The transformation of data towards knowledge in eyes of the Positivist and the Interpretivist

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The transformation of data towards knowledge

in eyes of the Positivist and the Interpretivist

Author: Sean Imamkhan Student number: 11394404

University of Amsterdam - Faculty of Science (FNWI) Thesis Master Information Studies: Business Information Systems (BIS)

Final version: 17-08-2018 Supervisor: dhr. ir. A.M. (Loek) Stolwijk

Examiner: dhr. drs. A. (Arjan) Vreeken

Abstract. Positivism and interpretivism are respected epistemological standpoints, which are concerned with the question of ‘how to come to knowledge’ regarding society. The positivist uses the natural science approach to come to their knowledge of society, where the interpretivist uses a more humanistic approach of coming to their knowledge of society. In this study, the widely recognized DIKW hierarchy is been applied to the standpoints of the positivist and the interpretivist. The DIKW hierarchy states that data generate information, information generate knowledge and knowledge generate wisdom. Furthermore, as a frame of reference of how the positivist and interpretivist transform data into knowledge, data, information and knowledge are also separately defined as objects from the ontological positions of objectivism and subjectivism. Both ontology and epistemology refer to the definition of knowledge. Ontology is concerned with the question ‘knowledge of the existence of objects in the world’. The objectivist believes objects in the world exist apart from the social actor, where the subjectivist believes objects in world exist interdependent of the social actor. The ontological positions facilitate the transformation process of data towards knowledge, in the eyes of the positivist and the interpretivist. The findings of this study shows that the positivist follows a linear approach in coming to knowledge from information and data, this mean data, information and knowledge are following each other up in the transformation process, which is well in line with the assumption of the DIKW hierarchy. The interpretivist follows a non-linear approach in coming to knowledge from information and data, which mean there is no clear view of the transformation elements; data, information and knowledge in what is following each other up. In this study, the line between data and information is thin or even blurred, in case of the interpretivist.

Keywords. data, information, knowledge, data to knowledge, data transformation to knowledge, positivist, interpretivist, positivism, interpretivism, knowledge perspectives, objectivist, subjectivist objectivism, subjectivism, ontology, epistemology, ontological, epistemological, DIKW hierarchy, DIKW pyramid, DIKW assumption, DIKW, DIK, generation of knowledge, knowledge as input.

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The definition of knowledge is quite hard to pin down given the different perspectives on ‘what do we consider to be knowledge’ (Henriques, 2013; Rowley, 2007). Henriques (2013) mentioned that the oldest concept of knowledge refers to the theory of: Justified True Belief (JTB), stated by the Greek philosopher Plato. The JTB theory consist of: a mental representation about a state of affairs that corresponds to the actual state of affairs. This mean the actual state is true and the representation can be validated by logical and empirical factors of the believer (Henriques, 2013). But what is data? And how does data relate to information?

Data from a computer point-of-view, is something in its digital form, where it is been presented by binary values for transporting and showing the data or information on-screen (Rouse, 2017). This concept is based on the work of the father of information theory: Claude E. Shannon. Shannon prescribes data and information as logistics processes, where splitting the information in the smallest possible chunks of data (i.e. bits having the ability of possessing only two values; 0 or 1), plays a fundamental role in sending and receiving the (total) information (Jha, 2016). Russell Ackoff, a professor in organizational change and a system theorist, describes data as symbols that contain properties of objects and events. Information is something that consist out of processed data (Ackoff, 1999). Ackoff (1999) mention an example of that idea by illustrating the census taking concept. Census takers collect data and convert the results into tables. The converting step is where the data is been processed into information, in this case by presenting it in tables.

As stated before, there are different ways in approaching the concept of data, information and knowledge. In this research, the focus is on the scientific perspective of a positivist and an interpretivist, regarding the transformation of data towards knowledge.

According to Huizing (2007), the positivist perspective on knowledge is ubiquitous in knowledge and information theories. However, a millennium went over in discussing what knowledge really means, resulting in an unclear definition of knowledge. Therefore, the question of how to come to knowledge has always been a respected branch of philosophy (Huizing, 2007). Positivism and interpretivism are both scientific standpoints, or disciplines of how to come to knowledge (Bryman, 2012).

In 2007, Rowley found out that there is a less clear unified concession on the processes which leads to the transformation of data towards knowledge. According to her findings it is not clear if data, information and knowledge can be approached as three distinct concepts (‘objects’). In contrast however, Rowley (2007) mentioned that a certain relationship can be established from data to information, and from information to knowledge, hence at two levels instead of three. Data towards information is explained in terms of structuring data for attaining meaningfulness, usefulness, relevance and value to the data. Information towards knowledge is defined by

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understanding the operationalization or actionability of information (Rowley, 2007), for example, understanding how to put the information in practice (e.g. organizations).

In this research, the focus also lies in the transformation of data towards knowledge, but then studied in the eyes of the positivist and the interpretivist. The researcher is curious how those scientific standpoints come to knowledge, when data and information as (distinct) objects are been taking as precursors towards their knowledge claims. How do the positivist and the interpretivist come to know something? When the well-recognized assumption (Rowley, 2007) is taken that data generate information and information generate knowledge (Ackoff, 1989, 1999). In section 2.4. the elaborated research questions can be found.

Furthermore, this research is structured as follows: In the next chapter (2. Literature Review) the hierarchical development of data towards knowledge is explained. After that, the notions of positivism and interpretivism are further described, as they are scientific perspectives of how to come to knowledge, and the main subject of this study. Also, the ontology theory is explained, as it acts as a frame of reference and facilitator of how the positivist and interpretivist transform data into knowledge. Finally, the research questions along with the conceptual framework follows from that. In the chapter after the literature review (3. Methodology), the focus is on the methodology that is been used to gather the results of this research. This includes: A literature research is executed to 2 positivism and 2 interpretivism studies, regarding the transformation of data towards knowledge. Also, the ontology definitions of data, information and knowledge are studied in the literature to facilitate that transformation process. In chapter 4 (4. Results), the outcomes of the research questions are construed, which answers how the positivist and interpretivist transform data into knowledge, funded on the ontological definitions of what is data, information and knowledge. Chapter 5 (5. Conclusion), provides a short summary and a conclusion of this study. The conclusion unfolds that the positivist and the interpretivist both have their own way of coming to knowledge, from having information and data as precursors towards that generation of knowledge. The positivist follows a linear approach, which mean data, information and knowledge are following each other up in the transformation. The interpretivist follows a non-linear approach, which mean the line between data and information is thin, or even blurred in coming to generate knowledge. After the conclusion (6. Discussion & Limitations), the focus is on providing a critical (personal) reflection of this study, which include discussing the limitations and implications. Next to it, recommendations are given for future research. Finally, the research concludes with used references and the Annex A.

2. Literature Review

In the first part of this chapter, literature regarding the research area is been analysed and reviewed as building blocks for defining the research questions and the conceptual framework. The conceptual framework emerges in the last section of this chapter. 2.1. DIKW

What is Data? What is Knowledge? And how are those two related to each other in the development? As Rowley (2007) state in her paper: the DIKW (Data-Information-Knowledge-Wisdom) hierarchy is one of the best recognized model in information and

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knowledge literatures that describes the transformation, or the hierarchical development of data towards wisdom (Ackoff, 1989; Zeleny, 1987). It can be therefore agreed that the DIKW is a widely accepted and used model in information sciences and knowledge management (Hey, 2004; Sharma, 2008). According to Russell Ackoff (1989, 1999), which is been generally seen as the initiator of the DIKW hierarchy (Bernstein, 2009; Frické, 2009; Jennex, 2009; Rowley, 2007; Sharma 2008), the DIKW hierarchy is articulated as follows (Rowley, 2007):

- Data: symbols that represent objects, events and environmental properties. It is the product of observation by the senses. They are of no use until they can be structured (processed) into a relevant form;

- Information: processed data that is become useful (meaningful). They answer the ‘who’, ‘what’, ‘when’, ‘where’, and ‘how many’ questions. Information can be inferred from data. Meaning that raw data which is not been processed (yet), can become information in a later stadium. Technology can support the processing part of (loads of) data, by using its capabilities of generating, storing, retrieving and processing data into information. Not all data have to be used when becoming information. Because, not all the data might me relevant to produce the (desired) information1_{. As Boisot (1998) distinct data} from information, by stating that information is extracted and filtered from data;

- Knowledge: answers the ‘(know)-how-to’ questions. This is a further operationalization of information by embracing information in its function of providing instructions to execute a specific task for example in practice; - Understanding: answers and appreciate the ‘why’ questions. Bellinger, Castro,

and Mills (2004) elaborate, that it enables the capability to synthesis new knowledge from previous experienced knowledge or information;

- Intelligence: focus on increasing the efficiency of previous mentioned stages. Think of minimizing the amount of resources to process the same information, knowledge and understanding;

- Wisdom: focus on increasing the effectiveness, which result in adding value to the efficiency. This requires the involvement of the mental structure to assign a judgement to a certain situation. This judgement is inherent to the mental function, which embrace the ethical and aesthetic properties of the individual, and is therefore unique and personal (Rowley, 2007). As Ackoff (1999) defines it in his paper:

The difference between efficiency and effectiveness—that which differentiates wisdom from understanding, knowledge, information, and data—is reflected in the difference between development and growth. Growth does not require an increase in value; development does. Therefore, development requires an increase in wisdom as well as understanding, knowledge, and information. (Ackoff, 1999, pp. 1-2)

1_{For example: imagine there are a lot of blocks of wood on the ground. The blocks of wood} are considered as not of any use, and is therefore viewed as data. The blocks are structured into a relevant form, in this case into a physical table. By structuring into a relevant form, information is created (Rowley, 2007). On the ground, there are still a lot of blocks of wood (data) remaining, in this example, not all the data has been used to produce the desired table (information).

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Furthermore, Bellinger et al. (2004) believes, wisdom is a unique human state which requires one to have a soul, where Jessup and Valacich (2003) define wisdom as accumulated knowledge, which allows to understand how to apply concepts from one situation to others. Also, wisdom relate having the capability to act critically or practically in any situation, which is connected to an individual’s belief system (Jashapara, 2005). Meacham discuss wisdom as the manner in which knowledge was held, and the way it was put in practice (Sternberg, 1990). Rowley (2006) studied different definitions of wisdom and came up with the following summary: “the capacity to put into action the most appropriate behaviour, taking into account what is known (knowledge) and what does the most good (ethical and social considerations)” (p. 257).

Ackoff is not the only one who mentioned the articulation of the DIKW hierarchy (Rowley, 2007). The first mention of the hierarchy stems out of poetry, which was acknowledged by Harlan Cleveland (Sharma, 2008).Cleveland (1982) mentioned poet Thomas Stearns Eliot as the first one who suggested the hierarchy implicitly. In 1934, Eliot wrote for the chorus The Rock: “Where is the life we have lost in living? Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?”. Another mention of the hierarchy was made by Frank Zappa in 1979, which mention also had a connection to the arts. Zappa (1979) song: “information is not knowledge, knowledge is not wisdom, wisdom is not truth, truth is not beauty, beauty is not love, love is not music and music is the best”. Milan Zeleny mentioned the hierarchy in 1987 (two years before Ackoff mentioned it). He articulated the hierarchy into forms of knowledge metaphors. This contains: ‘know-nothing’ (referring to: data), ‘know-what’ (referring to: information), ‘know-how’ (referring to: knowledge), ‘know-why’ (referring to: wisdom) (Rowley, 2007; Sharma, 2008).

Ackoff mentioned ‘intelligence’ and ‘understanding’ as additional layers (Ackoff, 1989). Zeleny (1987) mention ‘enlightenment’ as a layer above wisdom, which is about gaining the sense of truth, defining the sensibility of right and wrong, and getting it accepted and respected on social level. Zeleny linked the ‘enlightenment’ layer to the knowledge metaphor of ‘know-yourself’ (Zeleny, 2011). Choo (1996) mention ‘signals’ as the input for data creation. The transformation of signals into data is been made by sensing, selecting (i.e. physical structuring) the signals.

Bellinger et al. (2004) disagree with having understanding as a separate layer. They approach understanding on each level that support the transition of data towards wisdom. In their eyes, data is a fact, event or statement without relations. Information is about attaining understanding of relationships, for example, connecting cause with effect. Knowledge is about understanding patterns, like predicting the next step based on previous experienced connections. For example: if A happen, and B follows from that, the chance is plausible that C happen. The transition of knowledge to wisdom builds on understanding principles, which embodies knowledge into an amalgamation of understanding the knowledge of being what it is. For example: It is A, because it is A. This knowledge claim is based on understanding all the systemically interacting elements which develop in claiming: A is A.

A remarkable thing to mention, is that the DIKW hierarchy is not a confirmation of one of the oldest and dominating definition of knowledge by Plato (Mutongi, 2016), which refers to the: justified true belief (JTB) theory (Henriques, 2013). Plato defines the JTB theory by stating something to be knowledge (Lacewing, 2015):

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1. When somebody believes something is true (e.g. subject A believes object B exist);

2. the object exists (i.e. it is true that B exist) and;

3. it can be justified that object B exists (e.g. subject A can touch object B). Mutongi (2016) explains that the DIKW hierarchy is not a confirmation of Plato’s knowledge theory, because the JTB theory claims that something is considered as knowledge, when it is possible to justify-it-true-belief, and the DIKW hierarchy states that knowledge is always generated by information, whether it is justified or not.

Summing this part up, it is outlined that the DIKW hierarchy is articulated by different people in different ways, and different layers or perspectives were stated by different people. However, the most shared known view result into the DIKW model (Rowley, 2007) as displayed in figure 1.

Figure 1. The DIKW hierarchical model

Figure 1 illustrate that there can be no wisdom without knowledge, there can be no knowledge without information, there can be no information without data (Ackoff 1989). Secondly, it is displayed as a pyramid, since transforming into a higher state leads into filtering elements in the lower stages (Rowley, 2007). In other words, there is less information than data, less knowledge than information and less wisdom than knowledge (Jennex, 2009). Also, Ackoff (1989) mention that higher layers include layers that fall below it (p. 3).

In the next section, the emphasis is on elaborating the concept of positivism and interpretivism, as this study investigate how the positivist and the interpretivist come to their knowledge claims, when the widely recognized DIKW hierarchy (Rowley, 2007) is been followed, which states that data generate information and information generate knowledge (Ackoff, 1989, 1999).

2.2. Definition of Knowledge

What is knowledge? The definition of knowledge is quite hard to pin down regarding the different perspectives on ‘what do we consider to be knowledge’. According to Gregg Henriques Ph.D., the theory of knowledge refers to two philosophers’ angles:

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epistemological and ontological considerations (Henriques, 2013). In the next subsections, the ontological and epistemological theories are explained, where objectivism and subjectivism relate to ontology, and epistemology to positivism and interpretivism.

2.2.1. Epistemology (Positivism & Interpretivism)

Social researcher Professor Bryman (2012) view about epistemological is described as: what is regarded as acceptable knowledge in a discipline2_{. That consideration can be} tackled from positivism and interpretivism. A positivist defines acceptable knowledge studied from a natural science point-of-view. Which can be characteristics by a more objective view of approaching knowledge, testing knowledge according to fundamental laws and principals, and gathering facts that provides the basis for laws to be tested in social reality. This is external from the (personal) values of the researcher, which can be stereotyped with quantitative research methods and deductive (testing theory) research strategies. Auguste Comte (1798-1857) is been seen as the founder of the term Positivism. Auguste was a French philosopher who introduced the term in the 19th century in his books: Course in Positive Philosophy and A General View of Positivism3_.

Auguste believed that society could be studied in a way the physical world is been studied. As gravity is a truth in the physical world uncovered and explained by natural laws, the same laws and methods could be applied in studying the social world. Also, positivism believes that society should be studied with the senses, which therefore appreciate rigid and linear applied methods (Crossman, 2018).

Interpretivism captures a more subjective meaning of defining what acceptable knowledge is, rather than studying them from an objectivism point-of-view, which is preferable as a positivist. An interpretivist sees social sciences separately from studying the natural sciences. Researchers that take the role of an interpretivist are more or less concerned about the (in-depth) empathetic understanding of contextual human behaviour, which include moving themselves in the point views of people’s actions, emotions, thoughts and so on. This can be stereotyped with qualitative research methods and inductive (generating theory) research strategies (Bryman, 2012). Interpretivism roots itself in the philosophical studies of hermeneutics and phenomenology, also the German sociologist Max Weber (1864-1920) is commonly being credited as the central influencer of interpretivism in sociology (Chowdhury, 2014). Weber developed the theory of verstehen (‘understanding’), which is a German term meaning: to understand, to perceive, to know and to comprehend the nature and significance of a phenomenon in question (Elwell, 1996). Weber uses verstehen for understanding both human action and intention in context. Achieving verstehen, can be reached by empathetic understanding the human actions from their points views (Chowdhury, 2014).

2_{I.e. the science of how to come to knowledge (Huizing, 2007).}

3_{Auguste’s books are translated from French to English. The book series Cours de}

Philosophie Positive, were published between 1830 and 1842 (Barnes & Fletcher, 2017), and freely translated by H. Martineau into the form of The Positive Philosophy of Auguste Comte (Referring to: Course in Positive Philosophy), published in 1853 (The Editors of Encyclopaedia Britannica, 2018). A General View of Positivism by J. H. Bridges, which was published in 1865 (Bridges, 1865), was a translation of Discours sur l'ensemble du positivisme, published in 1848 (Gane, 2006).

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Concluding this part, the interpretivist engages the perspective of the people been studied in defining the multiple perspectives view on reality, instead of accepting one, (natural) reality, as in case of positivism (Greener, 2008). The difference between natural sciences and social sciences, can be approached as the difference between explaining (erklären) and understanding (verstehen), as the German philosopher Wilhelm Dilthey (1833-1911) express this view in understanding Geisteswissenschaften (i.e. understanding the human mind or mental appearances) as opposite of natural science (Bransen, 2001).

2.2.2. Ontology (Objectivism & Subjectivism)

Bryman (2012) defines ontological considerations as: studying the existences of objects in the world in relation to their observations by social actors. This can be studied from objectivism and constructivism. As an objectivist, social actors and the objects in the world exist independently from each other. For example: A flower exists without the existence of a human. As Huizing describe objectivism as: “we should view the world as consisting of distinct objects that can and should be separated from their originators and users” (Huizing, 2007, p. 74). In case of constructivism, social actors and objects in the world don’t exist independently from each other. The meaning and existence of objects are socially construed. Applying the example of the flower to a constructivism point-of-view, the flower only exists when it can be captured by the values of the human mind (i.e. it only exists when we can see it with our eyes). Another aspect of the constructivism point of view is that the definition of a flower can change over time. Since, social constructions and their values about objects in the world may also change4 over time (Bryman, 2012). Huizing defines the view of Bryman’s constructivism as subjectivism (Huizing, 2007). He describes subjectivism as: “we should focus on human beings and see them as acting on the world through sensemaking, and in that way modifying the context they live in” (Huizing, 2007, p. 92). Subjectivism emerged itself in the twentieth century after dissatisfaction with objectivism having a central role in science. This does not imply that subjectivism took over the central role of objectivism. Mostly, subjectivism is approached as different thinking with regard to objectivism thinking. However, there is an increasing view on knowledge and information being approached as a social phenomenon, rather than (economic) external objects5_{, according to Huizing (2007) on subjectivism. One notable definition of the} subjectivism view is that knowledge emerge by studying the inherent properties of objects in the world in relation to their interactions with social actors (interactional features), which can result into attaching a (personal/symbolic) meaning to the object in question (Huizing, 2007).

In this study, the notion subjectivism and constructivism are merged by using the term subjectivism, as their meanings are closely related to each other. According to the researcher’s conclusion of studying both definitions, the differences is that one pays more attention to the dynamic and the change in social constructions, to be able to observe surrounded objects and linking meaning to them (constructivism). The other

4_{E.g. changing beliefs about the meaning of the existence of a flower, due gaining new} knowledge and/or undergo changes in the current social construction, which can result in a different (world) view about a flower.

5_{An example of an objectivist and subjectivist view: from a subjectivist, a rose (object) can} act as a symbol of love (social phenomenon). Where the economic value of the rose (e.g. status of the thorns), is related to the objectivist view (Huizing, 2007), think of selling the rose.

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focus more on the interactional relationship between social actors and the inherent properties of the objects, for attaching (symbolic) meanings to a certain object (subjectivism). The similarity can be found that both notions concern the dependencies of human involvement- and- values on the existence of objects in the world, which also mean that objects do not necessary retain fixed meanings (Bryman, 2012; Huizing 2007).

2.3. Bridge to Research Questions (relevance research)

The previous sections described the DIKW hierarchy, ontology and epistemology, where positivism and interpretivism refer to the latter. In this part, the bridge or relevance of this study towards the research questions is explained.

The DIKW hierarchy state that knowledge can only be generated by already having information and data generated. Also, it is discussed that positivism and interpretivism are unique scientific views of how to come to knowledge. As Huizing (2007) state: “epistemology or the science of ‘how people come to know’ is and has always been a respected branch of philosophy” (p. 98). Nevertheless, it is therefore worthy to investigate how the positivist and interpretivist come to knowledge, when the widely recognized DIKW hierarchy is been followed (Rowley, 2007). In other words, this research gives insight in how the positivist and the interpretivist come to knowledge, from information and data as precursors. These insights are relevant, since the positivist and the interpretivist do knowledge claims in their own manner (Bryman, 2012). It is therefore interesting to gain some transparency of how they come, or reach knowledge by applying the DIKW hierarchy. The DIKW hierarchy is chosen, since it is widely recognized and accepted in knowledge and information literature, as mentioned in 2.1. This research test at the same time, if the DIKW is (still) valid, by embracing the hierarchy from the perspective of the positivist and the interpretivist.

In the end, this research gives insight or transparency in the generation of knowledge as the positivist and the interpretivist. This is relevant, since those scientific perspectives both come in accepting knowledge from their discipline (Bryman, 2012). The known DIKW hierarchy is applied to enable transparency in reaching knowledge from information and data. At the same time, this research test if the DIKW assumption is valid by connecting the perspective of the positivist and the interpretivist towards it.

Concluding this part, the following main research question emerges in this study: 2.4. Research Questions

“What are the differences and similarities in the transformation of data towards knowledge between perspectives of the positivist and the interpretivist?”

What are the differences and similarities between the positivist and the interpretivist, when knowledge is achieved from information and data as precursors. To be more specific, data function as raw material for information and information as raw material for knowledge (Ackoff, 1989, 1999; Rowley, 2007). Differences are expected, since the positivist and the interpretivist have both their unique way in attaining and accepting something to be knowledge (Bryman, 2012). If so, similarities between those two perspectives will be clarified to examine if that manifest in a unified image of reaching knowledge, having data and information as input for that knowledge.

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As mentioned before, knowledge also refer to ontology (Henriques, 2013; Huizing, 2007; Bryman, 2012). To gain a whole image of reaching knowledge as a positivist and an interpretivist, the researcher also investigated the ontological questions of ‘what is’ data, information and knowledge. This for defining their existence as (distinct) objects in the world, before diving into ‘how’ the positivist and the interpretivist come to their knowledge. In other words, before knowledge is extracted from information and data, as a positivist and an interpretivist, the existence of data, information and knowledge is defined from an objectivist and a subjectivist, to connect ‘how’ that is achieved, with ‘what’ does exist. In short, the ontology act as a frame of reference for the epistemology part, and at the same, support the transformation process of data towards knowledge in the eyes of the positivist and the interpretivist, which is further explained in the methodology chapter.

The following sub questions represent the what is questions to meet the discipline of ontology, as from the perspective of an objectivist and a subjectivist:

1. “What is Data?” 2. “What is Information?” 3. “What is Knowledge?”

How the positivist and interpretivist come to knowledge, builds on the generation of information and data, since this study follows the assumption of the DIKW hierarchy, which result into the following sub questions, from the perspective of a positivist and an interpretivist:

4. “How is Data been achieved?” 5. “How is Information been achieved?” 6. “How is Knowledge been achieved?”

The how is questions refers to how to come to knowledge as a positivist and an interpretivist, which meets the discipline of epistemology.

The research questions are captured in a conceptual framework, which is been visualized and explained in the next section.

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2.5. Conceptual Framework

Figure 2. The Conceptual Framework (CF)

Figure 2 shows the conceptual framework (CF) that is been used to gather results of this research study. The CF synthesis different theoretical concepts into one integrated framework to be taken as viewpoint for executing this research (Imenda, 2014).

In this framework, data, information and knowledge are placed in the ontological oval-diagram, which refers in defining their existence as (distinct) objects as an objectivist and a subjectivist. The arrows refer to how data leads in achieving information, and how information leads in achieving knowledge, both captured in the eyes of the positivist and interpretivist. The arrows navigate outside the oval-diagram, since its represent the epistemological consideration. Although, the input and output of the arrows are connected to the ontological oval-diagram, to establish a relationship between epistemology and ontology. The relationship is needed, since both refer to the two philosophers’ angles of knowledge (Henriques, 2013).

Figure 2 is not presented as a pyramid, as one might would expect. Because the interest is on the transformational aspects, rather to investigate if there is less knowledge, than information and less information than data. Secondly, wisdom is not included in the CF, since positivism and interpretivism regards to knowledge, which already is achieved after generating information (Ackoff, 1989, 1999).

In the next chapter, the mechanical operation of the CF is been explained, which include the elaboration of how the results of this research is gathered and analysed.

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3. Methodology

Positivism and interpretivism have both their unique way of coming to knowledge, where positivism believes society should be studied with the same principles as natural science, interpretivism believes society should be studied apart from using natural science (Bryman, 2012). This difference result in both using their own methodologies approaches for studying society, which are outlined in table 1 (Carson, Gilmore, Perry, & Gronhaug, 2001;Jamieson, 2009; Weber, 2004):

Methodology approaches Positivism Interpretivism

Relationship between reality and research

Obtain hard, objective knowledge

Focus on generalization and abstraction

Governed by hypotheses and stated theories

Deductive approach (testing theory) (Bryman, 2012)

Understand / gain knowledge by perceiving (subjective)

Focus on specific and concrete Trying to understand specific context

Inductive approach (generating theory) (Bryman, 2012)

Focus researcher Describing and explanation (erklären)

External, detached Reaching reliability

Understanding (verstehen) and interpreting

Internal, attached Reaching validity Role researcher Distinction between reason and

feeling

Use rational, consistent, rigid, logical approaches

Distinction between facts and value judgments

Distinct between science and personal experience

Allow reasoning, but also feeling (no clear distinction)

Use of pre-understanding (prior knowledge)

Less distinction between facts and (personal) value judgements Accept personal experience along with science

Specific methods Prefer Quantitative methods Prefer Qualitative methods Data is mostly statistical and

direct measurable for quantitative and analyse purposes. This means it is possible to observer trends, correlations (e.g. erklären laws of human behaviour)

Data is detailed, like coded interviews to achieve (in-depth or rich) verstehen (e.g. understanding human perceptions)

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Variables can be controlled (e.g. fixed static questions)

Variables are less or not controlled (e.g. people as variables are unpredictable)

(Online) Surveys, laboratory experiments, field experiments, structured interviews

Case studies, unstructured interviews, ethnographic studies, phenomenographic studies, and ethnomethodological studies (e.g. internal observing and participating) Table 1. Positivism and Interpretivism overall methodology approaches

The author did a qualitative research in form of a literature study to 2 scientific selected Master’s theses6_{with regard to positivism and 2 with regard to interpretivism. The} content of table 1 is used to determine if a study concern to positivism or interpretivism. A literature research is executed, because the methodologies approaches of table 1 is traceable in their research studies, since the methodology is a key part of a research or thesis (SkillsYouNeed, 2018). Worth to mention is, that table 1 doesn’t necessarily imply that positivists can’t never use qualitative methods (Su, 2017), or that interpretivists can never use quantitative methods (Babones, 2016), and/or that each focus area needs to be treated in their studies. The focus in determining the researcher perspective, regards if the researcher tries to reach verstehen (interpretivist) or erklären (positivist) (Bransen, 2001), whether that is achieved with quantitative or qualitative methods. Table 1, therefore only function as a guided framework.

Furthermore, the theses are further studied for making the connection with the epistemological arrows of figure 2 (i.e. the transformation of data towards knowledge, in eyes of the positivist and the interpretivist), which include: in the methodology part of a research its written what kind of data will be collected and how (Statistical Training Unit, 2010),this is therefore linked with achieving data as a positivist and an interpretivist. In the results/conclusion part of a research, data is been processed/structured (analysed) into a meaningful form (presented findings of the data) (Monash University, 2018), which is therefore linked with achieving information as a positivist and interpretivist. In the discussion part of a research, the information of the results section is coloured with limitations, personal interpretations, where the researcher’s interpretation can be based on common sense (Swaen, 2014), Boisot (1998) defines common sense as knowledge that is widely diffused, but not codified (p. 58). The discussion section can also be linked with information that is combined with understanding and capability, which lives in the minds of people (Laudon & Laudon, 2006), since the researcher should express his or her thought about the validity, based on the gained insights (Swaen, 2014), thus moving from information to knowledge (Rowley, 2007), achieved as a positivist and an interpretivist7_.

The definitions of data, information and knowledge are also studied in the literature to have it scientifically argued, where their existence as (distinct) objects is

6_{On request of the supervisor, Master’s theses of the University of Amsterdam are selected} (where he fulfilled the role of supervisor or second examiner (second reader) regarding the theses), since the structure of those theses are well arranged according to the requirements of an academic research, which also include describing the methodology (University of Amsterdam - Faculty of Science, 2016).

7_{The positivist and interpretivist studies are studied in their whole, rather than studying the} chapters fragmentally. This for gaining an overall understanding of how data leads to knowledge.

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determined by the ontological tendency of objectivism and subjectivism, as outlined in table 2 (Bryman, 2012; Huizing, 2007):

Objectivism Subjectivism

Objects in the world exist independently from social actors

Objects in the world exist interdependent from social actors

Objects have economic values Objects have symbolic values Objects retain static meanings Objects can have variable meanings Focus on the inherent properties of objects Focus on the interactional features of objects

Table 2. Objectivism and Subjectivism main criteria’s

It is been tried to capture only definitions that could be strongly connected to the criterions of table 2, this for covering the load of objectivism and subjectivism. The existence is justified for each definition regarding ‘what is’ data, information and knowledge. The ontological part act as a frame of reference of serving the transformation process of how data, information and knowledge is achieved as the positivist and the interpretivist, with what does exist as the objectivist and the subjectivist. Furthermore, each epistemological part regarding achieving data, information and knowledge as a positivist and an interpretivist, is also justified by providing some transparency from the studied theses.

After the ontological and the epistemological questions are researched, the answers of those considerations are assembled into a coherent framework, which function as answer to the main research question of this study:

“What are the differences and similarities in the transformation of data towards knowledge between perspectives of the positivist and the interpretivist?”

Enumerating this chapter up into the following research steps to be executed: 1. 2 positivism and 2 interpretivism Master’s theses are selected to be studied,

concerning the transformation of data towards knowledge. Table 1 is used as a criterion to determine if a master’s thesis concern to positivism or interpretivism, before processing them;

2. After choosing 2 positivism and 2 interpretivism studies, the chapters of the theses are investigated for making the connection with data, information and knowledge. The method chapter function as achieving data, the results/conclusion chapter as achieving information, and the discussion chapter as achieving knowledge, this as a positivist and an interpretivist; 3. The ontological definitions of data, information and knowledge are studied in

the literature, and justified according to the tendency of objectivism and subjectivism, as outlined in table 2. The ontological consideration function as a frame of reference of how the positivist and the interpretivist comes in achieving knowledge, from information and data. The ontological questions are therefore first researched to connect how the positivist and the interpretivist comes in knowledge, with what does exist in terms of data, information and knowledge, as an objectivist and subjectivist;

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4. Concluding, the outcomes of the positivist and the interpretivist (epistemological), and the objectivist and the subjectivist (ontology) are assembled into a coherent framework, which display how the positivist and the interpretivist transform data into knowledge. In this step, the ontological outcomes act as a facilitator for that transformation process. The ontological part has two functions as one might notice. First, it acts as a frame of reference, and secondly it facilitates the transformation process of data towards knowledge, in the eyes of the positivist and the interpretivist.

4. Results

The analysed data concerning the ontological and epistemological research questions are answered in this chapter. The first part regard to ontology, where the existence of the definitions of data, information and knowledge is justified as an objectivist and/or subjectivist. The second part provides results of how the positivist and the interpretivist comes in achieving knowledge, data and information. The epistemological part is also justified. In the last part, the outcomes regarding ontology and epistemology are assembled into a coherent framework, which shows the transformation of data towards knowledge, in eyes of the positivist and interpretivist.

4.1. What is Data?

Definitions (O) / (S) Justification

Data as bits;

Data from a computer point-of-view, is presented by binary values (i.e. splitted into bits; having the ability of possessing only two values; 0 or 1) for transporting or processing the data (Rouse, 2017). This concept is based on the father of information Theory: Claude E. Shannon. See also Annex A for the connection between data (bits) and information (constructed bits).

O Data as binary values (arranged bit values)8_{can present texts,} images, sounds or videos on the computer (Rouse, 2017). This is connected to an objectivism view, since the data is stored in the computer and not in the human mind. Where the computer (object) exist apart from the human (social actor). However, the input of the data into a computer, could come from the human mind (Tuomi, 1999).

Data as interpretation;

Subjectivists emphasize that data can be interpreted in various ways. Since people have unique mental frameworks about the world (which can be due differences in social and cultural values) (Huizing, 2007).

S This is connected to subjectivism since its embracing the symbolic meaning of data (object), connected to the social actor believes. In this case data is been interpreted and understood by the recipient (Bocij, Chaffey, Greasley, & Hickie, 2003), which also show the thin line of data towards information, and the relationship of data and information (Rowley, 2007). This also suggest that meaning of data is subjective. What one (social actor) sees as information (object), the other might see as data with no real significance

8_{8 bits is one 1 byte (Rouse, 2017). For example: 00101011 (8 arranged bits) could} represent a word (data structured into information).

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(Boddy, Boonstra, & Kennedy, 2005; Jashapara, 2005). Data as recorded item;

Data items are recorded descriptions of events, things, transactions and activities (Boddy et al., 2005; Laudon & Laudon, 2006; Turban, Rainer, & Potter, 2005).

O/S Objectivism:

If a data item is only recorded in a computer (e.g. IT-database), then it exists without the human, since the data is stored in the computer, where the computer (object) exist apart from the human (social actor).

However, the input of the data into a computer, could come from the human mind (Tuomi, 1999).

Subjectivism:

If a data item is only recorded in the human mind, where that data is not yet structured into a useful relevant form (Ackoff, 1989; 1999). Than that data only exists, when the holder (in this case the human) of that data exist.

Table 3. Definitions of Data regarding Objectivism = O and Subjectivism = S 4.2. What is Information?

Information as an object;

Objectivists sees information as objects, which can be quantified, measured and traded for attaining economic value. (Huizing, 2007)

O Information as an object can be processed stored and secured in computer databases to protect their economic value. Which can be connected to objectivism. Also disembodying information from people’s mind and converting it into decontextualized and standardized objects is the goal of the objectivist, as mentioned by Huizing (2007).

Information as a difference; Subjectivists sees information as a difference, that makes a difference to hearer or reader. More specific, it focusses on the interpretation and human sense making for attaining meaning to the information in question (Huizing, 2007).

S This is a subjectivism view, as stated by Huizing (2007). Including: Information is handled in ways that suit their social practices (Putnam, 1983).

Even how people are dressed can affect how information is been used (Fiske, 1991). Also, the meaning of information to a social actor can differ, when he or she arrives in different contexts, but also the same information can differ to person A in comparison to person B (e.g. due different personal values, beliefs (OpenStax CNX, 2018), experiences and other personal references, which can influence the human sensemaking, individually). Information in this sense, is approached as social phenomenon rather than (economic) objects (Huizing, 2007).

Information as transmission;

Claude E. Shannon sees information as physical quantities, were the focus lies on exchanging information between sender and receiver, by deconstructing information into the smallest chunk of data (i.e. bits) to be able send it over channel (line), were the bits are been reconstructed into information, as

O

This approach of information can be connected to an objectivism view. Since the focus here lies on the exchange of the message (information), rather than the person's possible biased view on the message. It embraces a transactional view of information exchange, unidirectional.

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intended by the transmitter (Shannon, 1948).

Claude E. Shannon is known as the father of information theory (Rouse, 2017). See the Annex A for an extended description about his information theory.

Information as communication: Subjectivists approach information transmission in a form of interaction, non-anonymously relationship, bidirectional where both sender and receiver assign the same symbolic meaning to the message been exchanged.

(Huizing, 2007).

S This is a subjectivist view of information communication, where the symbolic meaning is an aspect of subjectivism. This also mean that the meaning of a message is not necessarily fixed, because the meaning of message can change during the process of social interactions, which is due intersubjective perceptions on a message meaning (Huizing, 2007).

Table 4. Definitions of Information regarding Objectivism = O and Subjectivism = S 4.3. What is Knowledge?

Explicit Knowledge;

Nonaka & Takeuchi (1995) mention explicit knowledge as knowledge that is (hard) codified, documented, readable, disembodied and treated as objects (Beynon-Davies, 2002), designed for sharing (Rowley, 2007).

Boisot (1998), and some other researchers (Hedesstrom & Whitley, 2000), point explicit knowledge as codified knowledge.

O This view is connectable to objectivism, because when there is explicit knowledge (object), it can exist without the existence of the human (social actor). For example: knowledge that’s been documented, exist on its own. Of course, it's arguable if explicit knowledge regard to knowledge, when knowledge is by many authors considered as the property of human mind (Rowley 2007), where explicit knowledge is disembodied from the human mind (Nonaka & Takeuchi, 1995). Although, explicit knowledge fits Ackoff’s (1989) view on knowledge, which answers (know)-how-to questions in form of providing instructions. Procedural knowledge is a form of knowledge that refer to an

instructional approach, as how to do something (Henriques, 2013). For example: how to something in context of a training course, could be knowledge that is been codified (Awad & Ghaziri, 2004).

Tacit Knowledge;

Tacit knowledge is knowledge that is integrated in the beliefs and values of the individual, which make the knowledge intangible (not touchable), and therefore difficult to transfer (Nonaka & Takeuchi, 1995; Polanyi, 1962, 1967; Laudon & Laudon, 2006).

S This form of knowledge can be connected to subjectivism, since tacit knowledge (object) is inherent to the human (social actor) mind (Bocij et al., 2003). This also implies that tacit knowledge not necessarily retain static meanings, because values and beliefs of a person is also not necessary static. Values and beliefs can vary over time, as people evaluate and debate their current state, for example when trying to

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Philosopher and scientist Michael Polanyi9_{introduced the idea of tacit} knowledge in the fifties (Polanyi, 1962, 1967; Hedesstrom & Whitley, 2000), by stating: “we know more than we can tell” (Polanyi, 1966, p. 4). He refers to the aspects of hard to encode (e.g.

documenting the knowledge) and hard to communicate (because the knowledge is embedded in the individual’s mind) (Nonaka & Takeuchi, 1995; Polanyi, 1962, 1967).

integrate to another culture’s values system10_(OpenStax CNX, 2018).

Tacit knowledge can also be connected to knowledge as an asset by Boisot (1998); Boisot (1998) describes that knowledge approached as an asset, act differently in comparison to physical assets. Where physical assets can be sensed as materialized products, knowledge assets can be approached as dematerialized products. This implies that knowledge assets could exist forever11_{from a theoretical} point-of-view, since they can be seen as dematerialized (intangible) products, which doesn’t rust like a physical (materialized) bicycle for example.

Tacit knowledge can also be linked with personal knowledge, which refers to first-hand experience, autobiographical facts and idiosyncratic preferences (Henriques, 2013).

Knowledge as an object;

Objectivists sees knowledge, as tradable objects, like information. This means knowledge is disembodied and codified into objects to extract and protect its economic value (Huizing, 2007). Knowledge as objects can also be linked to explicit knowledge, since explicit knowledge is also disembodied from the human mind into objects (Nonaka & Takeuchi, 1995; Tuomi, 1999).

O People who embrace objectivism believe that knowledge can be fully captured in objects, and that those objects have meanings on themselves (Huizing, 2007). The focus in determining the price or economic value is on the distribution of knowledge, rather the use / meaningfulness of knowledge objects. Knowledge and learning consist of representation from practice, where objective information is absorbed and stored in the mind (Huizing, 2007). This form of learning can be connected to behaviourism and cognitivism (Abcouwer & Smit, 2007). Where behaviourism focus on the positive behaviour of learning something, think of processing feedback, and cognitivism focus on obtaining (objective) knowledge, internally focused (Trago & Mulder, 2017). Knowledge as a social phenomenon;

Subjectivist sees knowledge as social phenomenon’s, which focus on interactions and negotiations to attain usefulness (Huizing, 2007).

S This can be connected to the subjectivism view of knowledge. Since knowledge emerge by interacting with other social actors, which makes the meaning of knowledge socially constructed. This also implies that knowledge do not necessary retain static values, as their meanings getting

9 _{Polanyi mentioned an example of the tacit knowledge concept in his book: The Tacit}

Dimension, where he stated that a human knows to recognize a person across a thousand or even a million persons. Still, it is not possible to completely communicate (transfer of knowledge) how the person’s is been recognized (Polanyi, 1966).

10 _{An example of differences in culture values and beliefs: two male colleagues holding} each other hands in the United States, is been often associated with the symbol of romantic feelings. Where, holding each other hand in Africa, is been considered as a symbol of friendship (OpenStax CNX, 2018).

11_{However, the economic value of a certain knowledge asset can lose its value over time} (Boisot, 1998), like when using yesterday knowledge to overcome today’s and tomorrow's challenges (Trago & Mulder, 2017). Dr. Chipo Mutongi (2016) provides an explanation in her paper about the value change of knowledge over time: “some years ago a person who could have contracted the HIV virus was least expected to live for more than ten years but with the antiretroviral therapy, today, a person can live for so many years and who knows tomorrow a cure could be found” (p. 68).

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mutually (re-)constructed by gaining new insights due interactions and/or negotiations (Huizing, 2007). This form of knowledge can be linked with the approaches of

connectivism, which focus on learning by making

connections (Siemens, 2004), being a member of a network is important to achieve knowledge (Trago & Mulder, 2017), making a bridge with other circles or constructions can lead into heterogenic (novel) information or knowledge, due differences of similarities by the other party (Granovetter, 1973). And constructivism, which states that people put meaning in their own way by (re)arranging concepts, based on integrating new knowledge into their current knowledge system, due gaining new insights and/or experiences (Trago & Mulder, 2017).

Table 5. Definitions of Knowledge regarding Objectivism = O and Subjectivism = S 4.4. How is Data been achieved?

The Master’s theses of Chen (2018) and Wesselink (2018) are selected for positivism, and the theses of Boeve (2018) and Ablinger (2018) for interpretivism.

How is data been achieved as the positivist? Justification

The positivist achieve data by retrieving and filtering data from (online) IT-databases, where data-columns are specified to represent the data-attributes name or type of data (e.g. time, name, frequencies. Constructed bits values i.e. data as bits). This can be linked to data as recorded item as an objectivist, since the data represent ‘things’ regarding the research focus, and the data exist apart from the researcher.

Chen (2018) gathered data by distributing his survey online on LinkedIn in different groups and communities to cover a broad geographic area. Wesselink (2018) collects data by filtering and retrieving data from internal databases of G4S, CBS, Rijkswaterstaat (RWS), and Koninklijk Nederlands Meteorologisch Instituut (KNMI). The dataset consists out of columns and consist of types as: time, location, message, activity and so on). Data is also filtered according to the relevance, or things of the researcher focus (Wesselink, 2018).

Both Chen (2018) and Wesselink (2018) accessed

information systems (IT) for the collection of data (Rowley, 2017).

How is data been achieved as the interpretivist? Justification

The interpretivist achieve data by being aware of the context in which the data should be collected. This mean that the interpretivist encounters the perspectives and settings of the participants, during the collection of the data, for increasing its validity and sensemaking (enriching the data). This is linked to data as interpretation, since the positivist verify the interpretations of their collected data, with the participants.

Boeve (2018) state in her paper: “the ecological validity has been warranted by conducting all nine

interviews in the interviewee’s natural atmosphere, in their office or their homes” (p. 9). Which mean the setting of the data been collected is taken into account. Furthermore, Boeve (2018) describe the focus on the collection of data is on words, which she refers as trying to understand their participants12_{different perspectives in the collection}

12_{In this study, ‘respondent’ refers to researched object(s) with regard to positivism, and} ‘participant’ refer to researched object(s) with regard to interpretivism. This terminology is based on how the positivist and the interpretivist approached their researched object(s) in their study. In

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process. Also, the interpretation of the data is validated by providing the outcomes of the collected data, with the participants (Ablinger, 2018; Boeve, 2018). Boeve (2018) state explicitly that she follows an interpretive research approach in her paper.

Table 6. Data achieved as the positivist and the interpretivist 4.5. How is Information been achieved?

How is information been achieved as the positivist? Justification

The positivist transform data into information by applying statistical methods to the data. The data is then presented into a structured form (data becomes information), mostly tables (Ackoff, 1999) or visuals (e.g. scatterplots), that present numeric (quantify) values. This can be linked with

information as an object, since its purpose regards to finding relationships (correlations) or patterns measured between different data variables, based on quantifiable information, for accepting or rejecting hypothesis. In case of information exchange (e.g. sending or receiving surveys), it embraces a unidirectional communication between sender (researcher) and receiver (respondent), where the focus lies on exchanging the message, which can be linked with information as transmission.

Chen (2018) and Wesselink (2018) both used statistical methods (like SmartPLS) to analyse and structure the data into a structured form. E.g. Wesselink (2018) used statistical methods to explain (erklären) correlations, an outcome given from her paper: “H7: There is no correlation between storm has and the number of notifications” (Wesselink, 2018, p. 9). The next example shows structured information of a Cronbach’s Alpha (statistical) test by Chen (2018):

Figure 3. Data structured into an informational form (Chen, 2018) The input of the survey (information) are gathered when they are filled in by the respondent, this is after a month of collection, in case of Chen (2018).

How is information been achieved as the interpretivist? Justification

The interpretivist encapsulates different perspectives, beliefs and values with regard of achieving information, this can be linked with information as a difference. The line between data and information is thin, or even blurred in case of the interpretivist, since the information is based on enriched data, where enriched data is rooted by information of the

participants views. The information exchange (e.g. unstructured interviews) can be linked with information as communication, since the emphasis is on understanding the participant perspective (bidirectional), when exchanging messages.

Boeve (2018) describe that she did qualitative research in form of interviews to understand (verstehen) her participant perspectives. Secondly, interviews are executed to align the interpretation of gathered information with the participants (Ablinger, 2018). Furthermore, new questions were asked during the semi-structured interviews for gaining a rich image of their participant perspectives. This is referred as in-depth interviews. The interviews were transcribed and coded to make sense of the gathered data, or information (Boeve, 2018).

Table 7. Information achieved as the positivist and the interpretivist

case of positivism: data (e.g. survey) is been unidirectional filled in by the respondent, and in case of interpretivism: data is enriched by letting their researched objects participate in validating the collected data.

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4.6. How is Knowledge been achieved?

How is knowledge been achieved as the positivist? Justification

The positivist achieve knowledge by evaluating the information, which include discussing the reliability of the data been collected, and how representative the data is for generalization and its use for the future (‘operationalization of the information’). They base their claims on their insights, where those claims are also linked to their tacit knowledge. An example: a positivist values different personal interest, sensed during a semi-structured interview, as biased13 (Wesselink, 2018). That view is described from her perspective in the discussion section of the research, which make the knowledge claim at the same time explicit. This can be connected to Polanyi’s view about seeing tacit knowledge as the precondition for explicit knowledge. Where tacit knowledge underlines all the explicit knowledge available, by making tacit knowledge ‘explicit’ (Tuomi, 1999).

Wesselink (2018) discuss the reliability of the data that represent her study, which include: that the data might be outdated over time, also a full data saturation is not been reached during several setbacks occurred in the research process.

Chen, (2018) also discuss the reliability of the data been used in his study. He states: “first of all, it was assumed that participants provided their answers honestly in the survey. To facilitate the honest reply, participants were informed about anonymity and confidentiality before participants of the study” (Chen, 2018, p. 12). Chen (2018) also gives suggestions for future research, which include collecting a larger sample size to represent a better characterization of the population (generalization aspect).

How is knowledge been achieved as the interpretivist? Justification

The interpretivist achieve knowledge by making ‘sense’ of the information, where that information is built by the perspectives of participants. They make sense of it by institutionalizing those perspectives, into their knowledge claim, by giving the different social actors voices, which is connectable with knowledge as a social phenomenon. Also, the interpretivist makes use of tacit knowledge by integrating the participants perspectives into their values and beliefs system, when making a knowledge claim. Boeve (2018) does this by merging the result and discussion chapter into one. This is because there is a less distinction between reasoning and feeling regarding the role of an interpretivist as mentioned in table 1. The knowledge becomes in a certain degree14_{explicit, since the outcome of their knowledge} claims is described in their theses (referring to codified knowledge).

Boeve (2018) gives different stakeholder (social actors) perspectives voices by encapsulating their perspectives into the result & discussion section of her research. After that, she creates a line between different perspectives, which result into a converged knowledge claim. From her paper: (1) “the stakeholders agreed upon two points. All involved want a more sustainable alternative for heating.” (2) “two stakeholders expressed their concerns with regard to time. The intensive collaboration that is needed between the involved stakeholders is time consuming” (Boeve, 2018, pp. 15-16). Also, Ablinger (2018) describe the use of social actor perspectives in her knowledge claim. She states that more participants should be interviewed in future, to create more measurements indicators regarding her research topic; process mining.

Concluding the interpretivist knowledge approach: “I am also grateful to the interviewees for their kind inputs that greatly improved my insights on the energy transition, though the interpretation here remains my own” (Boeve 2018, p. 19).

Table 8. Knowledge achieved as the positivist and the interpretivist

13 _{Where in the case of interpretivism, a biased (person’s view) could be considered as} valuable knowledge (Bryman, 2012).

14_{In a certain degree explicit, since some parts of the tacit knowledge becomes explicit} (Tuomi, 1999). Furthermore, this is because when knowledge is codified its losing the authentic beliefs, and values (referring to disembodying knowledge from the human mind, as mentioned before).

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4.7. The transformation of data towards knowledge in eyes of the Positivist and the Interpretivist

Based on the previous sections, a framework is created, where the transformation of data towards knowledge in eyes of the positivist and the interpretivist is clarified. Figure 4 display the positivist view, and figure 5 the interpretivist view. Only the ontological aspects that facilitate the transformation process, are absorbed and included in the frameworks.

Figure 4. The transformation of data towards knowledge in the eye of the positivist

The positivist view is linkable to the DIKW hierarchy, since the transformation follows a linear path as can be seen in figure 4. Data exist in its unstructured form (e.g. data in columns), where data is retrieved unidirectional (information as transmission), (e.g. one-way sending survey, output, and one-way receiving survey, input15_{). It becomes} information when statistical (rigid) methods structure the gathered data into a relevant form, like tables. After that, the information is discussed regarding their representativeness, which lead in understanding the information capabilities (i.e. moving to ‘knowledge’).

Figure 5. The transformation of data towards knowledge in the eye of the interpretivist

15_{One might expect an arrow from information towards data, regarding the information} transmission of the respondent towards the researcher (e.g. the respondent sends the filled survey to the researcher). This arrow is left out in figure 4, because the focus in the frameworks are on the transformational aspects, rather than embracing its communication exchanges on its own.

The transformation of data towards knowledge in eyes of the Positivist and the Interpretivist

The transformation of data towards knowledge

in eyes of the Positivist and the Interpretivist

Table of Contents