Den 27:e november går CIBAS omvärldsbevakningskonferens, Intelligence 3.0, av stapeln.  Där kommer ny forskning inom ämnet omvärldsbevakning presenteras tillsammans med case studies signerade några av Sveriges ledande omvärldbevakningsföretag.

Vi är delfinansiärer aktiv part i forskningsprojektet CIBAS som studerar hur omvärldsbevakning och affärsanalys behöver utvecklas för att möta och bäst utnyttja den snabba utvecklingen inom social och datacentrerad webbteknik.

Temat för konferensen är det nya medielandskap som växer fram och de utmaningar vi ställs inför då vi ska skapa klarhet och insikter utifrån ständigt växande dataströmmar som rör sig i nya banor. Hur kan vi arbeta och samarbeta i denna nya miljö?

Läs mer på http://ci-nätverket.se/intelligence-3-0/

 

 

Visualization is nothing new. Humans have during long time had a need to represent and externalize thoughts and ideas. Through various means, for example, pencil and paper, humans have created the opportunity to develop human thinking. Visualizations are external representations.

A tradition of visualization has its background in statistics. It involves various forms of charts that allow users to gain insights of the data that forms the basis for the visualization. Developments in technology, particularly Internet development, have meant that the area has taken something of a leap. New ways to visualize a data has its background in development of, for example, social media. One such example is the word clouds witch is a graphical representation of how often different words are used in a specific context.

Visualization is an area that for a relatively long time had the interest of researchers in the research realm of HCI but also in other research spheres – especially cognitive science. Visualization has a wide range even within HCI research. It can involve everything from visualization of statistic data, visualization to create game worlds (virtual worlds). It can be about how data from electro microscope or an x-ray machine can be visualized for the user to gain insight and create knowledge from data. The definition often used within the HCI domain is: Information Visualization – The use of computer-supported, interactive, visual representation of abstract data to amplify cognition (Card, Mackinlay, & Shneiderman, 1999).   

Developments in the field have been very rapid and alongside research articles it has been important to take note of other literature books and industry reports. In the books I have read visualization is presented as an industry, branch and area of technology. The content in these books differ from the research articles I have read. This possible can be explained by that research takes time. The area of ​​visualization has recent years attracted interest in many areas. The journalistic task is to explain something, and this technology will come in handy. Nathan Yau explains how visualization is all about “telling stories with data” (Yau, 2011, sid 1).

Two of the articles that I have read are published in other fields than HCl but have also contributed to knowledge and above all put the area in a context. Lurie & Mason describes the impact of visualization on decisionmaking (Lurie & Mason, 2007). The article is published in the research field of marketing and describes the importance of visualization to gain insights and there by be able to make wise decisions. Lurie & Mason works within the the researchfield decision-making and look up on visualization from this perspective. Lurie & Mason use the term “visual perspective” to refer to how a given visual representation changes the relationship between visual information and the decision maker (Lurie & Mason, 2007). One aspect of visual perspective is “interactivity,” or the user’s ability to change perspective, for example, by rotating or simulating movement around an a set of data. Lurie & Mason concludes that the design of visual representation as encoded information from several different aspects such as shape, color, texture, geometri. When the user, in this case decision makers, use the artifact there is a decoding. The representation works only if the coding is correct and effective and in relation to the users ability to decode.

Card, Mackinlay, & Shneiderman uses the concept of knowledge crystallixation and it referres to when one or more people gather and organize information in order to understand it or gain knowledge from it (Card et al., 1999, p 13).  The result can be a report or summary. In this context it is possible to express how visualization is used to create patterns from something abstract and in this way create the ability to understanding and gain knowledge.

When reading the selected articles and literature some areas emerges. Theese are: Representation, Cognition, Data, Information, Amplified Cognition, Patters of use, Technology, Designprocess, and it is theese areas I describe in short here.

 

Representation

Rieber describes how visualization is a tool to solve a problem (Rieber, 1995). Visualization is a problem-solving-tool. Rieber insert visualization in the area of problem-solving research and believes that the use of visualization can be considered as a problem-solving strategy. He further describes how an external representation of a problem may be needed to find a solution.

By describing a set of simple and historical examples Rieber shows how visualization served as tools for solving problems for a long time in human history. It is not only more dramatic events in history that have a relationship with the visualizations, but often problems and decisions in common peoples everyday lives. The approach to how visualization and external representation constitute a problem-solving strategy is, according to me, well in line with user-centered design. There must be a clear thought about the problem that the visualization solve. There must be an investigation of who the user is and the benefits arising from the use of the artifact.

Rieber provides several interesting examples of the importance of being able to ”inner visualisation” The example he describes comes from the scientific comunety and how some very famous scientists such as Albert Einsten, August Kelué, Roger Shepard, all testify to how they can close their eyes and see things (for example atoms organize in a special cluster). But Rieber does not use the concept of internal representation in his text. This is a concept used in later research on visualization but I perceive that it exactly what Rieber describes with his examples. Rieber nor use the concept of external represention.This is also something that are established later in the litterature.

Liu, Nersessian, & Stasko resembles external representation with a symbol (Liu, Nersessian, & Stasko, 2008). The symbol carries meaning about something and when humans understand the symbols (as intended) a there is an effect. A picture or symbol is an external representation. A graph is a picture or symbol that represents for example a large amount of data or information. Within research area cognition the word representation mainly stands for something else namely the mental images we create in your head to understand what we are seeing or experiencing. Cognitive science solely focuses on finding internal representations and abstract rules inside the brain (Liu et al., 2008).

Liu, Nersessian, & Stasko describes how there in the HCI research community is a perception that knowledge of cognition is the responsibility of the cognitive scientists and it must be abandoned by HCI research. Even so, Liu, Nersessian, & Stasko examining a theory called ”distributed cognition” and it has its home in cognition research. It is central in this theory how humans have learned to use different tools to teach us things. The pen and paper is an example of such tools. By externalizing our thoughts, we can also take the idea further and develop new thoughts and ideas. We can also better communicate our thoughts with other people and there by collectively develop knowledge. The concept “amplify” (cognition) is launched and relate to how learning increases in power when these cognitive tools are used.

Card, Mackinlay, & Shneiderman uses the term external representation to describe how humans through use tools to relieve working memory and by this create the opportunity to push the “thoughts” further (Card et al., 1999). The written language and above all the written numbers are used as an example. It would not have been possible to develop the mathematical thinking without the ability to use symbols externalizing complex thoughts (Card et al., 1999 p. 3). The line of argument is how visualization is used for thinking and this is captured with the books subtitle ”using vision to think.”

The importance that maps has had for shipping and humans opportunity to explore the world are one given example. The development of the charts and its importance to understand large quantities of something are another example of cognitive tools. The relationship between thinking, externalization and communication is established.  The researchers describes briefly how this is the case and how there is a complex interaction but Card, Mackinlay, & Shneiderman does not go into detail on the subject of cognition. Instead the goal of their analysis is to determine how complex data rendering allows for data-based visualization and how this represents a tool for thinking.

Odification, Price, Brooks, Vessey, & Street reason about how the internal representation arrangements are created and relate to external representation (Odification, Price, Brooks, Vessey, & Street, 2006).  My opinion is that although this realation is very complex it is central to HCI research. My interpretation is that there is a challenge in creating a visualization that is relevant to the user. The goal for the designer is to create an external representation that can be perceived by the user and the user must make sense of it the user must gain some kind of insights from the visualization. The user must find it useful.

The basic idea is that digital technology in design of visualization creates the ability to provide different views on the same data. It is possible to present data in different ways (ways that fits the individual user and their internal representations better). In this context in the word interactivity is not mainly focusing of navigation. It’s mainly about the interaction possibilities for the user to create external representation that is in line with its internal representation. In this way the visualization becomes effective.

Cognition

There area of cognition is not described in particularly high extent in the articles I have read. There seems to be a approach with in the HCI community that “cognition as a subject shall be handle by the cognition research and I find this hard to accept. The is theories used in HCI that has its background from cognition research area and cognitive science. Cognitive fit theory is one example and it concerns the relationship and interaction between problem solving, internal representations and external representations. Liu, Nersessian, & Stasko describes information visualization as a field that not is matured and that there are a lack of theories to lean on. They see their own research as a first tentative steps regarding development of theories for visualization (Liu et al., 2008).

Cognitive fit theory provides an explanation for performance differences among users across different presentation formats such as tables, graphs, and schematic faces (Odification et al., 2006). In this manner both the internal and external representations, and the interactions among them, contribute to the mental representation for task solution that is developed to solve the problem (Odification et al., 2006). The work Odification, Price, Brooks, Vessey, & Street has done is very extensive and the article is multidimensional. Other researchers in the field of visualization are referring to this article. It is the notion of internal and external representation that most central.

Data

All data must in some way be structured in tables to be visualized (Card et al., 1999). Nathan You describe in the book Visualize This: The Flowing Data Guide to Design, Visualization and Statistics the importance of getting hold of data, structure data and format data. This is the foundation of digital visualization and Nathan Yau says that it is when the designer manages these parts as design opportunities are created (Yau, 2011).

My opinion is Nathan Yau’s book is about the possibilities new technology created the past 10 years to collect, organize, and visualize information. Not least, the book is about the technologies just to find, collect and organize data. Technology has over the years become more user-friendly and accessible. More individuals and organizations can work to visualize data.

But it is not only new technologies that are contributing to the development of the field. There are changes in society that reflects on the domain. As an example can an ongoing shift in approach in the governmental area where there is an increasingly large effort to make data available to the public in formats that can easily be used. The idea is that the data has value and that social benefits may arise if the data are easy to reach.  This trend is called OpenGov (or Open Gov moment). Another area that can be singled out as contributing the development is social media such as Twitter and Facebook where large amounts of data being created and it is located in the corporate interest that their data can be used in ways that support their business models. There is a relation between the growing amount of data and the development in the area of visualizations.

Interaction

Yi, Kang, Stasko, & Jacko thinks that within HCI research there has been a focus on the representation in terms of visualization and area interactation is neglected (Yi, Kang, Stasko, & Jacko, 2007). They argue that the interaction aspect is important because if digital artifacts, visulisations being built and they are not interactive the designer doesn’t  utilized the technologie. They claim there is a big difference between an analog visualization for example on paper and a static visualization (digital). Although it is understandable that the digital visuliseringen can be created ”on demand” the interaction posibilites are not used.  The researchers literature review on the subject gives them a oportunety to create list of categories – different interaction possibilities:

• Select: mark something as interesting
• Explore: show me something else
• Reconfigure: show me a different arrangement
• Encode: show me a different representation
• Abstract/Elaborate: show me more or less detail
• Filter: show me something conditionally
• Connect: show me related items (Yi et al., 2007).

The researchers go through each category carefully and also give examples. This list is the result of their research, and they argue that the list of categories can be developed. Yi, Kang, Stasko, & Jacko do not use the concept of pattern but I believe this would be termed as different patterns and the list could be very useful in a practical design work.

Amplify Cognition

Card, Mackinlay, & Shneiderman uses the term ”ampify cognition” and raising questions how and when visualization reinforce cognition (Card et al., 1999). This can be investigated by giving a group of people the same task to solve, the one given tools in the form of a visualisation while the other group did not have access to this. Then the research/designer can measure the time it takes to solve the task. Card, Mackinlay, & Shneiderman describes a few central areas where visulisations can offer efficency: Visualization offers a compact information in a small space. Visualizations can offer to zoom in on details. Trends and patterns can be quickly identified. Visalization can do so that searches are avoided and so on. What is recurrent and central is the fast accesses to information that a visualization can offer the user. Yau writes in detail about variety and recurring areas for use of for visualization. A recurring need is to describe the trends that occur over time. It is recurrent through visualization show proportions of something. Relationships between different things is grateful to visualize and spatial context (Yau, 2013).

Forms and structure of visualisations

Card, Mackinlay, & Shneiderman discuss of the notion of ”cost structure”. It relates to how the visualization is created to be as efficient as possible for the user. It’s about organizing information in a way so that the benefit for the user is as large as possible according to the users goals. The user should use as little time as possible on achieving the goals she has. Card, Mackinlay, & Shneiderman then moves on to visual structures which deals with how the visualization should look like in order to be understood and effectively used. Here comes the concept perception in.

Process

Tory & Möller concludes that the process of designing the visualization must take its starting point from the user’s needs and support the user in his task (Tory & Möller, 2004). It advocates a user-centered design process with a process consisting of analysis, design, prototype and testing then iteration of this process (otherwise, the results of this study primarily to determine that there is not much systematic research on visualization that is user-centered). Data Points: Visualization That Means Something is another book from Nathan You. Also in this book there is a focus on the importance of finding out what is to be achieved with the visualization.  There is also a focus on the graphics side of data analysis using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data (Yau, 2013).

From this book I wish to highlight how Yau expresses how visualization is a medium. The argument given is that visualization is used in so many different purposes. From statistical analysis to art, making it difficult to reason about visualization as a contiguous area. I find it interesting that it is only in this book, which was published in 2013, as visualization are described as “a medium: a way to explore, present and express meaning in data” (Yau, 2013).

It is only two years between Yau’s two books. Thematic the books are presented in a similar manner. An observation is that there are more examples in the latter book and the examples are more diverse. An interpretation I make is that the area has exploded in recent years. Yau will return in this book again and again to the concept of meaning: “Visualizations that’s means something”. The author describes a design process and a model is presented. Do note that this is only briefly done. In these books, and creates thoughts about my own upcoming project where I just will sketch out a process.

Interactive Data Visualization: New Directions for Accounting Information Systems Research was published in 2010 and has a focus on visualization and decision making in organizations (Dilla, Janvrin, & Raschke, 2010). The researchers develop a taxonomy for examining the current state of interactive data visualization research related to accounting decision making. It gives an overview on the research area and articles in the field.  Dilla, Janvrin, & Raschke´s research is done with in the scientific area of ​​information systems, but the study is published in a journal in the field of accounting. In accounting and finance, a variety of IT systems are used and from these it is possible to retrieve data. This data forms the basis for economic decisions and for the user to create insights from the data there is a need for various forms of cognitive tools. In this way, the work of creating these cognitive tools its starting point from existing methods in the field of enterprise resource planning (ERP) and Balanced Scorecard (BSC).

How is visualization for decision making used within the field of accounting? To explain this, the researcher lean primarily on two theories or perspectives. The first is ”cognitive fit” that was developed in the early 1990s by Iris Vessey (developed later, in 2006, by Vessey). The theory proposes that the correspondence between task and information presentation format leads to superior task performance for individual users.

The second theory or perspective Dilla, Janvrin, & Raschke retrieves from marketing research and it is called Judgment and decision-making (JDM) and is created by Lurie and Mason in 2007 (Dilla et al., 2010). By applying these two perspectives describe Dilla, Janvrin, & Raschke how they are developing a framework that examines linkages between task and decision maker characteristics and interactive data visualization. The framework also examines the link between interactive data visualization and decision processes and outcomes. Dilla, Janvrin, & Raschke identify conditions under which various aspects of interactivity have been shown to affect decision processes and outcomes.

As I understand it he primary conclusion is that the user’s personal characteristics play a major role regarding which kongitiva tools should be used. If tools are used where the user is able to select data, representation arrangements and type of visualization, high demands on skills and knowledge.

Most of the research discussed in this review is consistent with a cognitive fit perspective: It suggests that the effectiveness of information visualization techniques, such as interactive infor- mation and navigation tools and interfaces that allow the user to select their preferred information representation, depends on task characteristics, such as the dimensionality and complexity of data and decision maker characteristics, such as domain-specific expertise and cognitive ability (Dilla et al., 2010). As a passage describes how the user perceives well presented information and interactive information more credible. I find this very interesting because this is a wrong idea – false data or wrong data doesn’t become a truthfull or right just becaouse it is designed in a professional and attractive way.

 

 

 

 

 

References

Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999). Readings in information visualization : using vision to think. San Francisco: Kaufmann.

Dilla, W., Janvrin, D. J., & Raschke, R. (2010). Interactive Data Visualization : New Directions, 24(2), 1–37. doi:10.2308/jis.2010.24.2.1

Liu, Z., Nersessian, N. J., & Stasko, J. T. (2008). Distributed Cognition as a Theoretical Framework for Information Visualization, 14(6), 1173–1180.

Lurie, N. H., & Mason, C. H. (2007). Visual Representation : Implications for Decision Making, 71(January), 160–177.

Odification, M., Price, M. F., Brooks, W., Vessey, I., & Street, M. (2006). T HE R OLE OF C OGNITIVE F IT IN THE R ELATIONSHIP B ETWEEN S OFTWARE C OMPREHENSION AND, 30(1), 29–55.

Rieber, L. (1995). A historical review of visualization in human cognition. Educational Technology Research and Development, 43(1), 45–56. doi:10.1007/BF02300481

Tory, M., & Möller, T. (2004). Human factors in visualization research. IEEE Transactions on Visualization and Computer Graphics, 10(1), 72–84. doi:10.1109/TVCG.2004.1260759

Yau, N. (2011). Visualize this : the FlowingData guide to design, visualization, and statistics. Indianapolis, Ind.: Wiley Pub.

Yau, N. (2013). Data points : visualization that means something. Indianapolis: John Wiley {&} Sons.

Yi, J. S., Kang, Y. A., Stasko, J., & Jacko, J. (2007). Toward a deeper understanding of the role of interaction in information visualization. IEEE Transactions on Visualization and Computer Graphics, 13(6), 1224–31. doi:10.1109/TVCG.2007.70515

 

 

Dashboards are used by companies and organization to get an overview and to gain insights and in this way to be able to control and develop the organization. I want to create a framework for a design methodology that aims to build a dashboard for work environment risk analysis. Using the artifact the users effectively gain insights into the risk analysis process on a large number of local and geographically dispersed units. The problem addressed is how the designer take the right design decisions on WHAT to visualize and HOW it should be presented. There is a large focus on the relationship between data, data representation, visualization and cognition. I would also say that it is a user-centered design process.

Introduction

Image 1. Senior Manager within a group that has the responsibility to control the process of working on a larger number of units that are geographically dispersed. To help them, she has a dashboard where data is visualized and presented

Dashboards are used for corporate and business analysis in order to get an overview monitor and guide the development of an organization or a company. The area Compliance Management concerns information gathering, analysis and control for the organization to adhere to the laws and rules that apply.  Dashboards are a part of a Compliance Software. A particular focus is on users who are senior leaders, national or international levels. In this project a senior leader who needs to control how the work environment is managed at hundreds of local branches or places of business. A systematic approach to health and safety at work is about to pay attention and take into account all the circumstances of the work environment that may affect employees health and safety. Image 1 describes how a senior manager has the responsibility to guide the process of work environment on a larger number of units that are geographically dispersed. To help her make the right decisions, she has a dashboard where data is visualized and presented. Figure 1 may represent a target image for the artefact to be created.

Problem

How could a framework for designing a dashboard for the management of health and safety risk assessments on a larger number of units be developed.

Background

Dashboarddesign

When a dashboard shall be developed the designer must understand what is considered to be a signs of success (or the opposite) in the field. The designer must analyses the Business Performance Management (BPM) and he/she must produce knowledge on Key Performance Indicators (KPI) (Frolick & Ariyachandra, 2006), (Weber & Thomas, 2005), (Chowdhary, Palpanas, Pinel, Chen, & Wu, 2006). This is a demand-driven (user-centric) perspective. It is also possible to have a supply-driven (data centred) perspective. (Borgman, Heier, & Bahli, 2012). Here, the designers start of from the data and data sources that are available. There are also reasons to learn about national and international standards and perceptions what constitutes success in a particular field or industry (Ryan, Lewis, Fretwell, Doster, & Daily, 2013). By this the KPIs can be examined in a wider context. It becomes possible to compare one organization to another.

It is possible to divide the design process in different parts. These are: BPM-analysis, KPI-analysis, analysis of data and data sources, data aggregation, visualization, presentation. There is also a major need for knowledge on existing technologies, data formats and data structures.

In the article Harnessing the web information ecosystem with wiki‐based visualization dashboards McKeon introduces the idea of a wiki‐like system for building dashboards (McKeon, 2009).  A very simple instructive image is presented in the article that essentially shows some different parts of a dashboard. The last part, social media is of particular interest to McKein. Social dimensions are not as interesting for me at this point in current project but the other parts can be regarded general in the preparation of creating a dashboard. Here below shows the five main parts of McKeins image.

Data sources > Data aggregator > Visualization > Presentation > Social media

Data sources can be internal data (produced within the organization) or external data (such as meteorological data, or data from social media). Data aggregation is the part where different data and data sources are mixed. By combining multiple data sets new patterns emerge and new knowledge arises. Visualization phase is when the developer chooses which method or model for visualization that is most suitable to communicate with the user. The presentation is when all the visualizations are compiled into a single page. This part also concerns the interface where the user can switch between different visualizations or variables. This article clarifies the importance of how the developer must understand what data formats, data structures and standards that exist. How data is structured and in what format it is when it is obtained from the different data sources. The developer needs a good knowledge of the structure and format to be able to ”get the data into” the aggregator. There should also be a given structure and format of the data ”from the” aggregator for an easy way to generate visualization – either by existing programs or through programming. It must also be easy to compile all the visualizations in a presentation; a dashboard.

With consideration of the argumentation above I have chosen to sketch on a separate overview of the design process. This is obviously a matter that will need to be developed during the process and this development is also part of the process. In this paper, the four points is seen as a first sketch based on my prior knowledge of the subject.

1. Demanddriven, usercentric analys
2. Supplydriven, datacentric analys
3. Development of visualizations
4. Presentation

I will also need knowledge about technology. It is technology that makes this possible and the whole process is framed by technology. I do not express technology as a step or phase of the process but as a prerequisite for the project. Questions about data, data format, data structure is central to the project, but also the choice of technology solution. There are a number of ways to build a dashboard and the project includes an understanding of the various options. Briefly, there is a set of tools on the market for visualization. It is also possible to create visualization by programming.

It will be necessary that the model becomes more detailed. Each point (1-4) itself contains of parts that will be described. In this way, the model will be developed during the project and the model is part of the framework to be developed. The model is the outcome of the design-orientated research.

Working environment (health and safety at work)

A systematic approach to health and safety at work is about to pay attention and take into account all the circumstances of the work environment that may affect employees health and safety. This is in Sweden regulated in the Work Environment Ordinance (1977:1166 ) and in the Work Environment Act (1977:1160) . In Sweden the governmental authority Swedish Work Environment Authority monitors that the law is followed. They publish detailed specifications for how the companies will work to fulfil the law.  The key document from the Swedish Work Environment Authority is AFS 2001:1 that constitutes what must be done to comply with the legislation. And in this is stated that every company or organization are conducted to once a year or at major organizational changes conduct a risk analysis.

At the international level there is a standard for work environment called OHSAS 18001. It is the basis for how safety management systems should be designed. The management system is a structure of how the organization works with their health and safety. It includes monitoring, evaluation and reporting of environmental performance. If OHSAS 18001 is done the right way to fulfil the requirements for systematic safety work the organisation also for fills the Swedish law and AFS 2001:1 automatically. It is possible to argue that the risk analysis is central not only on a national but also on an international level.

Risk Analysis

A risk analysis takes its starting point from available data, research and statistics on occupational risks in a particular sector and, based on this knowledge, the analyst produces a number of checkpoints.  Risks are highlighted and weighted. An action plan is created and then the each risk must be addressed. Risk assessment, summaries of injuries and incidents and action plans must be (by law) to be documented.

IT support for risk analysis

The company Glykol AB develops an IT system for risk analysis called CheckSys. It is from this system that the data will be retrieved for visualization and for this reason the core functions of the system is explained. The IT system CheckSys supports a risk analysis process for specific, targeted control issues. The concept supports the user throughout the process with current accurate information, check points, proposed measures and reference to regulations. The process is documented automatically. The concept was developed for safety control and risk management for good work environment and the concept can be applied to any industry or profession.

User Groups

Thinking about creating a dashboard for risk analysis in the work environment is based on the idea that work is important, not only from a human perspective but also from a business perspective. There are high costs for a company with sick people. Accidents, illness or death is very negative for the brand Companies need to compete for the best talent in the market and it is not only the salary that determines whether a talent chooses to take up employment. The work environment is also something that affects the ability to attract employees. It is a generally accepted view that it is profitable with systematic work environment management.  (Calculating the international return on prevention for companies : Costs and benefits of investments in occupational safety and health, n.d.)

It is common with various forms of commercial chains in Sweden. It May be a commercial chain with a large number of stores, car repair shop, hamburger restaurants and so on. It could be a brand with so-called franchisees. It will be a central issue at the national level to manage, operate, so that all local branches or franchise taker in the group stay with the laws or regulations on work environment. The profession of this this is called Compliance Management  (Sandner, Kehlenbeck, & Breitner, 2010). The IT systems or tools used for compliance management called for the compliance software.

The primary user of the artefact is a senior manager with responsibility for work environment within a larger group. A title that commonly used HR-manager. HR stands for Human Resource and this person is responsible to guide and improve the work environment. The challenge is to control the work environment on a large number of geographically dispersed units. Mekonomen which is a group within the automotive industry, to take one example, had by the end of 2012, more than 400 stores and over 2,300 affiliated service centers, operating under the Mekonomen different brand (Årsredovisning Mekonomen, Meca 2012, 2012). How shall the senior manager be able to get an overview or manage the risk analys process on such a number of locations each year.

The dashboard that is developed in this project is a key part of the compliance software whose purpose is to get an overview and to control the process of risk analysis for good work on a large amount of geographically dispersed units. The HR-manager must be able to demonstrate that there is a systematic work environment management, how it occurs and what effect it will have. These reports or information must be presented to the board of directors and shall, if the organization wishes to develop resonate in document management and external communication.

There is another user-level and it is the HR-manager at a local level. Note that the Swedish law and Environment Act is very clearly designed with regarding liability. It is difficult to delegate a work environmental responsibility and it is always the CEO who has the legal responsibility. If there is an accident, the president can be prosecuted. For that reason, the local HR manager needs to assure the local CEO that the work environment is in accordance with Swedish law.

Method

Below the four parts of a design process is sketched and I have outlined the problems, methods and expected results. The table also has two focuses; Design orientated research and Research orientated design. Fällman differentiated design-oriented design from research – oriented design. Design-oriented – research is the design methodology and research the area – the product knowledge. In Research-oriented design research is methodology and design area. Here is the product an artefact (Fallman, n.d.). In the left column, then the result is some kind of design knowledge while in the right column is the expected result which ultimately becomes a digital artefact.

Design orientated research	Research orientated design
Demanddriven – usercentric Problem How to find out which the design needs are. Method Reading, questionnaire, interview. Outcome Template – a tool for information gathering.	Demanddriven – usercentricProblem What insights the user should be able to get from the dashboard? Method BPM and KPI investigation. Outcome List of KPIs
Supplydriven datacentricProblem How to find out which design is possible? Method Systematic analysis of IT systems, data, and data representation Outcome Template as a tool to create an understanding of data access, data structure.	Supplydriven datacentricProblem What data are available and how is it structured? Method Analyzing IT system CheckSys, database model and data. Outcome List and description of available data
VisualizationProblem Visualizations which enhances cognition Method Prototype – user test – Iteration Outcome Knowledge of the design process, data, representation, visualization, cognition.	VisualizationProblem How will the data de visualized? Method Building visualization with some form of technology. Outcome Sketch, prototype, visualization
PresentationProblem Which design decisions need to be made for the presentation? Method Prototype – user test – Iteration Outcome Knowledge of the design process, interaction aspects of the presentation.	PresentationProblem How are they different visualizations compiled / presented? Method Compiling visualization with any kind of technology. Outcome Sketch, prototype, product – the compilation.

 

Delimitation

I want to discuss the delimitation in depth with my supervisor. I realize the importance of delimitation but I find it difficult to sort parts out from this project without losing in credibility. It seems to me that all parts I sketches are equally important.

One way to delimit this research project would be to focus on the visualization of data and presentation of visualizations. The first two parts sketched above consisting of a usercentric analysis and a datacentric analysis would in this case work as a contextual background. The two analyses are presented as input in the design project.

The formal work of the master’s program then takes its starting point from the existence of a good knowledge on BPM and KPIs. There will also be a perception that it is possible to produce data from the IT system CheckSys. Here is an example of questions that I assume are important to the national coordinator of work environment within a group.

How many local entities have started a risk analysis? How many have finished a risk analysis? How many have started their second risk analysis? How many have completed their second risk analysis.

In the example above the project take its starting point in how this is visualized in the wisest way? In witch manner is the visualization enhancing cognition? In this delimitation the artefact will be one (1) visualization and / or presentation of data.

One idea is that this (first) visualization is done to a certain level; a sketch or prototype. After this, I would go ahead and produce next sketch of visualizations. When I reached the number of visualizations I will need to analyse their relationship. How are they presented on the dashboard? This part of the work will involve interaction design. Should the user be able to interact with the dashboard? What happens for example if the user is given the option to choose to see all the visualizations based on a specific variable; for example the variable year?

Visualization and HCI
30,000 years ago, humans began scraping and painting images and characters that represented things and events of their lives. Images depicting the animals, hunting, people. It is conceivable that these images were part of a communication between people (while these images certainly also have other functions, such as religious or ritual). Humans now started externalizing information which is a big step in human history – we now had the ability to store information, store knowledge. Memory, knowledge and insights could now travel over longer distances but also conveyed from one generation to another (Lindqvist & Söderlind, 2013). People have been arranging data into tables (columns and rows) at least since the 2nd century C.E., but the idea of representing quantitative information graphically didn’t arise until the 17th century. For this innovation we have the French philosopher and mathematician Rene Descartes to thank (Few 2013). When talking about data visualizations and human perception there is an underlying thought that the data represents something. By collecting data and then somehow present the data, we humans can create an understanding of what the data represents. It seems that humans more easy  can create knowledge from images than from large amounts of data.

Well-designed interactive visualizations help users gain insights from their data, identify patterns, and make decisions. During visual analysis, a single analyst or a group, access information from multiple sources to combine insights (Elias & Bezerianos, 2012). Information visualization can be described as the interactive computer based visual representation of abstract data to amplify cognition (Sandner et al., 2010). Yau believes that visualization is not to be seen as a tool, but rather as a medium (Yau, 2013). The aim is to create meaning from the data. It has been a long time in human history been a need to explain complex processes and context in a simple way.

It is very clear that when someone wants to research the area occurs that a need for both research and practical design hand in hand. It seems very positive to have a practical problem to address. By providing a practical problem, there are given reasons to raise questions about who the user is, what insights that visualization is to provide and what data is available. Here are som examples from the HCI research community.

Production of complex IT system requires review, monitoring and management. The various participants in the projects must also understand what the other participants or groups of participants are doing and the dashboard is in this perspective also a form of communication between various stakeholders (Treude & Storey, n.d.). Another article describes how dashboards are used in health care (Ryan et al., 2013). One research project is about analyzing and visualizing how networks at banks are doing (Barcelos, Aburjaile, Leite, Oliveira, & de Melo-MinarcTi, 2012). One article are focusing on building and deploying learning analytics dashboards in multiple learning Environments (Vozniuk, Govaerts, & Gillet, 2013).

It is very common in the articles I read with findings about the importance of understanding human perception and cognition, but it is seldom offered any detailed explanation precisely how human perception works. An example off such article is Data Visualization for Human Perception in which the author notes that we (the designer) must follow design principles “That are derived from an understanding of human perception”.  But then again there are no explanations of human perception and visualization. In the article A Model for the Visualization Exploration Process the visualization process and results are presented (Jankun-Kelly, n.d.). But neither this research focuses on cognition, but has a strong focus on analysing the data available. Yau explains how the process of developing a visualization a winding process that requires expertise in statistics and in design.

Some researchers argue that when designing visualizations it is effective with participatory approaches to user-centered design, in which users and other stakeholders are involved in co-creating. That the artifact then becomes more useful and usable (Goodwin et al., 2013). The article Creative User-Centered Visualization Design for Energy Analysts and Modelers is very interesting from that perspective (Goodwin et al., 2013). This article also shows how extensive the design process of this kind can be.

A key issue in the design of visualizations is how the visualization shall provide the best cognitive enhancement. En example: If Peter has 20 apples, Karin has 40, Anders has 33, Olle 67 and Anna 12 apples. What type of visualization is the easiest for humans to create knowledge.

1.     Histogram 2.     Piechart 3.     Polarchart

The example is a very simple and it is possible to question whether any visualization at all is needed. But I want to illustrate how the designers face a variety of choices based on a user-centric perspective. In this context, the ability to gain insights from a specific visualization could be regarded as a design quality. Qualities in design has been given some attention in the HCI community. A number of researchers have published articles on this and a lesson is that all design qualities is not relevant for all design objects (Gaver, 2012), (Zimmerman, Forlizzi, & Evenson, 2007), (Cross, 2001). I would guess that it would be possible to reason about design qualities for both visualization and respect dashboard.

It should be noted that visualization is a wide area in HCI. There are many parts that are not relevant for this project. It may be a matter of how data from an X-ray machine shall be visualized as a three-dimensional image of internal organs. It also may involve visualization of complex relationships in social media and so on.

In this context I do the research within the tradition of visualization that has its background in the field of statistics. In The Encyclopedia of Human- Computer Interaction, 2nd Edition is a chapter called Data Visualization for Human Perception (Few 2013 ) witch gives a historical review and summary of  key works in the field. Briefly, there is a culture of visualization and established methods. Such examples are bar charts, pie charts, etc. Another area is the visualization of the spatial aspects where maps are common. It is common with the temporal aspect and timelines is a cultural property in visualization. Recent years word clouds or tagg-clouds has established itself as a regular recurring way to prove the existence of something and so on . In HCI , the term pattern is established and there are reasons to examine whether there are patterns for visualization (Fallman, 2003), (Löwgren, 2002), (Wolf, Rode, Sussman, & Kellogg, 2006), (Erickson, 2000), (Welie & Veer, n.d.), (Road & Guy, 2005). To me it seems possible to investigate if there are patterns to be made in visualization of a process (risk analysis process).

Reading
Soon the Module Interactive Media Design Topic will begin and as I understand it would be a great opportunities learn more on central issues (From Course syllabu: One of two optional courses, each worth 5 credits, Which are Offered in order to allow students to choose Their Own areas of specialization). If the project as proposed in this document would happen the reading could involve following areas: Visualization, data representation, cognition. There should also be reading in design theory and processes to better understand what a framework is and should be. See Annex 2 for the current draft for reading.

Discussions on theory and methods

The primary challenge is that the project is excessive in relation to the time available. At the same time, I feel that it is not possible to select certain parts (1-4) and leave some parts behind. To enter the field of visualization without first analyzing user requirements or availability and format of the data will be to make the mistake that many believe that will lead to failure. The product will become neat visualization without meaning. This is something I want to discuss with my supervisor and consult a good delimitation. I see the following challenges in this project:

a) It is wide and multilayered research area. There must be a clear delimitation and schedule (see Annex 1 for a first sketch on timetable).

b) It is in the borderland information – cognition which is complex.

c) It involves an understanding of data formats, data communication, technology, programming, and I have not indebt knowledge on this.

d) Expenses – Professional visualization software costs money.

It is very common in the articles I read with findings about the importance of understanding human perception and cognition, but the articles do not offers any detailed explanation. I experience that there not is a particular focus within the HCI Community to actually evaluate how easy or difficult it is to create insight or knowledge from a particular visualization.

It has been rewarding to learn how common it is to start from a given problem and both the design process and the research process often has a user-centric perspective. It puts my project in a larger context. I think that it is possible to work in the manner proposed. Above all, it is interesting that in the area of visualization is always important with a need to understand the purpose of a particular visualization. That the visualization is about achieving certain specified benefits of the design at the same time visualizations of nature are visual (Graphic / aesthetic). I interpret the design orientated research to be rooted in reality and that it is welcoming to the research-oriented design aim to achieve different benefits.

Zimmerman, Forlizzi and Evenson gives in their article Research Through Design as a Method for Interaction – Design Research in HCI ideas for some criteria to design research can be evaluated based(Zimmerman et al., 2007). They raise questions about the research contributes to the understanding of the design process. Research results must be new. They must contribute to new knowledge. The research must be relevant to the research community, not only to specific researcher. I understand that research will relate to previous research but also be designed in such a way that it is possible to build on the research.

It is fortunate that both safety and risk analysis are areas that are dynamic. Work environment concerns many. There is an international standard and the area is researched. Risk analysis is a process that can be used in many fields and by this also a wide area. It is a general process. Perceptions of visualization, perception and cognition are also the established areas. For these reasons I believe that it is possible to create visualizations, presentations, dashboards and framework and the knowledge is generalizable. It is my opinion that after taking into account Zimmerman, Forlizzi and Evenson tips on how design research should be evaluated I see great opportunety to succeed in this project.

 

 

 

References

Barcelos, Y., Aburjaile, F., Leite, L. R., Oliveira, S. T., & de Melo-MinarcTi, R. C. (2012). Combining traditional and high-density visualizations in a dashboard to network health monitoring. 2012 IEEE Conference on Visual Analytics Science and Technology (VAST), 295–296. doi:10.1109/VAST.2012.6400509

Borgman, H. P., Heier, H., & Bahli, B. (2012). Paradise by the Dashboard Light: Designing Governance Metrics in Turbulent Environments. 2012 45th Hawaii International Conference on System Sciences, 4178–4188. doi:10.1109/HICSS.2012.465

Calculating the international return on prevention for companies : Costs and benefits of investments in occupational safety and health. (n.d.). International Social Security Association. Retrieved from http://www.issa.int/content/download/182976/3652717/file/2-ROP-FINAL.pdf

Chowdhary, P., Palpanas, T., Pinel, F., Chen, S., & Wu, F. (2006). Model-Driven Dashboards for Business Performance Reporting. 2006 10th IEEE International Enterprise Distributed Object Computing Conference (EDOC’06), 374–386. doi:10.1109/EDOC.2006.34

Cross, N. (2001). Designerly Ways of Knowing: Design Discipline Versus Design Science. Design Issues, 17(3), 49–55. doi:10.1162/074793601750357196

Elias, M., & Bezerianos, A. (2012). Annotating BI Visualization Dashboards : Needs & Challenges, 1641–1650.

Erickson, T. (2000). Lingua Francas for Design : Sacred Places and Pattern Languages, 357–368.

Fallman, D. (n.d.). Research-oriented Design, 1–3.

Fallman, D. (2003). Design-oriented human-computer interaction. Proceedings of the conference on Human factors in computing systems – CHI  ’03, (5), 225. doi:10.1145/642651.642652

Frolick, M. N., & Ariyachandra, T. R. (2006). Business Performance Management: One Truth. Information Systems Management, 23(1), 41–48. doi:10.1201/1078.10580530/45769.23.1.20061201/91771.5

Gaver, W. (2012). What should we expect from research through design? Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems – CHI  ’12, 937. doi:10.1145/2207676.2208538

Goodwin, S., Dykes, J., Jones, S., Dillingham, I., Dove, G., Duffy, A., … Wood, J. (2013). Creative user-centered visualization design for energy analysts and modelers. IEEE transactions on visualization and computer graphics, 19(12), 2516–25. doi:10.1109/TVCG.2013.145

Gresh, D. L., Rabenhorst, D. a., Shabo, a., & Slavin, S. (2002). PRIMA: A case study of using information visualization techniques for patient record analysis. IEEE Visualization, 2002. VIS 2002., 509–512. doi:10.1109/VISUAL.2002.1183817

Jankun-Kelly, T. J. (n.d.). A spreadsheet interface for visualization exploration. Proceedings Visualization 2000. VIS 2000 (Cat. No.00CH37145), 69–76,. doi:10.1109/VISUAL.2000.885678

Lindqvist, M., & Söderlind, P. (2013). Informationskompetens : en grundbok (2., [uppda.). Stockholm: Sant{é}rus.

Löwgren, J. (2002). The use qualities of digital designs, 1–14.

McKeon, M. (2009). Harnessing the web information ecosystem with wiki-based visualization dashboards. IEEE transactions on visualization and computer graphics, 15(6), 1081–8. doi:10.1109/TVCG.2009.148

Road, L., & Guy, E. S. (2005). “… real , concrete facts about what works …”: School of Computing , Mathematical and Information Sciences , University of Brighton, 99–108.

Ryan, J., Lewis, C., Fretwell, C., Doster, B., & Daily, S. (2013). A Balanced Scorecard Approach to Perioperative Process Management: A Case Study Perspective. 2013 46th Hawaii International Conference on System Sciences, 2606–2615. doi:10.1109/HICSS.2013.29

Sandner, T., Kehlenbeck, M., & Breitner, M. H. (2010). Visualization of Automated Compliance Monitoring and Reporting. 2010 Workshops on Database and Expert Systems Applications, 364–368. doi:10.1109/DEXA.2010.77

Treude, C., & Storey, M. (n.d.). Awareness 2 . 0 : Staying Aware of Projects , Developers and Tasks using Dashboards and Feeds, 365–374.

Weber, A., & Thomas, R. (2005). KEY PERFORMANCE Measuring and Managing the Maintenance, (November).

Welie, M. Van, & Veer, G. C. Van Der. (n.d.). Pattern Languages in Interaction Design : Structure and Organization.

Wolf, T. V., Rode, J. a., Sussman, J., & Kellogg, W. a. (2006). Dispelling “design” as the black art of CHI. Proceedings of the SIGCHI conference on Human Factors in computing systems – CHI  ’06, 521. doi:10.1145/1124772.1124853

Vozniuk, A., Govaerts, S., & Gillet, D. (2013). Towards Portable Learning Analytics Dashboards. 2013 IEEE 13th International Conference on Advanced Learning Technologies, 412–416. doi:10.1109/ICALT.2013.126

Yau, N. (2013). Data points : visualization that means something. Indianapolis: John Wiley {&} Sons.

Zimmerman, J., Forlizzi, J., & Evenson, S. (2007). Research through design as a method for interaction design research in HCI. Proceedings of the SIGCHI conference on Human factors in computing systems – CHI  ’07, 493. doi:10.1145/1240624.1240704

Årsredovisning Mekonomen, Meca 2012. (2012). Retrieved from http://vp083.alertir.com/files/press/mekonomen/201303225178-2.pdf

Non-scientific sources

Visualization as Process, Not Output  Retrieved from http://blogs.hbr.org/2013/04/visualization-as-process/ 2013-10-28

Årsredovisning Mekonomen, Meca 2012. (2012). Retrieved from http://vp083.alertir.com/files/press/mekonomen/201303225178-2.pdf 2013-10-28

 

 

 

 

 

 

Appendix 1 – Timetable a first sketch

1 December 2013 – 15 January 2014
Reading Interactive Media Design Topic. Efforts to carve out a clear process of research and design process. Detailed schedule clear.

1 January 16 to February 15
Working with prototypes and documentation of the design process.

February 16 to March 15
Working with prototypes and documentation of the design process.

March 16-April 15
Maria Normark, preliminary information: Around the 26th of March will design report is submitted and the design concept / prototype pitchas the class.

April 16 to May 15
It is unclear whether students should continue with design process and design of protyper or if students should focus entirely on writing a scientific article. Need answers to this.

May 16-June 15
Maria Normark, preliminary information: One of the last days of May to master article submission and it is vented through the opposition procedure at the beginning of June.

 

 

Appendix 2 – Suggested reading

S. Card, J. Mackinlay, and B. Shneiderman, “Readings in Information Visualization – Using Vision to Think,” Morgan Kaufmann, January 1999.

A historical review of visualization in human cognition http://link.springer.com/article/10.1007/BF02300481

Distributed Cognition as a Theoretical Framework for Information Visualization
http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4658127&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4658127

http://interaction-design.org/courses/information_visualization-_getting_dashboards_right.html