Privacy Policy

We are very delighted that you have shown interest in our enterprise. Data protection is of a particularly high priority for the management of the SIX-S GmbH. The use of the Internet pages of the SIX-S GmbH is possible without any indication of personal data; however, if a data subject wants to use special enterprise services via our website, processing of personal data could become necessary. If the processing of personal data is necessary and there is no statutory basis for such processing, we generally obtain consent from the data subject.

The processing of personal data, such as the name, address, e-mail address, or telephone number of a data subject shall always be in line with the General Data Protection Regulation (GDPR), and in accordance with the country-specific data protection regulations applicable to the SIX-S GmbH. By means of this data protection declaration, our enterprise would like to inform the general public of the nature, scope, and purpose of the personal data we collect, use and process. Furthermore, data subjects are informed, by means of this data protection declaration, of the rights to which they are entitled.

As the controller, the SIX-S GmbH has implemented numerous technical and organizational measures to ensure the most complete protection of personal data processed through this website. However, Internet-based data transmissions may in principle have security gaps, so absolute protection may not be guaranteed. For this reason, every data subject is free to transfer personal data to us via alternative means, e.g. by telephone.

1. Definitions

The data protection declaration of the SIX-S GmbH is based on the terms used by the European legislator for the adoption of the General Data Protection Regulation (GDPR). Our data protection declaration should be legible and understandable for the general public, as well as our customers and business partners. To ensure this, we would like to first explain the terminology used.

In this data protection declaration, we use, inter alia, the following terms:

  • Personal data
    Personal data means any information relating to an identified or identifiable natural person (“data subject”). An identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person.
  • Data subject
    Data subject is any identified or identifiable natural person, whose personal data is processed by the controller responsible for the processing.
  • Processing
    Processing is any operation or set of operations which is performed on personal data or on sets of personal data, whether or not by automated means, such as collection, recording, organisation, structuring, storage, adaptation or alteration, retrieval, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, restriction, erasure or destruction.
  • Restriction of processing
    Restriction of processing is the marking of stored personal data with the aim of limiting their processing in the future.
  • Profiling
    Profiling means any form of automated processing of personal data consisting of the use of personal data to evaluate certain personal aspects relating to a natural person, in particular to analyse or predict aspects concerning that natural person’s performance at work, economic situation, health, personal preferences, interests, reliability, behaviour, location or movements.
  • Pseudonymisation
    Pseudonymisation is the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person.
  • Controller or controller responsible for the processing
    Controller or controller responsible for the processing is the natural or legal person, public authority, agency or other body which, alone or jointly with others, determines the purposes and means of the processing of personal data; where the purposes and means of such processing are determined by Union or Member State law, the controller or the specific criteria for its nomination may be provided for by Union or Member State law.
  • Processor
    Processor is a natural or legal person, public authority, agency or other body which processes personal data on behalf of the controller.
  • Recipient
    Recipient is a natural or legal person, public authority, agency or another body, to which the personal data are disclosed, whether a third party or not. However, public authorities which may receive personal data in the framework of a particular inquiry in accordance with Union or Member State law shall not be regarded as recipients; the processing of those data by those public authorities shall be in compliance with the applicable data protection rules according to the purposes of the processing.
  • Third party
    Third party is a natural or legal person, public authority, agency or body other than the data subject, controller, processor and persons who, under the direct authority of the controller or processor, are authorised to process personal data.
  • Consent
    Consent of the data subject is any freely given, specific, informed and unambiguous indication of the data subject’s wishes by which he or she, by a statement or by a clear affirmative action, signifies agreement to the processing of personal data relating to him or her.

2. Name and Address of the controller

Controller for the purposes of the General Data Protection Regulation (GDPR), other data protection laws applicable in Member states of the European Union and other provisions related to data protection is:

SIX-S GmbH
Hinter der Kirche 1A
22880 Wedel
Phone: +49 4103 96 73 229
Email: contact@six-s.com
Website: www.six-s.com

3. Cookies

The Internet pages of the SIX-S GmbH use cookies. Cookies are text files that are stored in a computer system via an Internet browser.

Many Internet sites and servers use cookies. Many cookies contain a so-called cookie ID. A cookie ID is a unique identifier of the cookie. It consists of a character string through which Internet pages and servers can be assigned to the specific Internet browser in which the cookie was stored. This allows visited Internet sites and servers to differentiate the individual browser of the dats subject from other Internet browsers that contain other cookies. A specific Internet browser can be recognized and identified using the unique cookie ID.

Through the use of cookies, the SIX-S GmbH can provide the users of this website with more user-friendly services that would not be possible without the cookie setting.

By means of a cookie, the information and offers on our website can be optimized with the user in mind. Cookies allow us, as previously mentioned, to recognize our website users. The purpose of this recognition is to make it easier for users to utilize our website. The website user that uses cookies, e.g. does not have to enter access data each time the website is accessed, because this is taken over by the website, and the cookie is thus stored on the user’s computer system. Another example is the cookie of a shopping cart in an online shop. The online store remembers the articles that a customer has placed in the virtual shopping cart via a cookie.

The data subject may, at any time, prevent the setting of cookies through our website by means of a corresponding setting of the Internet browser used, and may thus permanently deny the setting of cookies. Furthermore, already set cookies may be deleted at any time via an Internet browser or other software programs. This is possible in all popular Internet browsers. If the data subject deactivates the setting of cookies in the Internet browser used, not all functions of our website may be entirely usable.

4. Collection of general data and information

The website of the SIX-S GmbH collects a series of general data and information when a data subject or automated system calls up the website. This general data and information are stored in the server log files. Collected may be (1) the browser types and versions used, (2) the operating system used by the accessing system, (3) the website from which an accessing system reaches our website (so-called referrers), (4) the sub-websites, (5) the date and time of access to the Internet site, (6) an Internet protocol address (IP address), (7) the Internet service provider of the accessing system, and (8) any other similar data and information that may be used in the event of attacks on our information technology systems.

When using these general data and information, the SIX-S GmbH does not draw any conclusions about the data subject. Rather, this information is needed to (1) deliver the content of our website correctly, (2) optimize the content of our website as well as its advertisement, (3) ensure the long-term viability of our information technology systems and website technology, and (4) provide law enforcement authorities with the information necessary for criminal prosecution in case of a cyber-attack. Therefore, the SIX-S GmbH analyzes anonymously collected data and information statistically, with the aim of increasing the data protection and data security of our enterprise, and to ensure an optimal level of protection for the personal data we process. The anonymous data of the server log files are stored separately from all personal data provided by a data subject.

5. Subscription to our newsletters

On the website of the SIX-S GmbH, users are given the opportunity to subscribe to our enterprise’s newsletter. The input mask used for this purpose determines what personal data are transmitted, as well as when the newsletter is ordered from the controller.

The SIX-S GmbH informs its customers and business partners regularly by means of a newsletter about enterprise offers. The enterprise’s newsletter may only be received by the data subject if (1) the data subject has a valid e-mail address and (2) the data subject registers for the newsletter shipping. A confirmation e-mail will be sent to the e-mail address registered by a data subject for the first time for newsletter shipping, for legal reasons, in the double opt-in procedure. This confirmation e-mail is used to prove whether the owner of the e-mail address as the data subject is authorized to receive the newsletter.

During the registration for the newsletter, we also store the IP address of the computer system assigned by the Internet service provider (ISP) and used by the data subject at the time of the registration, as well as the date and time of the registration. The collection of this data is necessary in order to understand the (possible) misuse of the e-mail address of a data subject at a later date, and it therefore serves the aim of the legal protection of the controller.

The personal data collected as part of a registration for the newsletter will only be used to send our newsletter. In addition, subscribers to the newsletter may be informed by e-mail, as long as this is necessary for the operation of the newsletter service or a registration in question, as this could be the case in the event of modifications to the newsletter offer, or in the event of a change in technical circumstances. There will be no transfer of personal data collected by the newsletter service to third parties. The subscription to our newsletter may be terminated by the data subject at any time. The consent to the storage of personal data, which the data subject has given for shipping the newsletter, may be revoked at any time. For the purpose of revocation of consent, a corresponding link is found in each newsletter. It is also possible to unsubscribe from the newsletter at any time directly on the website of the controller, or to communicate this to the controller in a different way.

6. Newsletter-Tracking

The newsletter of the SIX-S GmbH contains so-called tracking pixels. A tracking pixel is a miniature graphic embedded in such e-mails, which are sent in HTML format to enable log file recording and analysis. This allows a statistical analysis of the success or failure of online marketing campaigns. Based on the embedded tracking pixel, the SIX-S GmbH may see if and when an e-mail was opened by a data subject, and which links in the e-mail were called up by data subjects.

Such personal data collected in the tracking pixels contained in the newsletters are stored and analyzed by the controller in order to optimize the shipping of the newsletter, as well as to adapt the content of future newsletters even better to the interests of the data subject. These personal data will not be passed on to third parties. Data subjects are at any time entitled to revoke the respective separate declaration of consent issued by means of the double-opt-in procedure. After a revocation, these personal data will be deleted by the controller. The SIX-S GmbH automatically regards a withdrawal from the receipt of the newsletter as a revocation.

7. Contact possibility via the website

The website of the SIX-S GmbH contains information that enables a quick electronic contact to our enterprise, as well as direct communication with us, which also includes a general address of the so-called electronic mail (e-mail address). If a data subject contacts the controller by e-mail or via a contact form, the personal data transmitted by the data subject are automatically stored. Such personal data transmitted on a voluntary basis by a data subject to the data controller are stored for the purpose of processing or contacting the data subject. There is no transfer of this personal data to third parties.

8. Routine erasure and blocking of personal data

The data controller shall process and store the personal data of the data subject only for the period necessary to achieve the purpose of storage, or as far as this is granted by the European legislator or other legislators in laws or regulations to which the controller is subject to.

If the storage purpose is not applicable, or if a storage period prescribed by the European legislator or another competent legislator expires, the personal data are routinely blocked or erased in accordance with legal requirements.

9. Rights of the data subject

  • Right of confirmation
    Each data subject shall have the right granted by the European legislator to obtain from the controller the confirmation as to whether or not personal data concerning him or her are being processed. If a data subject wishes to avail himself of this right of confirmation, he or she may, at any time, contact any employee of the controller.
  • Right of access
    Each data subject shall have the right granted by the European legislator to obtain from the controller free information about his or her personal data stored at any time and a copy of this information. Furthermore, the European directives and regulations grant the data subject access to the following information:
    • the purposes of the processing;
    • the categories of personal data concerned;
    • the recipients or categories of recipients to whom the personal data have been or will be disclosed, in particular recipients in third countries or international organisations;
    • where possible, the envisaged period for which the personal data will be stored, or, if not possible, the criteria used to determine that period;
    • the existence of the right to request from the controller rectification or erasure of personal data, or restriction of processing of personal data concerning the data subject, or to object to such processing;
    • the existence of the right to lodge a complaint with a supervisory authority;
    • where the personal data are not collected from the data subject, any available information as to their source;
    • the existence of automated decision-making, including profiling, referred to in Article 22(1) and (4) of the GDPR and, at least in those cases, meaningful information about the logic involved, as well as the significance and envisaged consequences of such processing for the data subject.Furthermore, the data subject shall have a right to obtain information as to whether personal data are transferred to a third country or to an international organisation. Where this is the case, the data subject shall have the right to be informed of the appropriate safeguards relating to the transfer. If a data subject wishes to avail himself of this right of access, he or she may, at any time, contact any employee of the controller.
  • Right to rectification
    Each data subject shall have the right granted by the European legislator to obtain from the controller without undue delay the rectification of inaccurate personal data concerning him or her. Taking into account the purposes of the processing, the data subject shall have the right to have incomplete personal data completed, including by means of providing a supplementary statement. If a data subject wishes to exercise this right to rectification, he or she may, at any time, contact any employee of the controller.
  • Right to erasure (Right to be forgotten)
    Each data subject shall have the right granted by the European legislator to obtain from the controller the erasure of personal data concerning him or her without undue delay, and the controller shall have the obligation to erase personal data without undue delay where one of the following grounds applies, as long as the processing is not necessary:
    • The personal data are no longer necessary in relation to the purposes for which they were collected or otherwise processed.
    • The data subject withdraws consent to which the processing is based according to point (a) of Article 6(1) of the GDPR, or point (a) of Article 9(2) of the GDPR, and where there is no other legal ground for the processing.
    • The data subject objects to the processing pursuant to Article 21(1) of the GDPR and there are no overriding legitimate grounds for the processing, or the data subject objects to the processing pursuant to Article 21(2) of the GDPR.
    • The personal data have been unlawfully processed.
    • The personal data must be erased for compliance with a legal obligation in Union or Member State law to which the controller is subject.
    • The personal data have been collected in relation to the offer of information society services referred to in Article 8(1) of the GDPR.If one of the aforementioned reasons applies, and a data subject wishes to request the erasure of personal data stored by the SIX-S GmbH, he or she may, at any time, contact any employee of the controller. An employee of SIX-S GmbH shall promptly ensure that the erasure request is complied with immediately. Where the controller has made personal data public and is obliged pursuant to Article 17(1) to erase the personal data, the controller, taking account of available technology and the cost of implementation, shall take reasonable steps, including technical measures, to inform other controllers processing the personal data that the data subject has requested erasure by such controllers of any links to, or copy or replication of, those personal data, as far as processing is not required. An employees of the SIX-S GmbH will arrange the necessary measures in individual cases.
  • Right of restriction of processing
    Each data subject shall have the right granted by the European legislator to obtain from the controller restriction of processing where one of the following applies:
    • The accuracy of the personal data is contested by the data subject, for a period enabling the controller to verify the accuracy of the personal data.
    • The processing is unlawful and the data subject opposes the erasure of the personal data and requests instead the restriction of their use instead.
    • The controller no longer needs the personal data for the purposes of the processing, but they are required by the data subject for the establishment, exercise or defence of legal claims.
    • The data subject has objected to processing pursuant to Article 21(1) of the GDPR pending the verification whether the legitimate grounds of the controller override those of the data subject.If one of the aforementioned conditions is met, and a data subject wishes to request the restriction of the processing of personal data stored by the SIX-S GmbH, he or she may at any time contact any employee of the controller. The employee of the SIX-S GmbH will arrange the restriction of the processing.
  • Right to data portability
    Each data subject shall have the right granted by the European legislator, to receive the personal data concerning him or her, which was provided to a controller, in a structured, commonly used and machine-readable format. He or she shall have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided, as long as the processing is based on consent pursuant to point (a) of Article 6(1) of the GDPR or point (a) of Article 9(2) of the GDPR, or on a contract pursuant to point (b) of Article 6(1) of the GDPR, and the processing is carried out by automated means, as long as the processing is not necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. Furthermore, in exercising his or her right to data portability pursuant to Article 20(1) of the GDPR, the data subject shall have the right to have personal data transmitted directly from one controller to another, where technically feasible and when doing so does not adversely affect the rights and freedoms of others. In order to assert the right to data portability, the data subject may at any time contact any employee of the SIX-S GmbH.
  • Right to object
    Each data subject shall have the right granted by the European legislator to object, on grounds relating to his or her particular situation, at any time, to processing of personal data concerning him or her, which is based on point (e) or (f) of Article 6(1) of the GDPR. This also applies to profiling based on these provisions. The SIX-S GmbH shall no longer process the personal data in the event of the objection, unless we can demonstrate compelling legitimate grounds for the processing which override the interests, rights and freedoms of the data subject, or for the establishment, exercise or defence of legal claims. If the SIX-S GmbH processes personal data for direct marketing purposes, the data subject shall have the right to object at any time to processing of personal data concerning him or her for such marketing. This applies to profiling to the extent that it is related to such direct marketing. If the data subject objects to the SIX-S GmbH to the processing for direct marketing purposes, the SIX-S GmbH will no longer process the personal data for these purposes. In addition, the data subject has the right, on grounds relating to his or her particular situation, to object to processing of personal data concerning him or her by the SIX-S GmbH for scientific or historical research purposes, or for statistical purposes pursuant to Article 89(1) of the GDPR, unless the processing is necessary for the performance of a task carried out for reasons of public interest. In order to exercise the right to object, the data subject may contact any employee of the SIX-S GmbH. In addition, the data subject is free in the context of the use of information society services, and notwithstanding Directive 2002/58/EC, to use his or her right to object by automated means using technical specifications.
  • Automated individual decision-making, including profiling
    Each data subject shall have the right granted by the European legislator not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her, or similarly significantly affects him or her, as long as the decision (1) is not is necessary for entering into, or the performance of, a contract between the data subject and a data controller, or (2) is not authorised by Union or Member State law to which the controller is subject and which also lays down suitable measures to safeguard the data subject’s rights and freedoms and legitimate interests, or (3) is not based on the data subject’s explicit consent. If the decision (1) is necessary for entering into, or the performance of, a contract between the data subject and a data controller, or (2) it is based on the data subject’s explicit consent, the SIX-S GmbH shall implement suitable measures to safeguard the data subject’s rights and freedoms and legitimate interests, at least the right to obtain human intervention on the part of the controller, to express his or her point of view and contest the decision. If the data subject wishes to exercise the rights concerning automated individual decision-making, he or she may, at any time, contact any employee of the SIX-S GmbH.
  • iRight to withdraw data protection consent
    Each data subject shall have the right granted by the European legislator to withdraw his or her consent to processing of his or her personal data at any time. If the data subject wishes to exercise the right to withdraw the consent, he or she may, at any time, contact any employee of the SIX-S GmbH.

10. Data protection provisions about the application and use of LinkedIn

The controller has integrated components of the LinkedIn Corporation on this website. LinkedIn is a web-based social network that enables users with existing business contacts to connect and to make new business contacts. Over 400 million registered people in more than 200 countries use LinkedIn. Thus, LinkedIn is currently the largest platform for business contacts and one of the most visited websites in the world.

The operating company of LinkedIn is LinkedIn Corporation, 2029 Stierlin Court Mountain View, CA 94043, UNITED STATES. For privacy matters outside of the UNITED STATES LinkedIn Ireland, Privacy Policy Issues, Wilton Plaza, Wilton Place, Dublin 2, Ireland, is responsible.

With each call-up to one of the individual pages of this Internet site, which is operated by the controller and on which a LinkedIn component (LinkedIn plug-in) was integrated, the Internet browser on the information technology system of the data subject is automatically prompted to the download of a display of the corresponding LinkedIn component of LinkedIn. Further information about the LinkedIn plug-in may be accessed under https://developer.linkedin.com/plugins. During the course of this technical procedure, LinkedIn gains knowledge of what specific sub-page of our website was visited by the data subject.

If the data subject is logged in at the same time on LinkedIn, LinkedIn detects with every call-up to our website by the data subject—and for the entire duration of their stay on our Internet site—which specific sub-page of our Internet page was visited by the data subject. This information is collected through the LinkedIn component and associated with the respective LinkedIn account of the data subject. If the data subject clicks on one of the LinkedIn buttons integrated on our website, then LinkedIn assigns this information to the personal LinkedIn user account of the data subject and stores the personal data.

LinkedIn receives information via the LinkedIn component that the data subject has visited our website, provided that the data subject is logged in at LinkedIn at the time of the call-up to our website. This occurs regardless of whether the person clicks on the LinkedIn button or not. If such a transmission of information to LinkedIn is not desirable for the data subject, then he or she may prevent this by logging off from their LinkedIn account before a call-up to our website is made.

LinkedIn provides under https://www.linkedin.com/psettings/guest-controls the possibility to unsubscribe from e-mail messages, SMS messages and targeted ads, as well as the ability to manage ad settings. LinkedIn also uses affiliates such as Eire, Google Analytics, BlueKai, DoubleClick, Nielsen, Comscore, Eloqua, and Lotame. The setting of such cookies may be denied under https://www.linkedin.com/legal/cookie-policy. The applicable privacy policy for LinkedIn is available under https://www.linkedin.com/legal/privacy-policy. The LinkedIn Cookie Policy is available under https://www.linkedin.com/legal/cookie-policy.

11. Data protection provisions about the application and use of Xing

On this website, the controller has integrated components of XING. XING is an Internet-based social network that enables users to connect with existing business contacts and to create new business contacts. The individual users can create a personal profile of themselves at XING. Companies may, e.g. create company profiles or publish jobs on XING.

The operating company of XING is XING SE, Dammtorstraße 30, 20354 Hamburg, Germany.

With each call-up to one of the individual pages of this Internet site, which is operated by the controller and on which a XING component (XING plug-in) was integrated, the Internet browser on the information technology system of the data subject is automatically prompted to download a display of the corresponding XING component of XING. Further information about the XING plug-in the may be accessed under https://dev.xing.com/plugins. During the course of this technical procedure, XING gains knowledge of what specific sub-page of our website was visited by the data subject.

If the data subject is logged in at the same time on XING, XING detects with every call-up to our website by the data subject—and for the entire duration of their stay on our Internet site—which specific sub-page of our Internet page was visited by the data subject. This information is collected through the XING component and associated with the respective XING account of the data subject. If the data subject clicks on the XING button integrated on our Internet site, e.g. the “Share”-button, then XING assigns this information to the personal XING user account of the data subject and stores the personal data.

XING receives information via the XING component that the data subject has visited our website, provided that the data subject is logged in at XING at the time of the call to our website. This occurs regardless of whether the person clicks on the XING component or not. If such a transmission of information to XING is not desirable for the data subject, then he or she can prevent this by logging off from their XING account before a call-up to our website is made.

The data protection provisions published by XING, which is available under https://www.xing.com/privacy, provide information on the collection, processing and use of personal data by XING. In addition, XING has published privacy notices for the XING share button under https://www.xing.com/app/share?op=data_protection.

12. Legal basis for the processing

Art. 6(1) lit. a GDPR serves as the legal basis for processing operations for which we obtain consent for a specific processing purpose. If the processing of personal data is necessary for the performance of a contract to which the data subject is party, as is the case, for example, when processing operations are necessary for the supply of goods or to provide any other service, the processing is based on Article 6(1) lit. b GDPR. The same applies to such processing operations which are necessary for carrying out pre-contractual measures, for example in the case of inquiries concerning our products or services. Is our company subject to a legal obligation by which processing of personal data is required, such as for the fulfillment of tax obligations, the processing is based on Art. 6(1) lit. c GDPR. In rare cases, the processing of personal data may be necessary to protect the vital interests of the data subject or of another natural person. This would be the case, for example, if a visitor were injured in our company and his name, age, health insurance data or other vital information would have to be passed on to a doctor, hospital or other third party. Then the processing would be based on Art. 6(1) lit. d GDPR. Finally, processing operations could be based on Article 6(1) lit. f GDPR. This legal basis is used for processing operations which are not covered by any of the abovementioned legal grounds, if processing is necessary for the purposes of the legitimate interests pursued by our company or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data. Such processing operations are particularly permissible because they have been specifically mentioned by the European legislator. He considered that a legitimate interest could be assumed if the data subject is a client of the controller (Recital 47 Sentence 2 GDPR).

13. The legitimate interests pursued by the controller or by a third party

Where the processing of personal data is based on Article 6(1) lit. f GDPR our legitimate interest is to carry out our business in favor of the well-being of all our employees and the shareholders.

14. Period for which the personal data will be stored

The criteria used to determine the period of storage of personal data is the respective statutory retention period. After expiration of that period, the corresponding data is routinely deleted, as long as it is no longer necessary for the fulfillment of the contract or the initiation of a contract.

15. Provision of personal data as statutory or contractual requirement; Requirement necessary to enter into a contract; Obligation of the data subject to provide the personal data; possible consequences of failure to provide such data

We clarify that the provision of personal data is partly required by law (e.g. tax regulations) or can also result from contractual provisions (e.g. information on the contractual partner). Sometimes it may be necessary to conclude a contract that the data subject provides us with personal data, which must subsequently be processed by us. The data subject is, for example, obliged to provide us with personal data when our company signs a contract with him or her. The non-provision of the personal data would have the consequence that the contract with the data subject could not be concluded. Before personal data is provided by the data subject, the data subject must contact any employee. The employee clarifies to the data subject whether the provision of the personal data is required by law or contract or is necessary for the conclusion of the contract, whether there is an obligation to provide the personal data and the consequences of non-provision of the personal data.

16. Existence of automated decision-making

As a responsible company, we do not use automatic decision-making or profiling.

This Privacy Policy has been generated by the Privacy Policy Generator of the DGD – Your External DPO that was developed in cooperation with German Lawyers from WILDE BEUGER SOLMECKE, Cologne.

Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

Aliquot

An aliquot is the ultimate sub-sample extracted in a 'Lot-to-Aliquot' pathway for analysis. By analogy, process analytical technology involves the extraction of virtual samples, which are defined volumes of matter interacting with a process analytical instrument.

Analysis

Analysis is the systematic examination and evaluation of the ultimate sub-sample of chemical, biological, or physical substance (Aliquot) to determine its composition, structure, properties, or presence of specific components.

Analytical Bias

Analytical bias is a systematic deviation of measured values from true values.  An analytical bias can arise from multiple sources, including instrument calibration errors, sample preparation techniques, operator method, or inherent methodological limitations. Unlike random errors, which fluctuate unpredictably, analytical bias consistently skews results in a particular direction. Identifying and correcting this bias is crucial to ensure the accuracy and reliability of analytical data (bias correction).

Analytical Precision

Analytical precision refers to the degree of agreement among repeated analyses of the same aliquot under identical conditions. It reflects the consistency and reproducibility of the results obtained by a given analytical method. High precision indicates minimal random analytical error and close clustering of analytical results around an average. Precision does not necessarily imply accuracy, as a method can be precise yet still yield systematically biased results. 

C

Composite Sampling

Composite sampling extracts a number (Q) of  Increments, established to capture the Lot Heterogeneity. Composite sampling is the only way to represent heterogeneous material. A composite sample is made by aggregating the Q increments subject to the Fundamental Sampling Principle (FSP). The required amount of increments for the requested Representativity Q can be carefully established to make sampling fit-for-purpose.

Compositional Heterogeneity (CH)

Compositional heterogeneity is the variation between individual fundamental units of a target material (particles, fragments, cells, ...). CH is an intrinsic characteristic of the target material to be sampled.

Correct Sampling Errors (CSE)
CSE are the errors that cannot be eliminated even when sampling correctly (unbiased) according to the Theory of Sampling (TOS). CSE are caused by Lot Heterogeneity and can only be minimised.
There are two Correct Sampling Errors (CSE):
  1. Fundamental Sampling Error (FSE)
  2. Grouping and Segregation Error (GSE)
Crushing
Crushing is the term used for the process of reducing particle size. Other terms are grinding, milling, maceration, comminution. Particle size reduction changes the Compositional Heterogeneity (CH) of a material. Composite Sampling and crushing are the only agents with which to reduce the Fundamental Sampling Error (FSE).

D

Data Format

Data must be reported as the measurement results and the Measurement Uncertainties stemming from sampling and analysis. Note that MUAnalysis and MUSampling are expressed as variances.

Data =            Measurement +/- (MUSampling ; MUAnalysis)

Example:       375 ppm +/- (85 ppm ; 18 ppm)

Note that the Uncertainties 85 ppm and 18 ppm are the square roots of MUSampling and MUAnalysis.

Data Uncertainty

See Total Measurement Uncertainty.

Distributional Heterogeneity (DH)

Distributional heterogeneity is the variation between groups of fundamental units of a target material. Groups of units manifest themselves as Increments used in sampling. DH is an expression of the spatial heterogeneity of a material to be sampled (Lot).

DS3077:2024

This standard is a matrix-independent standard for representative sampling, published by the Danish Standards Foundation. This standard sets out a minimum competence basis for reliable planning, performance and assessment of existing or new sampling procedures with respect to representativity. This standard invalidates grab sampling and other incorrect sampling operations, by requiring conformance with a universal set of six Governing Principles and five Sampling Unit Operations. This standard is based on the Theory of Sampling (TOS).

webshop.ds.dk/en/standard/M374267/ds-3077-2024

Dynamic Lot

A dynamic lot is a moving material stream where sampling is carried out at a fixed location. For both Stationary Lots and Dynamic Lots, sampling procedures must be able to represent the entire lot volume guided by the Fundamental Sampling Principle.

F

Fractionation

Fractionation is a way of processing a Lot or Sample before sampling (or subsampling). Fractionation separates materials/lots into fractions according to particle properties, e.g. size, density, shape, magnetic susceptibility, wettability, conductivity, intrinsic, or introduced moisture ...

Fundamental Sampling Error (FSE)

FSE results from the impossibility to fully compensate for inherent Compositional Heterogeneity (CH) when sampling. FSE is always present in all sampling operations but can be reduced by adherence to TOS' principles. Even a fully representative, non-biased sampling process will be unable to materialise two samples with identical composition due to Lot Heterogeneity. FSE can only be reduced by Crushing (followed by Mixing / Blending) i.e. by transforming into a different material system with smaller particle sizes.

Fundamental Sampling Principle (FSP)

The Fundamental Sampling Principle (FSP) stipulates that all potential Lot Increments must have the same probability of being extracted to be aggregated as a Composite Sample. Sampling processes in which certain areas, volumes, parts of a Lot are not physically accessible cannot ensure Representativity.

G

Global Estimation Error (GEE)

The GEE is the total data estimation error, the sum of the Total Sampling Error (TSE) and the Total Analytical Error (TAE).

Governing Principles

Six Governing Principles (GP) describe how to conduct representative sampling of heterogeneous materials:

1) Fundamental Sampling Principle (FSP)

2) Sampling Scale Invariance (SCI)

3) Principle of Sampling Correctness (PSC)

4) Principle of Sampling Simplicity (PSS)

5) Lot Dimensionality Transformation (LDT), and

6) Lot Heterogeneity Characterisation (LHC).

Grab Sampling

Process of extracting a singular portion of the Lot. Grab sampling cannot ensure Representativity for heterogeneous materials. Grab sampling results in a sample designated a Specimen.

Grouping and Segregation Error (GSE)

The GSE originates from the inherent tendency of Lot particles, or fragments hereof, to segregate and/or to group together locally to varying degrees within the full lot volume. This spatial irregularity is called the Distributional Heterogeneity (DH). There will always be segregation and grouping of Lot particles at different scales. GSE plays a significant role in addition to the Fundamental Sampling Error FSE. Unlike FSE however, the effects from GSE can be reduced in a given system state by Composite Sampling and/or Mixing / Blending. GSE can in practice be reduced significantly but is seldomly fully eliminated.

H

Heterogeneity

Heterogeneity refers to the state of being varied in composition. It is often contrasted with homogeneity, which implies complete similarity among components, which is a rare case. For materials in science, technology and industry heterogeneity is the norm. Heterogeneity applies to various contexts, such as populations of non-identical units, bulk materials, powders, slurries, biological swhere multiple distinct components coexist.

Heterogeneity in context of the Theory of Sampling, is described using three distinct characteristics, Compositional Heterogeneity CH, Distributional Heterogeneity DH and Particle-Size Heterogeneity

 

Heterogeneity Testing (HT)

Heterogeneity tests are used for optimizing sampling protocols for a variable of interest (analyte, feature) with regards to minimising the Fundamental Sampling Error (FSE).

Experimental approaches available are the 50-particle method, the heterogeneity test (HT), the sampling tree experiment (STE) or the duplicate series/sample analysis (DSA), and the segregation free analysis (SFA).

Recently, sensor-based heterogeneity tests have been introduced which bring the advantage of cost-effective analysis of large numbers of single particles.

Homogeneity

An assemblage of material units with identical unit size, composition and  characteristics. There are practically no homogenous materials in the realm of technology, industry and commerce (mineral resources, biology, pharmaceuticals, food, feed, environment, manufacturing and more) of interest for sampling. With respect to sampling, it is advantageous to consider that all materials are in practice  heterogeneous.

I

Incorrect Delimitation Error (IDE)

The principle for extracting correct Increments from processes is to delineate a full planar-parallel slice across the full width and depth of a stream of matter (Dynamic Lot. IDE results from delineating any other volume shape. When a sampling system or procedure is not correct relative to the appropriate Increment delineation, a Sampling Bias will result. The resulting error is defined as the Increment Delimitation Error (IDE). Similar IDE definitions apply to delineation and extraction of increments from Stationary Lots.

Incorrect Extraction Error (IEE)

Increments must not only be correctly delimitated but must also be extracted in full. The error incurred by not extracting all particles and fragments within the delimitated increment is the Increment Extraction Error (IEE). IDE and IEE are very often committed simultaneously because of inferior design, manufacturing, implementation or maintenance of sampling equipment and systems.

Incorrect Preparation Error (IPE)

Adverse sampling bias effects may occur for example during sample transport and storage (e.g. mix-up, damage, spillage), preparation (contamination and/or losses), intentional (fraud, sabotage) or unintentional human error (careless actions; deliberate or ill-informed non-adherence to protocols). All such non-compliances with the criteria for representative sampling and good laboratory practices (GLP) are grouped under the umbrella term IPE. The IPE is part of the bias-generating errors ISE that must always be avoided.

Incorrect Sampling Errors (ISE)

There are four ISE, which result from an inferior sampling process. These ISE can and must be eliminated.

  1. Incorrect Delimitation Error (IDE) aka Increment Delimitation Error
  2. Incorrect Extraction Error (IEE) aka Increment Extraction Error
  3. Incorrect Preparation Error (IPE) aka Increment Preparation Error
  4. Incorrect Weighing Error (IWE) aka Increment Weighing Error
Incorrect Weighing Error (IWE)

IWE reflects specific weighing errors associated with collecting Increments. For process sampling, IWE is incurred when extracted increments are not proportional to the contemporary flow rate (dynamic 1-dimensional lots), at the time or place of extraction. IWE is often a relatively easily dealt with appropriate engineering attention. Increments, and Samples, should preferentially represent a consistent mass (or volume).

Increment

Fundamental unit of sampling, defined by a specific mass or correctly delineated volume extracted by a specified sampling tool.

L

Lot

a) A Lot is made up of a specific target material to be subjected to a specified sampling procedure.

b) A Lot is the totality of the volume for which inferences are going to be made based on the final analytical results (for decision-making). Lot size can range from being extremely large (e.g. an ore body, a ship) to very small (e.g. a blood sample).

c) The term Lot refers both to the material as well as to lot size (volume/mass) and physical characteristics. Lots are distinguished as stationary or dynamic lots. A stationary lot is a non-moving volume of material, a dynamic lot is a material stream (Lot Dimensionality). For both stationary and dynamic lots, sampling procedures must address the entire lot volume guided by the Fundamental Sampling Principle (FSP).

Lot Definition

Lot Definition describes the process of defining the target volume, which will be subjected to Sampling.

Lot Dimensionality

TOS distinguishes Lot volume  according to the dimensions that must be covered by correct Increment extraction. This defines the concept of 'lot dimensionality', an attribute which is independent of the lot scale. Lot dimensionality is a characterisation to help understand and optimise sample extraction from any lot at any sampling stage. There are four main lot types: 0-, 1-, 2- and 3-dimensional lots (0-D, 1-D, 2-D and 3-D lots).

Lots are classified by subtracting the dimensions of the lot that are fully 'covered' be the salient sampling extraction tool in question. The higher the number of dimensions fully covered in the resulting sampling operation, the easier it is to reduce the Total Sampling Error TSE.

Lot Dimensionality Transformation (LDT)

By the Governing Principle Lot Dimensionality Transformation LDT, stationary 0-D, 2-D and 3-D lots can in many cases advantageously be transformed into dynamic 1-D lots, enabling optimal sampling. However, the application of LDT has practical limits as some lots cannot be transformed (e.g. a body of soil, or a mine resource, biological cells). The optimal approach for such cases is penetrating one dimension with complete increment extraction (usually height) turning a 3-D lot into a 2-D lot.

Lot Heterogeneity

The lot heterogeneity is the combination of Compositional Heterogeneity, Distributional Heterogeneity and Particle-Size-Heterogeneity.

CH + DH + PH

Lot Heterogeneity Characterisation
Lot Heterogeneity Characterisation is the process of assessing Lot Heterogeneity magnitude. Logically, it is impossible to design a sampling procedure without knowledge of the Heterogeneity of target material. Lot Heterogeneity Characterisation is the process of determining Lot Heterogeneity when approaching a new sampling project. There are two principal procedures of determining Lot Heterogeneity, Replication Experiment (RE) for Stationary Lots, and Variographic Characterisation (VAR) for Dynamic Lots. Heterogeneity Tests determine Constitutional Heterogeneity as the irreducible minimum obtainable of Sampling Variance, excluding all other Sampling Error effects.

M

Mass-Reduction

Mass-reduction is a physical process that divides a given quantity into manageable sub-samples. Mass-reduction must ensure that these sub-samples are representative of the original quantity (Representative Mass Reduction – Subsampling

Measurement

The total process of producing numerical data about a Lot, including sampling and analysis is called Measurement. Simultaneously, sensor-based analytical technology combines virtual sampling and signal processing. For both types of measurements the principles and rules of the  Theory of Sampling apply.

Measurement Uncertainty (metrological term) (MU)

MU expresses the variability interval of values attributed to a quantity measured. MU is the effect of a particular error, e.g. a sampling error, or an analytical error  or of combined effects (see MUTotal).

MUsampling reflects the variability stemming from sampling errors

MUanalysis reflects the variability stemming from analytical errors

MUtotal is the effective variability stemming from both sampling and analysis

MUtotal= MUsampling+ MUanalysis

Mixing / Blending

Mixing and blending reduces Distributional Heterogeneity (DH) before sampling/sub-sampling. N.B. Forceful mixing is a much less effective process than commonly assumed.

P

Particle-Size-Heterogeneity (PH)

PH is the compositional difference due to assemblages of units with different particle sizes (or particle-size classes).

Pierre Gy

The founder of the Theory of Sampling (TOS), Pierre Gy (1924--2015) single-handedly developed the TOS from 1950 to 1975 and spent the following 25 years applying it in key industrial sectors (mining, minerals, cement and metals processing). In the course of his career he wrote nine books and gave more than 250 international lectures on all subjects of sampling. In addition to developing TOS, he also carried out a significant amount of practical R&D. But he never worked at a university; he was an independent researcher and a consultant for nearly his entire career - a remarkable scientific life and achievement.

Precision

Precision is a measure of the variability of quantitative results. The larger the variability, the smaller the precision. In practice, precision is measured as the statistical variance s2 of the quantitative results (square of the standard deviation).

Primary Sample

The initial mass extracted from the lot. The Primary Sample is the product of Composite Sampling and consists of Q Increments. Both the mass of the Primary Sample as well as the number of increments extracted influence the sampling variability. As the primary sampling stage often has by far the largest impact on MUTotal, optimisation always starts at this stage.

Principle of Sampling Correctness (PSC)

The Principle of Sampling Correctness (PSC) states that all TOS' Incorrect Sampling Errors (ISE) shall be eliminated, or a detrimental Sampling Bias will have been introduced.

Principle of Sampling Simplicity (PSS)

PSS states that sampling along the Lot-to-Aliquot can be optimised separately for each (primary, secondary, tertiary ....) sampling stage. Since the Primary Sampling stage is often the dominant source of sampling error, optimization logically shall always begin at this stage.

Process Periodicity Error (PPE)

PPE is incurred if short-, mid- or long-term periodic process behaviour is not corrected for, in which case it may contribute to a sampling bias.

A process sampling strategy must make use of a high enough sampling frequency to uncover such behaviours; the sampling frequency must as a minimum always be higher than twice the most frequent periodicity encountered.

Process Sampling Errors (PSE)

PSE come into effect when Dynamic Lots are being sampled without compensating for process trends or periodicities (Process Trend Error and Process Periodicity Error).

Process Trend Error (PTE)

PTE occurs if mid- to long-term process trends are not corrected for, in which case they may contribute to a Sampling Bias. PTE and Process Periodicity Error PPE may, or may not, occur simultaneously depending on the specific nature of the process to be sampled.

Q

Q

Number of Increments composited to a Sample.

R

R

R is the number of replications of a series of independent complete ‘Lot-to-Aliquot’ Measurements, made under identical conditions applied in a Replication Experiment.

Replication Experiment (RE)

The replication experiment RE consists of a series of independent complete ‘Lot-to-Aliquot’ analytical determinations, made under identical conditions. The number of replications is termed R. RE provides MUSampling + MUAnalysis.

Representative Mass Reduction – Subsampling

Representative Mass Reduction (RMR) aka sub-sampling. TOS argues why Riffle-Splitting and Vezin-sampling are the only options leading to Representative Mass Reduction.

Representativity

A sampling process is representative if it captures all intrinsic material features, e.g., composition, particle size distribution, physical properties (e.g. intrinsic moisture) of a Lot.Representativity is a characteristic of a sampling process in which the Total Sampling Error and Total Analytical Error have been reduced below a predefined threshold level, the acceptable Total Measurement Uncertainty.
Representativity is the prime objective of all sampling processes. The representativity status of an individual sample cannot be ascertained in isolation, if removed from the context of its full sampling-and-analysis pathway. The characteristic Representative can only be accorded a sampling process that complies with all demands specified by TOS (DS3077:2024).

S

Sample

Extracted portion of a Lot that can be documented to be a result of a representative sampling procedure (non-representatively extracted portions of a Lot are termed Specimens).

Sampling

Sampling is the process of collecting units from a Lot (sampling procedure; sampling process): Grab Sampling or Composite Sampling. There are only two principal types of sampling procedures: Grab Sampling or Composite Sampling.

Sampling Accuracy

Closeness of the analytical result of an Aliquot with regards to the true concentration of the Lot]/glossary]. NB. “sampling accuracy” = “sampling + analytical accuracy”

Sampling Bias

The Sampling Bias is the difference between the true Lot concentration and the average concentration from replicated sampling. Such a difference is a direct function of the Lot Heterogeneity and as such inconstant; it changes with each additional sampling and can therefore not be corrected for. This is the opposite to the Analytical Bias for which correction is often carried out.

Sampling Error Management (SEM)

SEM determines the priorities and tools for all sampling procedures in the following order:

  1. Elimination of Incorrect Sampling Errors (ISE) (unbiased sampling)
  2. Minimisation of the remaining Correct Sampling Errors (CSE)
  3. Estimation and use of s2(FSE) is only meaningful after complete elimination of ISE
  4. Minimisation of Process Sampling Errors
Sampling Manager

The Sampling Manager is the Legal Person accountable for ensuring that all sampling activities are conducted in accordance with scientifically valid principles to achieve representative results. They are responsible for managing the design, implementation, and evaluation of sampling protocols while balancing constraints such as material variability, logistics, and resource limitations. This role requires expertise in the Theory of Sampling (TOS), leadership, project management and stakeholder communication skills.

Sampling Precision

The Sampling Precision is the variance of the series of analytical determinations, for example from a Replication Experiment (RE). Sampling precision always includes the Analytical Precision, since all analysis is always based on an analytical Aliquot, which is the result of a complete 'Lot-to-Aliquot' sampling pathway. Therefore sampling precision = sampling + analysis precision.

Sampling Protocol

Document explaining the undertakings necessary for the sampling process. It contains the tools and procedures from Lot-to-Aliquot[/glossary].

Sampling Scale Invariance (SCI)

The Principle of SSI states that all Sampling Unit Operations (SUO) can be applied identically to all sampling stages, only the scale of sampling tools differs.

Sampling Uncertainty

Sampling Uncertainty is the difficulty of collecting a representative sample due to Lot Heterogeneity; the more heterogeneous the material, the higher the uncertainty associated with any sample attempting to represent the whole Lot.

Sampling Unit Operations (SUO)
A Sampling Unit Operation is a basic step in the 'Lot-to-Aliquot' pathway. Five practical SUOs cover all necessary practical aspects of representative sampling: Composite Sampling, Crushing, Mixing/ Blending, Fractionation, and Representative Mass Reduction - Subsampling.
Secondary Sample

A secondary sample is the product of Representative Mass Reduction - Subsampling from a Primary Sample. Identical nomenclature applies for further Representative Mass Reduction steps (Tertiary...).

Specimen

A specimen is a portion of a larger mass/volume (Lot) extracted by a non-representative sampling process. Grab Sampling results in a specimen.

Stakeholder

A Stakeholder is any entity interested in the result coming from sampling and analysis. Data representing stationary or flowing heterogeneous materials are requested by different parties with a multitude of differing objectives. Stakeholders can be internal, from commercial organisations, public authorities, research and academia or non-governmental organisations.

Stationary Lot

A Stationary Lot is a non-moving volume of material where sampling is carried at from multiple locations, each resulting in an Increment. For both Stationary Lots and Dynamic Lots, sampling procedures must address the entire Lot volume guided by the Fundamental Sampling Principle (FSP).

T

Theory of Sampling (TOS)

TOS Theory and Practice of Sampling: necessary-and-sufficient framework of Governing Principles (GP), Sampling Unit Operations (SUO), Sampling Error Management rules (SEM) together with normative practices and skills needed to ensure representative sampling procedures. TOS is codified in the universal standard DS3077:2024.

Total Analytical Error

TAE is manifested as the Measurement Uncertainty resulting only from analysis (MUAnalysis). TAE includes all errors occurring during assaying and analysis (e.g. related to matrix effects, analytical instrument uncertainty, maintenance, calibration, other), as well as human error.

Total Measurement Uncertainty

Whereas Measurement Uncertainty (MU) is traditionally only addressing analytical determination, e.g. concentration := 375 ppm +/- 18 ppm (MUanalysis), Theory of Sampling (TOS) stipulates reporting analytical results with uncertainty estimates from both sampling and analysis.  This gives users of analytical data the possibility to evaluate the relative magnitudes of MUsampling vs. MUanalysis, enabling fully informed assessment of the true, effective data quality involved. A complete data uncertainty must have this format:

MUTotal = MUSampling + MUAnalysis

The attribute Total Measurement Uncertainty (MUTotal) is the most important factor determining the attribute data quality.

Total Sampling Error (TSE)

The Incorrect Sampling Errors (ISE) and Correct Sampling Errors (CSE) add up to the effective Total Sampling Error (TSE). TSE is causing the Total Uncertainty resulting from material extraction along the sampling pathway from-lot-to-aliquot (MUSampling).

Total Uncertainty Threshold

The acceptable Total Measurement Uncertainty, which must include the Sampling Measurement Uncertainty (MUSampling) and Analytical Measurement Uncertainty (MUAnalysis).

U

V

Variographic Characterisation (VAR)

Variography is a variability characterisation of a dynamic 1-dimensional dynamic lot. A variogram describes variability as a function of Increment pair spacing (in time). Variography is also applied in geostatisctics in describing the variability as a function of spacing/distance between analyses.