Quantitative Microbacterial Risk Assessment (QMRA)

QMRA is taking a part in Risk Assessment part. Here, there are 4 steps need to be taken into account, Hazard identification, Hazard Characterization, Exposure assessment, and Risk Characterization. The process starts with hazard identification and hazard characteristic, where the type of micro-bacteria (Salmonella, Listeria, E. Coli, etc) is introduced. In addition, the characteristic of determined micro-bacteria need to be studied to better understand how the micro-bacteria is grow and in what circumstances.
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Risk and Food

Risk can be defined as a chance of danger, damage, loss, injury, or any other undesired consequences. Most authors agree that risk involves 2 elements, possible consequences (impact) and associated uncertainty (probability of occurrence). The source of risk is known as hazard. So, hazard relates to the source of harm, while risk is the probability of the harm being experienced. Therefore, some authors defined risk as a combination of hazard and probability of hazard occurrence, where hazard is defined as the degree of harm to human beings, property, society or environment.
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Provenance and Semantic Web

Semantic Web is an extension of current web that provide machine readable format to allow machine (computer) to process, analyze and understand the meaning of data. There are some supported components to realize the concept of semantic web, also known as Semantic Cake. Figure below depict the picture of Semantic Cake. The widely used format in semantic web is rdf and ontology. RDF is a XML format document that represent data or information in directed-labeled graph in the Web. It does that by structuring information in subject-predicate-object called statement. The subject of 1 statement can also be the object of another statement creating rich-interrelated knowledge based. RDF is needed in the concept of Semantic Web, because it conveys the meaning that can be understood by computer.
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Provenance Documents

Provenance should be openly available and can be accessed to support transparency. Therefore, it need to be standardized, so provenance data can be exchanged and interlinked among applications. To achieve that, W3C defines a standard language for exchanging provenance called PROV. PROV is intended to facilitate the machine-processable data model for provenance. By providing a standardized vocabulary to describe flow of data, process, and responsibility, an application can be enriched with data-lineage about the origin of data. The abstract model and serialization of PROV is depicted below.
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Risk – Management / Analysis

RISK MANAGEMENT can be explained as a management function the object of which is the protection of people, assets and earnings by avoiding or minimising the potential for loss from pure risk, and the provision of funds to recover from losses that do occur. Risk Management involves the systematic identification, evaluation and control of all identified potential losses.

The aim of Risk Management is to develop a structured way of identifying and assessing the probabilities and consequences of risk, and selecting appropriate risk strategies to reduce the probability of, or losses associated. Moreover, analyse risk can provide decision support by systematization of knowledge to describe/express risk and how to mitigate the risk. Continue reading

Risk – Definition

Risk can be defined as a chance of danger, damage, loss, injury, or any other undesired consequences. Most authors agree that RISK involves 2 elements, possible consequences (impact) and associated uncertainty (probability of occurrence). The probability of p is defined as the fraction of times the accidental event A occurs if the activity considered were repeated an infinite number of times. Thus, probability can be used as a measure of uncertainty which is defined as the perceived inability to predict something accurately. In addition, when assessing and managing RISK, we need to encounter both the consequences of losses and the probability of risky events. Continue reading

Due Diligence in Food Supply Chain

Due Diligence is a way to fulfill a certain requirement. It gives more power and ‘teeth’ to comply with legislation, for example in food industry. By defining Due Diligence, the government can increase the legal responsibility to food premises on how they handling food. However, due diligence is a term that has various interpretations. Each organization perceives it differently and what they can do is to provide evidence of due diligence. Continue reading

Trust and Accountability

Provenance is concerned with causal dependencies between data and the process around it that contributes to its existence in a specific state. It can be used to make determination whether information can be trusted, integrate with another data source, support accountability, and give a credit for the originator. In essence, the notable uses of Provenance are as follows:

  • Reliability and quality -> given a derived dataset we are able to cite its lineage and therefore measure its credibility;
  • Justification and audit -> give a historical account of when and how data has been produced;
  • Re-usability, reproducibility and repeatability -> a provenance record not only shows how data has been produced, it provides all the necessary information to reproduce the results;
  • Ownership, security, credit and copyright -> who the information belongs to.

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Provenance – Introduction

Everything changes rapidly and it is difficult to trace back to see its originality. For example, the content of a blog that was previously contributed by known users, maybe updated by unknown user now. Provenance comes with a concept to overcome such enactment. According to the Oxford English Dictionary, Provenance is defined as:

  • the fact of coming from some particular source or quarter; origin, derivation.
  • the history or pedigree of a work of art, manuscript, rare book, etc.; concr., a record of the ultimate derivation and passage of an item through its various owners.

Another definition of Provenance is a record that describes the people, institutions, entities, and activities involved in producing, influencing, or delivering a piece of data or a thing. Continue reading