On-site Information Findability: Towards an integrative view

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On-site Information findability:

towards an integrative view

MASTER THESIS WITHIN: Informatics NUMBER OF CREDITS: 30

PROGRAMME OF STUDY: Information Architecture and Innovation AUTHORs: Rients Wiebren Johannes van Blanken, Zdeněk Šrejber JÖNKÖPING May 2020

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Master Thesis in Informatics

Title: On-site Information findability: towards an integrative view Tutor: Daniela Mihailescu

Date: 2020-06-03

Key terms: Findability, Information Architecture, and Social Informatics

Abstract

A major component of the internet are websites which each have their information architecture, but more importantly, findability. This thesis focusses on the topic of findability, which is defined by Morville as “The quality of being locatable or navigable” (Morville, 2005, p. 4). Findability has become more crucial due to an increasing amount of information and time people spent on searching and gathering information. This motivation has led to the aim of investigating findability through insights into, and a delineation of, two complementary perspectives: information architecture and social informatics. Empirical evidence was collected through semi-structured interviews with design practitioners, and a literature review was conducted to provide an integrated view of findability.

The STIN-model and berry-picking model provide a frame of reference which designers can use to improve the findability of their digital platforms. The most predominant suggestions based on the empirical evidence are as follows. Firstly, designers should remember that they are problem solvers and should always use methods appropriate to the problem that needs to be resolved. Secondly, designers should start with problem analysis, which should combine qualitative and quantitative methods to reach the optimal results with regards to user research. Finally, do not reinvent the wheel, make use of already existing tools that incorporate upgradeability and reusability.

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Figure 1 Honest work (KnowYourMeme, n.d., p. 1)

Acknowledgments

After two years of study, the final product of our work has been completed. Zdenek and Rients are proud to present this thesis, but before we can do so, there are some people we would like to thank. Firstly, we would like to thank Daniela Mihailescu for her guidance, feedback, and motivational support. We also thank Andrea Resmini for being our mentor and for teaching us invaluable skills which we can utilize for the rest of our lives. Our thanks also goes out to all the interviewees who have helped us to gather the required data. We would also like to thank all the colleagues and friends we had the opportunity to meet in this master. Moreover, our thanks also go to our friends and families who supported us during the master studies.

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1 Introduction

Huge mainframes computers stored inside large buildings evolved and decentralized into personal computers located on every office desk. Personal computers have spread from office desks to households. Single household computers evolved from a family-owned machine to several individually owned computing devices (Šrejber et al., 2019).

At the moment of writing, there exist 1.7 billion websites on the world wide web (Internetlivestats, 2020). All these websites have their own goals, content, and audience, but that also means much information is available in different shapes and forms and can be accessed from different sources. Consequently, and maybe ironically, this presents a challenge in finding a single, specific, desired piece of information. Each website has different qualities and features of findability, but besides the differences between these websites, they have something in common, design!

There is a critical issue of matching a website’s content to the preferences and needs of its users. “Most importantly, 61% of users said that if they did not find what they were looking for right away on a mobile site, they would quickly move on to another site” (Hendron et al., 2014, p. 3). Moreover, an adaption of content to be available and findable on different device types is of significant importance.

1.1 Problem Discussion

McKinsey executed a study about the Social Economy and found that individuals spend 19% of their time workweek on searching and gathering information (2012). Based on a 40-hour workweek, an individual would spend almost 8 hours, or a full workday, by just searching and gathering information. Due to the increasing amount of time people spend online searching and gathering information, the findability of information on websites has become a point of concern.

In the last thirty years, society has changed from “an industrial to an information society, in which the main targets and the results for the majority of the employed population will be information products and services” (Kolin, 2011, p. 460). This societal shift has created

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an urgent need for Information and Communication Technology (ICT) to “store, retrieve, transmit, and manipulate data or information” (Rennie & Law, 2009). For this reason, “today there is an objective social need for a systematic study of the information society in the field of scientific knowledge and disseminating it through a modernized educational system” (Kolin, 2011, p. 460).

The impulse for research of the findability problem arose from the personal experience of the authors, who faced troubles regarding the findability of information. The existence of this issue was further reinforced by the discussion with peers, who also expressed similar or identical problems when looking for information. Although the literature on findability exists and is available, the authors believe that theory is not being 100% utilized in real-world design.

A gap can be identified in how websites are designed so that software and web users can find the desired information. The application of Information Architecture standards allows designers to improve the findability of information on their websites, but this problem persists. Therefore the authors have decided to make information findability the topical subject of study and the question of immediate interest for both research and practice.

1.2 Objective

The objective of this master thesis is to review existing literature on findability and identify potential perspectives which combined with designers' work experiences provide insights and contribute to an integrative view on on-site information findability. To achieve that following research questions are addressed:

RQ1: What perspectives and frameworks can be derived from literature that provide insights into on-site information findability?

RQ2: What conceptual elements, which are being used by designers, exist and how do they provide insights into on-site information findability?

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1.3 Scope and limitations Scope

The scope of the thesis is focused on an exploration of information findability through Information and Communication Technologies (ICT), mainly accessed via the internet. This research provides an insight into fields of information findability.

The available literature is explored for theoretical knowledge, practitioners are interviewed to gain knowledge about their current processes and toolsets, and suggestions for digital design practitioners are provided and discussed. Lastly, the identification of potential areas and directions for further detailed research is also an expected outcome. The contribution of this research will include: a theoretically and empirically grounded integrative view on information findability.

Limitations

One of the main priorities and challenges in terms of limitation of qualitative research is acquiring a representative sample profile and achieving data saturation within the time frame of this thesis. Time and planning were essential factors as scheduling interviews, processing literature and gathering data were expected to be time-consuming activities. Another limiting factor, especially for the scope and planning of the research, was that the research was conducted as an expected student thesis starting in January 2020 and finishing in May 2020. The authors also had to plan according to lectures and workshop structure presented by the university.

The final factor that was introduced during this thesis was the COVID-19 global pandemic. This global pandemic forced the researchers to conduct their interviews via digital means, which left out body language and other aspects that can add value to data collection.

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1.4 Thesis structure

To visualize how this thesis has been structured, the following figure is provided. This figure is intended to provide a bird’s-eye view of the research.

Figure 2 Thesis structure

Phase A: the literature review, will provide different insights and perspectives into findability. Phase B will use the knowledge about findability and compare it to the results gathered from interviews. Afterward, the results of these steps will be analyzed and will provide a conclusion and a discussion.

1.5 Definitions Actant

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Ambient Findability - by Morville (2005, p. 6),

“who describes it as a world, where we can find anything or anyone from anywhere and at any time, and this is the world we should be striving to create around us, as it doesn’t exist yet”.

Designer

Person that uses their creative abilities to design tangible or intangible products, services or experiences, in order to solve an identified problem.

Findability - by Morville (2005, p. 4):

• “The quality of being locatable or navigable.”

• “The degree to which a particular object is easy to discover or locate”

• “The degree to which a system or environment supports navigation and retrieval.”

Information

What is Information? Information can be either physical, semantic or digital. Physical information is a perceived representation of the physical environment around us, semantic is perceived representation of communication between people and digital one arose after the introduction of ubiquitous ICTs and is perceived information transferred through digital space. (Hinton, 2014b)

Information Architecture – by Resmini (2014a, p. 85):

Information architecture is an applied art that solves the “problem arising when we need to manage, produce and consume large amount of information”.

Social Informatics is (Kling, 1999, p. 1)

“the interdisciplinary study of the design, uses and consequences of information technologies that takes into account their interaction with institutional and cultural contexts”

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2 Literature review

In this chapter, the review of literature related to information findability will be discussed.

2.1 Findability

The current state of findability

The act of searching and gathering information has been an activity of the human race since the start of time. However, we cannot always find the information we are looking for. Findability is the field of study that focusses on the findability of information and is defined by Morville as (2005, p. 4):

• “The quality of being locatable or navigable.”

• “The degree to which a particular object is easy to discover or locate”

• “The degree to which a system or environment supports navigation and retrieval.” Hendron et al. define four distinct aspects of findability: “(1) on-site search, (2) related links and products, (3) site match to customer needs and preferences, and (4) cross-device experience” (2014, p. 2).

Hendron et al. identify a type of findability that is concerned with information on a webpage: “On-site findability is concerned with the ability of a potential customer to find what they are looking for within a specific site” (2014, p. 1).

A way we design and use findability tools in the software, especially the web, has evolved from a physical space. Even in the pre-digital era, the physical environment was a major factor in how humans name and describe newly introduced artifacts and actors. The example presented by Morville (2005) is “homo erectus”, meaning “upright man” explain that this specie of human had straight back and its head up. Consequently, physical space is also a reason we say, for example, “go there … and there …” in the context of visiting a website. This works well for humans as, in our understanding, we can relate newly identified artifacts to artifacts/concepts that we already know from our experience. Moreover, even when social actors search for something new, they use known

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information and concepts, that are already know to them, even though it might not be 100% related to desired search results. (Rosenfeld et al., 2015)

As searching and gathering information has been a fundamental part of humanity, Morville further explains that: … “What we find influences what we do. But the first step is deciding to search, and the smallest of barriers will deter us. The primacy of accessibility is among the firmest ties that bind our rationality” (2005, p. 212). Since the smallest barriers will deter us from even starting to search and gather information, it becomes vital that information on websites, is findable for the user. The adage of: “You Can't Use What You Can't Find” (Morville, 2005, p. 160), perfectly describes this.

Models

Any time, any human makes such a search, the term “Human Information Interaction (HII)” can be used, as it describes the way users interact with information, regardless of which medium used for access or connection (Morville, 2005). HII can be viewed as a sub-set of the Human-Computer Interaction (HCI) field and is optimized for network information systems with a focus on user-centered methods and dynamic multi-channel behavior. Morville (2005, p. 59) states:

In such environments, users may find and interact with information objects though variety of devices and interfaces. The emphasis shifts from interfaces to information.

A lot of work in this field was done by Marcia J. Bates and the Berrypicking model she has introduced (Morville, 2005). Bates suggested that the usage patterns for information

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retrieval are not represented well with simple models where only one query can accomplish the desired results, as shown in figure 7.

Figure 3 Classic information retrieval model (Morville, 2005, p. 59)

Instead, Bates introduced the Berrypicking model, figure 8 below. What the berry-picking model aims to explain is that sometimes social agents have only limited or no knowledge (thought) about the desired search result (information that leads to Exit). By executing the repeating process of varying queries and retrievals of information, social agents slowly and gradually increase their knowledge that will eventually allow them to find the desired information. This model is thus a more accurate representation of the information retrieval journey each social actor undergoes on a regular basis.

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Going through the user journey of searching for information, it is crucial to mention there exist push and pull information. Push information is when information is pushed on the user, such as an aggressive advertisement or spam emails. Pull information, on the other hand, is something that the user desired to find within the network or system. Morville (2005) mentions an imbalance between the two, where the push is more dominant and takes up much more of the real-estate of websites. Marketing departments especially focus on pushing for the push information, mainly home pages of websites. Morville also urges designers that they need to “push for pull” and come up with designs where push and pull are in balance, and thus achieve ideal user-friendliness.

Additionally, Hendron et al. define several examples that the impact of findability has on a website:

74% of consumers get frustrated when content, offers, ads, or promotions on a website appear that have nothing to do with their interests. This decreases conversion rates and increases bounce rates, thus decreasing the overall findability of products across the site. As a result, companies that don’t invest time in site design, content creation, and recommendations that are relevant to their customers pay an enormous price (2014, p. 3).

Klyn (2010) introduced the concepts of Ontology, Taxonomy, and Choreography in the Information Architecture field. Moville (2005) in his book Ambient Findability he left out choreography and instead talks about Folksonomy. Choreography, defines interaction rules among the relationships. Folksonomy, in contrast, lets the users define such rules and relationships and can be thus viewed as an extension of taxonomy and choreography by employing users, people, folks in the process.

To evaluate folksonomy, we need to know about controlled vocabularies. Controlled vocabularies are pre-designed arrangements of words used to index information in high quality. A disadvantage is that such vocabularies can cover only a limited quantity of information (Morville, 2005). This disadvantage could be mitigated by the employment of folksonomy, where users can extend the missing parts. Thus, designers can and should

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embrace a design that enables and promotes the involvement of users. That way, indexation can cover a larger quantity of information, a self-explanatory real-life example can be wiki websites.

Summary

Findability could be defined as the quality and degree to which a particular object is easy to discover or locate and the quality and degree to which a system or environment supports navigation and retrieval(Morville, 2005).

Findability on the web has evolved from a physical space. The physical environment was a key factor in how humans name and describe newly introduced artifacts and actors. Furthermore, Morville explains that “What we find influences what we do. Nevertheless, the first step is deciding to search, and the smallest of barriers will deter us. The primacy of accessibility is among the firmest ties that bind our rationality” (2005, p. 212). Moreover, McKinsey executed a study about the Social Economy and found that individuals spend 19% of their time workweek on searching and gathering information (2012). Based on a 40-hour workweek, an individual would spend almost 8 hours, or a full workday, by just searching and gathering information.

From the overview of available model and Frameworks, both Berrypicking model by Bates and Folksonomy approach has proven to be a useful tool for design (Morville, 2005). Berrypicking is the model that replaced simple retrieval and more accurately maps user journeys during information retrieval. At the same time, folksonomy adds the benefit of potential user-generated content to the design of the solutions (e.g. user-generated tags, descriptions, and playlists).

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2.2 Information architecture

History of IA

With the ever-increasing amount of information in today’s world, the need to arrange information has never been more substantial. Resmini & Rosati define Information Architecture as: “Information architecture is the discipline that: Information architecture (IA) is a professional practice and field of studies focused on solving the basic problems of accessing, and using, the vast amounts of information available today” (2011, p. 33). However, this problem has been in existence far before the introduction of computers: “Around 330 B.C., ancient Egypt’s Library of Alexandria listed its contents in a 120-scroll bibliography” (UX Collective, 2017, p. 1).

The modern-day version of Information Architecture was brought to attention by, among others, Richard Saul Wurman. He used the term ‘Architecture’ in combination with ‘Information’ at the American Institute of Architecture conference of 1976 (Resmini & Rosati, 2011).

In 1998 an essential artifact in the development of Information Architecture was introduced: Information Architecture for the world wide web: “the book dealt with the increasing difficulty Wurman was experiencing in communicating rising amounts of information and presented a large selection of design solutions to the problem. It was a designer’s book: from a designer, for designers” (Resmini & Rosati, 2011, p. 37). This bookmarked the beginning of a new chapter in the world of IA and, in retrospect, can be seen as the cornerstone of ‘classic IA’. Its introduction led to information architecture becoming mainstream (Resmini & Rosati, 2011).

Further development of the Information Architecture field was sparked when: “Users were entering the scene as producers (or prosumers, a term acknowledging their mutated role as both consumers and producers of information), tagging was everywhere, and personal mobile devices and home appliances were redrawing the boundaries of computing” (Resmini & Rosati, 2011, pp. 41–42). The aforementioned advancements created the need for pervasive and ubiquitous Information Architecture as people were

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Figure 5 Moving into pervasive information architecture

spending an increasing amount of time in cyberspace. The following figure illustrates the timeline from classic IA to pervasive and ubiquitous IA (Resmini & Rosati, 2011, p. 43):

Now that we have taken a brief look into the history of Information Architecture, we will move on to understand its current state.

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13 The current state of IA

In today’s world, information architecture is past the point of being connected just to library science or aimed at web site design improvements. These were concerned with labeling, organization systems, navigation, search, and sorting systems. However, the ubiquitous blend of physical and digital space is the additional factor that has to be considered by current IA research and practice. E.g. social actors consume information in a different social and environmental context, through the usage of different mediums, devices, and technologies.

A definition of Information Architecture, according to Resmini (2014a, p. 85) is as follows:

Information architecture is an applied art that solves the “problem arising when we need to manage, produce and consume a large amount of information”.

Nevertheless, what is Information? Information can be either physical, semantic, or digital. Physical information is a perceived representation of the physical environment around us. Semantic is a perceived representation of communication between people, and digital one arose after the introduction of ubiquitous ICTs and is perceived information transferred through digital space. A factor for consideration is that while physical and semantic information is natural, digital information is wholly artificial and human-made. Digital information itself is not readable by humans, only computers can read it, but such information can be explained to humans through translation and means that we know from physical and semantic context. (Hinton, 2014b)

The definition of architecture concerning IA by Hinton (2014b, p. 104):

”This work is an act of architecture: the structuring of raw information into shared information environments with useful, navigable form that resists entropy and reduces confusion. This is a new kind of architecture that designs structures of information rather than of bricks, wood, plastic and

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stone (…) People live and work in these structures, just as they live and work in their homes, offices, factories and malls. These places are not virtual: they are as real as our own minds.”

As presented by Lacerda & Lima-Marques (2014, p. 8), Information architecture can be characterized by the following parameters:

• IA has a specific and relevant object of study • IA is inherently transdisciplinary

• IA has a growing community of scholars and practitioners • IA plays a significant and necessary role in society

• IA is experiencing a new context of framing with the rise of ubiquitous information spaces

Klyn (2010) explains his view of Information architecture in three concepts: 1. Ontology – understanding the meaning, its patterns, and rules

2. Taxonomy – arrangement of systems and structures to accomplish a task 3. Choreography – defining interactions rules among the relationships

With the increasing number of available information, it is becoming harder and harder for social actors to navigate within the ecosystem of digital artifacts and finding the desired information. To improve the findability of information is one of the focuses of IA. The adage “cannot see the forest for the threes” fit the situation perfectly.

The term “affordance” needs an explanation to understand the upcoming paragraph. Affordance is a term used for evaluating the opportunity for action, in the context of this research, it is an opportunity to find and retrieve the information. The term originates in the physical environment where animals evaluate the opportunities to gain an advantage in survival (Gibson, 1986).

As established previously, there is information all around us, and social actors might become overwhelmed by it. New devices create new interaction points and change the affordance of information for social actors. To manage this problem, a concept of Ambient findability was introduced by Morville (2005, p. 6), who describes it as a world,

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where we can find anything or anyone from anywhere and at any time, and this is the world we should be striving to create around us, as it doesn’t exist yet.

Definition of “ambient” by Morville (2005, p. 4) : • “Surrounding; encircling: e.g. ambient sound” • Completely enveloping

According to Hendron et al. (2014), we can split findability into external and on-site. Although very frequently used for business and marketing purposes, these principles also apply for the findability of any other information. External findability is concerned with “brand awareness” and search engine optimization (SEO) in case of online searches, in a setting of physical space, SEO is replaced with a “visible” location. Physical location and/or SEO are there both to ensure social actors can easily find the desired information. External findability is not the aim of this thesis. Once social actors land on the corresponding website or visit desired physical space, on-site findability is the primary concern. On-site findability has far bigger control over the experience of social actors. Many factors, such as navigation, structure, graphics, content, have a direct influence, and are part of the Information Architecture field.

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As presented by Degler (2014), one of the essential features of every good digital ecosystem, supported by IA and user experience, is a seamless transition between different roles of social agents. Different agents have a different origin, purpose, responsibility, and activity they intend to execute. Thus, the experience must be designed accordingly, either by predicting the behavior of social agents or even better by monitoring their activity, learning, and adapting the system. Such a process allows for human/centered approach in design by considering:

• Meaning of information and their relationships • Change of information on change of meaning • Change of relevance over time

• The amount of information and sustaining a relevance upon its increase

(Degler, 2014) Rosenfeld et al. (2015) describe several models of architecture when social actors look for information. Most frequently “too simple” model is used, where an actor asks a question, magic happens, and the final answer will display´. However, this model does not represent reality, its too straight forward, does not consider context or social actor as a factor for the search.

There are different situations, sometimes simple search could be enough, but other times social agents want to execute an in-depth, detailed search, or there might be a situation when they do not know what they are looking for.

In a nutshell, a quality findability solution always considers many factors related to the search, considers a change of actor’s needs and desires, may even suggest what it is that actor wants, and learns from every executed action to improve any future interaction with an actor.

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17 Frameworks

This section will delve deeper into what frameworks exist within Information Architecture.

Big Information Architect, Little Information Architect

From the introduction of Information Architecture into the world, two frameworks or perspectives were the primary focus: Big Information Architect and Little Information Architect. In his column with the same name, Morville defines Little Information Architect as: “the little information architect may focus solely on bottom-up tasks such as the definition of metadata fields and controlled vocabularies” (2000, p. 1), and defines Big Information Architect as: “the Big Information Architect may play the role of "an orchestra conductor or film director, conceiving a vision and moving the team forward” (2000, p. 1).

Big IA and Little IA have been the subject of much discussion, and have had an impact on the way people view the field of Information Architecture. Big IA’s approach gave rise to user-oriented principles. However, it also has a weakness: “Big IA has not developed deeper reproducible structures that can help designers understand how elements of a website shape dynamics between people and contribute to larger organizational structures.

By not having reproducible structures, Big IA’s impact is of a smaller nature compared to little IA. The consequence of this lesser impact is that Big IA is past its sell-by date and will not be used by designers/academics as a framework to guide their process. The cause of this problem is as follows: “Big IA was born during the consulting boom of the early 2000s, and as such, many Big IA practitioners are outside consultants. A custom-built approach for each project earns consultants more money” (Jaffe, 2019b, p. 1). As the primary driver of Big IA was to generate more income for the business, its value contribution toward the future was not viable.

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On the other end of the spectrum exists Little IA. According to Jaffe, “Little IA provides the structural approach to information architecture that Big IA lacks” (2019, p. 1). However, Jaffe also adds:

But Little IA has only defined structures that relate to navigation, search, and way-finding. This gap makes sense when understanding the development and positioning of the field. Little IA emerged from library science, and librarians are largely concerned with the organization of books and records to help people find them.

With this focus on navigation Little IA architects have developed important concepts such as hierarchical structures, taxonomies, and matrices (2019, p. 1).

As can be deduced from this quote, little IA’s impact cannot be underestimated, and they have contributed to improving website’s findability, information architecture, and overall improved structure. This has led to an increasing level of maturity for the field of Information Architecture.

However, as with Big IA, Little IA also lacks something: “What Little IA architects have not done is to develop an understanding of how structure impacts online environments outside of navigation” (Jaffe, 2019b, p. 1). Search Engine Optimization (SEO) is something that Little Architects have not taken into account. SEO can be defined as an essential component of external-findability (Hendron et al., 2014). As Little Architects have concerned themselves with on-site findability and information architecture, they have left the element of external findability by the side.

Big IA and Little IA each have their own merits and vices, but the overall takeaway is that they are frameworks and thereby tools to create digital structures. The choice for a digital structure is permanent and has stark repercussions on design and the overall information system later on in the process of creation.

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19 Jaffe identifies the third framework:

At the heart of the Structural language for information architecture is the search for a cohesive design language to give people more power to directly express what kinds of interactions they want to have. The Structural Information Architect fights for digital structures that can create emergent pockets for creative play, cafes for respectful debate, newsstands where people can purvey a broad range of opinions, reading nooks for quiet reflection. As we need public spaces in the physical world, so too do we need these kinds of spaces online (2019, p. 1).

The primary takeaway from these schools of thought and frameworks is that there exists a preeminent need to have a unified language for Information Architecture. As Information Architecture is the backbone and structure of many digital artifacts, it calls for a unified language.

Unified language

Context is the key to understanding how the world around us works. As described in the ‘current state of IA’, Information Architecture is the process of ‘making sense of things’ or sense-making in short (Resmini, 2014b). Hinton captures this in his book Understanding Context:

To make sense of the world, we’re always trying to place things in context, whether our environment is physical, cultural, or something else altogether. Now that we live among digital, always-networked products, apps, and places, context is more complicated than ever—starting with “where” and “who” we are (2014, p. 1).

Hinton’s explanation offers a perspective that pinpoints the importance of context with the creation of Information systems. This impacts how context plays a role in the way products and services should be designed so that they serve the end-user.

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As Hinton’s work articulates the importance of context in design, so indicates Jaffe the significance of a unified language for the design of information systems:

Defining these elements is so important because unlike in architecture and urban design, there is no centuries-long agreement of what basic information units are in the digital world and how they function. . . . In the digital world, there are lots of different individual visual design languages created by different companies, but no general functional language that can be used across different products (2019a, p. 1).

For this reason, Jaffe proposes ‘A Unified Language for the Design of Information Systems’ (2019a). Jaffe explains the building blocks of her proposed unified language:

It begins with fundamental units like objects, channels, and groups (letters), that build into modules (words), which combine to form blocks (sentences) and coalesce into platforms (books). This shared language can help designers better build online interactions across many different products and companies (2019a, p. 1).

Objects

“The basis of digital structures are objects. Objects are anything that can be conceived as one. What is viewed as “one” changes based on the goal of the system” (Jaffe, 2019a, p. 1).

Object groups

“Objects can be structured in many different ways. Object groups are multiple objects that are linked together in a meaningful way” (Jaffe, 2019a, p. 1).

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“Objects are connected to each other via channels. Channels are connections between objects that exchange information. Channels can be designed to transmit low or high levels of information between objects” (Jaffe, 2019a, p. 1).

Energy

“As a designer your system is in constant competition with all other systems that people can interact with for their time, attention, and energy” (Jaffe, 2019a, p. 1).

Levers

“Levers are tools to change the energy demand of a system or alter energy inputs. There are four different types of levers: affordances, mechanics, map generation, and games” (Jaffe, 2019a, p. 1) .

Base Dynamics

“The combination of an object, a channel, and a lever is called a base dynamic. Base dynamics are a one directional transfer of information. (Person or object) + channel + lever= base dynamic” (Jaffe, 2019a, p. 1).

Loops

“A loop is two connected base dynamics, or a user action and a response to this action. Base dynamic + base dynamic = Loop” (Jaffe, 2019a, p. 1).

Modules

“Modules are combinations of loops and objects into simple interactive units. They might be perceived as the equivalent of chairs and tables in the physical realm, or individual words in a language” (Jaffe, 2019a, p. 1).

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22 Blocks

“Blocks are multiple modules organized to create emergent interactions” (Jaffe, 2019a, p. 1).

Platforms

“If modules are like chairs and tables, and blocks are similar to sidewalks and playgrounds, platform structures are more like neighborhoods or cities” (Jaffe, 2019a, p. 1).

The above-described framework offers designers the opportunity to create a unified language for the creation of information systems. By using the same language as a perspective to create products and services, designers will be able to communicate their ideas to other designers as well as clients more clearly and understandably. This framework can help designers with the creation of any kind of digital product or service.

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Information Architecture framework for the Internet of Things

Information Architecture can be applied to any discipline where large amounts of information are involved. The Internet of Things (IoT) is a phenomenon whereby a plethora of devices that are connected to the internet, create information. Lacerda, Lima-Marques, & Resmini propose an information architecture framework for the Internet of Things (2019). The framework is made up of 16 principles that have been categorized into three high-level categories: Human, Architectural, and Systemic (Lacerda et al., 2019, p. 9):

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24 Human principles

Principles belonging to the human perspective identify guidelines that support the design of Internet of Things artifacts considering their subjective characteristics, the emergence of meaning, and the potentiality for action through subject/object relationships (Lacerda et al., 2019, p. 9). Architectural principles

Principles belonging to the architectural perspective identify guidelines that support the design of Internet of Things artifacts considering their objective characteristics. The principles share the premise that every artifact or space has an ontological nature since its existence is independent of individual subjects (Tuan 1977), and that they all possess an underlying architecture that is also an information architecture (Lacerda et al., 2019, p. 10).

Systemic Principles

Principles belonging to the systemic perspective identify guidelines that support the design of Internet of Things artifacts by considering them as part of the infosphere and of contextual information-based ecosystems. These principles address dynamics and behavior as a result of structure (von Bertalanffy 1998; Meadows 2008) and consider how information flows through artifacts, how actors and artifacts interact systemically, and with what consequences (Lacerda et al., 2019, pp. 13–14).

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25 Information Architecture Summary

With the ever-increasing amount of information in today’s world, the need to arrange information has never been more in demand. Resmini & Rosati define Information Architecture as: “Information architecture is the discipline that: Information architecture (IA) is a professional practice and field of studies focused on solving the basic problems of accessing, and using, the vast amounts of information available today” (2011, p. 33). Information architecture was first brought to attention by Richard Saul Wurman, and this attention was further increased by the introduction of the book ‘Information Architecture for the web and beyond” (Rosenfeld et al., 2015). This book was written by Louis Rosenfeld, Peter Morville, and Jorge Arango, and pushed Information Architecture into the mainstream. Information architecture moved from the ‘classic period’ as a result of the pervasiveness and ubiquitous computing.

In today’s world, information architecture is past the point of being connected just to library science or aimed at web site design improvements. These were concerned with labeling, organization systems, navigation, search, and sorting systems. However, a ubiquitous blend of physical and digital space is the additional factor that has to be considered by current IA research and practice. E.g. social actors consume information in a different social and environmental context, through the usage of different mediums, devices, and technologies.

Three frameworks have been discussed with regards to Information architecture: Big IA and Little IA, a unified language for the design of information systems, and an information architecture framework for the Internet of Things. Big IA and Little IA stem from the early days of Information architecture, where the discipline had not crystallized yet. The unified language has recently been introduced and offers designers a shared perspective for their design-process. The IA framework for the IoT offers principles and heuristics which designers can take as levers to design artifacts for the IoT while having an Information Architecture at the back of their minds. The red thread through the previously summarized topics is findability. Therefore it will be discussed in further detail in the next chapter.

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2.3 Social Informatics

The introduction of computers has had an immense effect on both society as a whole and the lives of individuals. Information Technology is a field that can be observed from its interplay with society. This interplay is defined in the discipline of Social Informatics. Social informatics (SI) is “the interdisciplinary study of the design, uses and consequences of information technologies that takes into account their interaction with institutional and cultural contexts” (Kling, 1999, p. 1). SI knows seven key aspects:

• The context of ICT use directly affects their meanings and roles • ICT are not value-neutral: their use creates winners and losers • ICT use leads to multiple, and often paradoxical effects • ICT use has ethical aspects

• ICT are configurable

• ICT follow trajectories; and

• Co-evolution of ICT system design/development/use (Sadiku et al., 2019, p. 6). SI is: “. . . a body of research that examines the social aspects of computerization” (Kling, 1999, p. 1). Computerization had a significant impact on the world and led to many socio-technical innovations. The most major of these innovations was the invention of the world-wide-web by Tim Berners Lee (Berners-Lee, 2000). This innovation eventually allowed people around the world to share information via, among other things, websites. Fichman et al. explain the focus of SI as “relationships among people, technology, and context are dynamic, complex, and critically important to understand.” They also provide information on the focal area of academic SI-research “SI is an important and dynamic discipline that focuses squarely on this theme and is an approach within which researchers study these complex relationships from a range of theoretical and methodological perspectives” (2015, p. 4).

History of SI

To understand the term ‘Social Informatics’ and explain what school of Social Informatics this research will use, its origin must be briefly introduced. The origin of Social Informatics can be traced back to seven different countries: “USA, the

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USSR/Russia, the UK, Norway, Slovenia, and also the lesser-known Japanese and German concepts” (Smutny, 2016, p. 1). Smutny offers an in-depth analysis of how informatics “has developed differently in namely Europe, the USA, and Russia due to the state of computer technology in different parts of the world in the 1960’s” (2016, p. 2). The research will use the USA approach of Social Informatics. This approach identifies four periods of development:

Figure 8 Social Informatics timeline

The current state of SI

The discipline of Social Informatics has been fragmented, and SI’s full scope is its Achilles heel (Smutny & Vehovar, 2019). The impact of this fragmentation can be seen in the number of articles that can be found when searching for ’Social-informatics’.

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Articles that clearly state the term of Social-Informatics are sparse, even though research that contributes to the field of Social Informatics is still being executed today. Meyer, Shankar, Willis, Sharma, & Sawyer explain with the following quote:

As these articles demonstrate, the workplace continues to be a topic of great interest to social informatics, but the character of the workplace, computing technology, and the worker have all changed. Furthermore, as computing technology has evolved it has become an essential and ubiquitous part of people’s lives well beyond work. The hyphen in “socio-technical” has become blurry; there is no longer either one or the other, but both. In short, the answer to the latter half of Kling’s question two decades hence is that social informatics matters now more than ever (2019, p. 311).

The current state of Social Informatics can be described as segregated and of significant importance. As ICT’s have become increasingly important to today’s society, so has the relevance of Social-informatics research.

Frameworks

SI is a transdisciplinary study, and as a result of this, it can use frameworks and methodologies from other fields. Frameworks SCOT and ANT were developed under the field of Science and Technology Studies (STS) but have an impact on the field of SI as they consider the social aspect of technologies (Meyer, 2014). The STIN framework was aimed and purposely developed for the field of SI by Kling, McKim & King (Kling et al., 2003).

Social Construction of Technology framework (SCOT)

SCOT is a framework based on the idea that human actions shape technology, and it is a one-way relationship where technologies do not influence society. The other main idea offered by SCOT is that technology cannot be understood without knowing how it is embedded in society. As presented by Pinch and Bijker (Pinch & Bijker, 1984), the main concepts of SCOT are:

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a. Interpretative flexibility – there is not only one interpretation of the artifact, but the meaning depends on the social context

b. Relevant social groups – there is not only one relevant social group, but many can apply, including for example end-users, designers, programmers, sales reps, and any possible sub-group

c. Design flexibility – one technology can be designed in many ways and to accommodate more target group

d. Problems and conflicts – multi-context technologies and especially the ones designed to accommodate more social groups can and will result in a conflict, which may be complex and hard to resolve

e. Closure – once a technology is developed and accepted (the target user’s problem is eliminated or changed), the Interpretative and Flexibility stage is closed. It will not be developed furthermore until the new user group is identified.

The contribution offered by SCOT is that there is no single best technology for the given problem, but there can be multiple perspectives, context, and users, thus multiple solutions. The main shortcoming is the assumption that technology has little to no influence on human actors and society. This assumption is also one of the most criticized attributes of SCOT (Meyer, 2014).

Actor-Network Theory framework (ANT)

ANT is used to analyze the network of social actors interacting with artifacts in their environment. Although ANT could be viewed as a subset of SCOT, it differs in a way that it puts equal focus on both human and non-human actors, for which it developed the term “actant”. Based on ANT, there are no actants nor artifacts that exist outside of relationships of a network, and thus everything needs to be considered (Meyer, 2014). Another concept ANT brings over SCOT is Translation. Any actant is available to any other actant for communication, and this brings the need for them to understand each other, and to do that, sometimes, the translation might be necessary. If there is successful communication between actants, they will then form an alliance, which is a stronger type of relationship. Stronger relationships are what actants aim for, as it means they are heard in the network (Alexander & Silvis, 2014a). An abundant source of controversy is a claim that human and non-human actants have no differences and equal weight (Meyer, 2014).

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Socio-Technical Interaction Network framework (STIN)

Developed by Rob Kling in the 1990s, it is a framework specifically designed to satisfy the needs and requirements of Social Informatics. (Kling et al., 2003). Meyer states that: The STIN strategy allows us to draw on the useful insights of SCOT and ANT but does not wholly embrace a relativist perspective and is skeptical of the possibility that non-human actants can exert agency in a social situation (Meyer, 2014, p. 63)

There are several assumptions when working with STIN:

1. The social and the technological are not meaningfully separable, at least not for the purpose of understanding how to design practice is usable and sustainable.

2. Theories of social behavior not only can but should influence technical design choices (and thus the STIN methodology has a normative dimension as well).

3. System participants are embedded in multiple, overlapping, and nontechnologically mediated social relationships, and therefore may have multiple, often conflicting, commitments. Further, the system plays roles of varying importance in the social or professional lives of system interactors. The sustainability of a system will depend on other systems and communication forums that the interactors already participate in; interactors may be bound only weakly to the forum under discussion. 4. Sustainability and routine operations are critical and must play a key role

(Kling et al., 2003, p. 56) The heuristics of STIN for understanding socio-technical systems include:

1. Identify a relevant population of system interactors 2. Identify the core integrator group

3. Identify incentives

4. Identify excluded actors and undesired interactions 5. Identify existing communication forums

6. Identify resource flows

7. Identify system architectural choice points

8. Map architectural choice points to socio-technical characteristics

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Points that make STIN unique to other STS frameworks are (Meyer, 2014) as follows. Point number 4: identify excluded actors and undesired interaction. STS models, such as ANT, involve everyone in the network but never consider the possibility that some actants might have been left outside of the network, either from the beginning or during the process of ICT development and introduction.

Moreover, point number 7: identify system architectural choice points. Meyer (2014) describes technologies as changing at points in time when a decision was made. Meyer also argues that by tracking these decision points, we can understand why decisions had to be made, what was decided, and why. At each point, we should also consider other heuristics introduced by the STIN model. That way, we can learn that the socio-technical configuration of technology was shaped (Meyer, 2014).

On the contrary, a weakness of the STIN model established by Meyer (2006) is that only the model was mostly adopted only by Kling’s students and colleagues. In order to be more acknowledged, it must achieve more widespread adoption. Meyer also points out the unclear labeling of STIN. Labels such as a model, a framework, heuristics, a type of entity, and a methodology are all used. This is in contrast with the previous work of Kling, where Kling managed to establish and clearly label the field of Social Informatics (Rosenbaum, 2013). The overarching term for STIN suggested by Meyer (2006) is a “strategy”. One weakness that has to be mentioned as well is the complexity of STIN and the heavy reliance on the skill of analyst that uses STIN, especially skills in eliciting and gaining access to the information from individuals and organizations (Meyer, 2006). To put in contrast, Kling et al. (2003) conclude their research of STIN as the model that helps to understand some key aspects of technological advances, but at the same time are aware that this new perspective gained through STIN will not solve problems with sustaining technological advancements nor will solve the integration of technology into a social world. They view the STIN model as an advancement in socio-technical analysis and the basis upon which more research should be established.

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32 Social Informatics Summary

Social Informatics (SI) is “the interdisciplinary study of the design, uses, and consequences of information technology that takes into account their interaction with institutional and cultural contexts” (Kling, 1999, p. 1).

Social Informatics is a field of significant importance, and its perspective is needed in today’s design and implementation of ICTs embedded in a social context (Meyer et al., 2019). History of SI talks about different schools of thought, and for this research, authors have decided to focus on US school founded and developed by Kling, as it is the most dominant, advanced, and developed school (Fichman & Sanfilippo, 2014).

In terms of frameworks, we went through three major frameworks, two of them (SCOT and ANT) were developed in non-SI fields, but follow some of the shared principles. Consequently, these frameworks have managed to have an impact on SI and even managed to change the field. This further proves the transdisciplinary nature of SI. A framework that was created specifically for the field of SI with its principles in mind is the STIN model by Kling (2003). To summarize STIN, we can use its heuristics:

1. Identify a relevant population of system interactors 2. Identify the core integrator group

3. Identify incentives

4. Identify excluded actors and undesired interactions 5. Identify existing communication forums

6. Identify resource flows

7. Identify system architectural choice points

8. Map architectural choice points to socio-technical characteristics

(Kling et al., 2003, p. 57) The above-mentioned transdisciplinary and frameworks should offer an excellent opportunity to establish a connection between Social Informatics with the field of Information Architecture presented in the upcoming chapter.

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2.4 Proposed Integrative view

The literature review was split into three main topics: Findability, IA, and SI. The same structure was applied for the summary with the synthesis of the aforementioned fields as the last element.

Findability

As fundamental as Information architecture is for the web, so is findability. If a social actor is unable to find a website in the first place, then how does it add value? As previously stated, the adage of: “You Can't Use What You Can't Find” (Morville, 2005, p. 160), perfectly describes this conundrum. The impact findability has on digital platforms is immense and, as such, should not be underestimated. Designers should see this analysis of literature as an enabler for data gathering, analysis, and discussion, which leads to suggestions that include findability as the most prominent aspect of a designer’s checklist. Based on the review, the authors of the research decided to take into account the BerryPicking model by Bates (Morville, 2005) for further analysis.

Information Architecture

The literature regarding Information Architecture provides us with an understanding of how information and the way its structured for users plays a significant role in the design of digital platforms. Frameworks that have been discussed provide designers with necessary footholds and bearing that they can use to solidify their creative processes. Information Architecture presents us with the knowledge we require to look beyond the essential functions of knowledge and perceive the ever-increasing landscape of information with a big-picture mindset which we can utilize to fuel our thinking and ideation processes. Moreover, the impact of Information Architecture rings true to this day, which can be seen by observing websites all around the world wide web. Social actors must be given well thought out information architectures so that the websites they use can be optimally exploited. For that reason, we decided to use the IoT framework designed by Resmini et al. (2019) and also utilize the benefits of Unified language (Jaffe,

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2019a). These frameworks were selected because they provide the authors with a deeper understanding of the field and how they can be used in combination with research results in order to provide insights.

Social Informatics

Social Informatics provides us with an overarching perspective about the connection between ICT, humans, and by extension, society as a whole. Kling et al. have laid the groundwork for generations of researchers to come, and the impact of their work are of great importance to the field of ICT. The proposed STIN-framework is of great value to the field of Social Informatics, supports the ideas that Social Informatics has brought into the world, and authors thus decided to use it for further analysis in the thesis.

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35 Integrated view model

Based on the theoretical framework, the authors of this thesis propose a compounded perspective regarding findability. The below-described model synergizes Findability, Information Architecture, and Social Informatics into one integrated view:

Figure 9 Proposed Integrative View

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3 Methods

In this chapter, the methods that have been used to gather the required data will be discussed.

3.1 Research Philosophy

Philosophy can be defined as: ”The study of the fundamental nature of knowledge, reality, and existence, especially when considered as an academic discipline” (Lexico.com, n.d., p. 1) or ”love of wisdom”. Concerning the research, the chosen philosophy impacts the way the authors think about their chosen topic and perspective. A person’s philosophy can be influenced by many factors such as, among others: cultural background, lived experiences, education-level, spoken language(s), and character.

A research philosophy provides the researcher with a tool to construct their reality. This affects how research results are interpreted and also knowledge contribution. Two essential elements of the research philosophy will be discussed: 1. Ontology (reality) and 2. Epistemology (knowledge).

Ontology

Scotland defines Ontology as follows (2012, p. 9) :

Ontology is the study of being (Crotty, 1998, p. 10). Ontological assumptions are concerned with what constitutes reality, in other words what is. Researchers need to take a position regarding their perceptions of how things really are and how things really work.

By choosing an ontology, the researcher provides themselves with a lens through which to perceive reality. This position influences the research design decisions and provides the researcher with a critical view of their research results, which constitutes their chosen reality.

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Furthermore, the ontological perspective that a researcher chooses can be one of ontological materialism or one of ontological idealism. Ontological materialists: “. . . believe that material things, such as particles, chemical processes, and energy, are more real, for example, than the human mind. They argue that reality exists regardless of human observers” (Lofgren, 2013b, p. 1). On the other hand, ontological idealists believe the opposite: “. . . believe that immaterial phenomenon, such as the human mind and consciousness, are more real, for example, than atoms and physical objects. They argue that reality is constructed in the minds of the observers” (Lofgren, 2013b, p. 1).

Epistemology

Scotland defines Epistemology as follows (2012, p. 9) :

Epistemology is concerned with the nature and forms of knowledge (Cohen et al., 2007, p. 7). Epistemological assumptions are concerned with how knowledge can be created, acquired and communicated, in other words what it means to know. Guba and Lincon (1994, p. 108) explain that epistemology asks the question, what is the nature of the relationship between the would-be knower and what can be known?

Moreover, epistemology can be constructed through one of two ways: empiricism and rationalism. Each of these epistemologies uses different perspectives to justify claims and beliefs. Empiricism poses that for knowledge to be true knowledge must be based on input from our senses, experiences, and observations (Lofgren, 2013a). Rationalism is concerned with reason instead of experiences and observations and that the human mind (rationale) is where new knowledge stems from (Lofgren, 2013a).

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Figure 10 Alternative stances on knowledge and reality

There exist multiple types of ontologies and epistemologies. Walsham provides an overview of different ontologies and epistemologies (1995, p. 104):

Ontologies and epistemologies are all part of a paradigm. A paradigm is a worldview/perspective and an overarching term for a collection of methods, ontologies, epistemologies, and methods (Scotland, 2012). Each paradigm has its advantages, disadvantages, underlying assumptions, and is suited for a different style or approach to research. It is the researcher's task to identify the paradigm that best suits their research.

Selected research philosophy

For this research, the paradigm of interpretivism has been selected. The interpretivist paradigm includes a relativistic ontology, which “is the view that reality is subjective and differs from person to person” (Scotland, 2012, p. 11). The interpretivist epistemology is that of subjectivism, which as above described by Walsham is: “each person constructs his or her reality” (1995, p. 104). Crotty elaborates on this definition by the following example: “We need to remind ourselves here that it is human beings who have constructed it as a tree, given it the name, and attributed to it the associations we make with trees” (1998, p. 44). Furthermore, the interpretive methodology is focused on: “understanding phenomenon from an individual’s perspective, investigating interaction among individuals as well as the historical and cultural contexts which people inhabit” (Scotland, 2012, p. 12).

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This thesis focusses on reviewing existing literature on findability and identifying potetial perspectives which combined with designers' work experiences provide insights and contribute to an integrative view on information findability. This aim ties well with the above described interpretivist methodology as it allows the researchers to generate qualitative data through interviews, which will be analyzed.

However, by choosing the interpretivist methodology, there exist some drawbacks and disadvantages. Firstly, as the interpretive paradigm makes use of a subjective form of reality, the research results can be interpreted differently by the researchers than by the interviewees. This has implications on the validity of the research. Secondly, as the nature of data is qualitative, the results are highly contextual, and its interpretation subjective. Due to these factors, the transferability of the research can come into question (Scotland, 2012).

The drawbacks will be contained by matching the interpretation of the researchers to the interviewees, this will be done by sending the interviewees a summary of their respective interview to check if there are any discrepancies in the interpretation.

3.2 Research approach

Qualitative deductive analysis has been used to “determining the extent to which qualitative data in particular study support existing general conceptualizations, explanations, results, and/or theories” (Patton, 2014, p. 791).

3.3 Research strategy

Interviews with designers have been undertaken to learn more about their approach toward the application of findability within the design of digital platforms.

Before the interviews could be undertaken, a list of questions was structured, which can be found in Appendix 2. These questions were formulated and selected based on elements from the theoretical framework that the researchers wanted to discuss with digital-platform designers.

On-site Information Findability: Towards an integrative view