefact (various versions of it) describing the topic (a description of reality) is understood as the third player, because it has such a critical role in the development of a shared belief system. The information artefact may have a physical form of e.g. a wiki page.(Cf. trialogical learning)

Uncertainty

Uncertainty refers not only to statistical uncertainty. The typology used in INTARESE builds on an adapted version of the Walker & Harremoës framework.
One dimension of uncertainties is the location of uncertainties (where the uncertainty is located). For most models it is applicable to distinguish between:
  • context
  • model structure
  • inputs
  • parameters
  • model outcome (result)
For the other dimension of uncertainties it is distinguished between three levels of uncertainties:
  • statistical uncertainty (known outcomes, known probabilities)
  • scenario uncertainty (known outcomes, unknown probabilities)
  • identified ignorance (unknown outcomes, unknown probabilities).

Uncertainty factor

Uncertainty factor is a reductive factor by which an observed or estimated no-observed-adverse-effect level (NOAEL) is divided to arrive at a criterion or standard that is considered safe or without appreciable risk. See also safety factor.[1]

Unconstrained dose-response model

Unconstrained dose-response model is no restrictions imposed on the estimates of parameters.[1]

Universal object

Universal object describes a kind of object with a particular purpose and a standardised structure according to its purpose and the PSSP ontology. The open assessment contains the following kinds of objects: assessment, variable, method, study, lecture, nugget, and encyclopedia article.

Upper-tail probability

Upper-tail probability is the probability that a variable exceeds a specified value.[1]

Uptake

Uptake is the process by which an agent crosses an absorption barrier. See also dose.

Validation

Validation is a process by which the reliability and relevance of a particular approach, method, process or assessment is established for a defined purpose.[1]

Valuation

  1. Valuation is a step in the full chain. It provides the means for comparing the outcomes of the models, e.g. health effects or, more generic, impacts. The outcomes are translated into a compound measure, e.g. DALYs, euros. Methods applicable are e.g. burden of desease (DALYs) or monetary valuation.
  2. Valuation only means monetary valuation.

Value

A value is used in relation to a value judgement, i.e. an opinion of an entity. It can be used concerning the valuation step but also for all other kinds of variables.

Value judgement

Value judgment is a preferenceD↷ for a certain state of the world, expressed by an individual or by a society. Value judgments - in contrast to valuation - include all kinds of statements of preferences, not only monetary valuation.
Assessment is about estimating impacts that may have either positive or negative value judgments attached to themselves or to the factors causally affecting them or to the factors causally affected by them. These values must be acknowledged in the process of making the assessments, not only in the decision making phase, otherwise there is a risk of compromising the relevance of the assessment. Combining phenomena of physical reality with the value judgments related to them requires methods to distinguish these two things from each other and bringing the value judgments to explicit scrutiny within an assessment.

Value of information

Value of information (VOI) in decision analysis is the amount a decision maker would be willing to pay for information prior to making a decision.[24]. Value of information is specific to a combination of a particular decision with several options, a particular objective (i.e., outcome of interest that can be quantitatively estimated), and a particular issue that is affected by the decision and is relevant for the objective. If all such issues are considered at the same time, we talk about expected value of perfect information.

Value variable

Value variable is a variable that describes a particular value judgement of an individual or a group. Value variables are used in assessments to give ethical or moral values to outcome variables (indicators).

Variability

Variability is an observable diversity in biological sensitivity or response, and in exposure parameters.[1]

Variable

Variable is a description of a particular piece of reality. It can be a description of a physical phenomenon, or a description of value judgements. Also decisions included in an assessment are described as variables. Variables are continuously existing descriptions of reality, which develop in time as knowledge about the topic increases. Variables are therefore not tied into any single assessment, but instead can be included in other assessments. A variable is the basic building block of describing reality.

Variance

Variance is a measure of variability, standard deviation squared.[1]

Weibull

Weibull is a form of a dose-response curve characterized by a relatively shallow slope at low doses that increases sharply as dose increases before leveling off at high doses.[1]

Weighted least squares estimate

Weighted least squares estimate is a parameter estimate obtained by minimizing the sum of squares of observed and estimated values weighted by a function, frequently the reciprocal of the variance of an observation.[1]

References

  1. 1.000 1.001 1.002 1.003 1.004 1.005 1.006 1.007 1.008 1.009 1.010 1.011 1.012 1.013 1.014 1.015 1.016 1.017 1.018 1.019 1.020 1.021 1.022 1.023 1.024 1.025 1.026 1.027 1.028 1.029 1.030 1.031 1.032 1.033 1.034 1.035 1.036 1.037 1.038 1.039 1.040 1.041 1.042 1.043 1.044 1.045 1.046 1.047 1.048 1.049 1.050 1.051 1.052 1.053 1.054 1.055 1.056 1.057 1.058 1.059 1.060 1.061 1.062 1.063 1.064 1.065 1.066 1.067 1.068 1.069 1.070 1.071 1.072 1.073 1.074 1.075 1.076 1.077 1.078 1.079 1.080 1.081 1.082 1.083 1.084 1.085 1.086 1.087 1.088 1.089 1.090 1.091 1.092 1.093 1.094 1.095 1.096 1.097 1.098 1.099 1.100 1.101 1.102 1.103 1.104 1.105 1.106 1.107 1.108 1.109 1.110 WHO Report
  2. Thomas Bayes (1763). "An Essay towards solving a Problem in the Doctrine of Chances. By the late Rev. Mr. Bayes, F.R.S., communicated by Mr. Price, in a letter to John Canton, A.M., F.R.S.". Philosophical Transactions of the Royal Society of London 53: 370–418. 
  3. Procter, J. (Editor-in-Chief) (1978). Longman Dictionary of Contemporary English, Longman Group Ltd., UK.
  4. Eemeren, F.H. van, & Grootendorst, R. (2004). A systematic theory of argumentation: The pragma-dialectical approach. Cambridge: Cambridge University Press.
  5. 5.0 5.1 5.2 5.3 5.4 5.5 5.6 5.7 IPCS (The WHO International Programme on Chemical Safety). Cite error: Invalid <ref> tag; name "IPCS_WHO" defined multiple times with different content Cite error: Invalid <ref> tag; name "IPCS_WHO" defined multiple times with different content Cite error: Invalid <ref> tag; name "IPCS_WHO" defined multiple times with different content Cite error: Invalid <ref> tag; name "IPCS_WHO" defined multiple times with different content Cite error: Invalid <ref> tag; name "IPCS_WHO" defined multiple times with different content Cite error: Invalid <ref> tag; name "IPCS_WHO" defined multiple times with different content
  6. Carl Barks: Flip Decision, Walt Disney Comics & Stories 149, Vol. 13, No. 5 (1953).
  7. 7.0 7.1 Gothenburg consensus paper, Dec 1999 by the WHO (World Health Organization) ECHP (European Centre for Health Policy).
  8. 8.0 8.1 D5 Intarese Conceptual Model of Assessment Framework (May 2007)
  9. Intarese guidance and methods for indicator selection and specification
  10. Wikipedia and old working definition of SP 4.
  11. 11.0 11.1 USTUTT (Stuttgart University)
  12. Covello, V.T. and Merkhofer, M.W. 1993. Risk assessment methods, Approaches for assessing health and environmental risks. Plenum Press, New York and London, p. 3.
  13. Rotmans, J. (1998). Methods for IA: The challenges and opportunities ahead. Environmental modelling and Assessment 3(3), 155.
  14. Parry, M. and Carter, T. (1998). Climate impact and Adaptation Assessment. Earthscan Publications Ltd., London, UK.
  15. Peterson G.D., Cumming G.S., Carpenter S.R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology 17(2), 358-366.
  16. Wikipedia definition on scenario
  17. Wikipedia definition on sensitivity analysis
  18. OASIS Reference Model for Service Oriented Architecture 1.0
  19. Intarese general method.
  20. United Nations. 1987."Report of the World Commission on Environment and Development." General Assembly Resolution 42/187, 11 December 1987. Retrieved: 2007-04-12
  21. Smith, Charles; Rees, Gareth: Economic Development, 2nd edition. Macmillan, 1998, Basingstoke. ISBN 0333722280.
  22. Sustainable development in Wikipedia
  23. Jouko Tuomisto, Terttu Vartiainen and Jouni T. Tuomisto: Dioxin synopsis. Report. National Institute for Health and Welfare (THL), ISSN 1798-0089 ; 14/2011 [2]
  24. Value of information in Wikipedia

See also