Boxes and Arrows: Stories by Sarah A. Rice

2003 Dublin Core Conference Summary

Madonnalisa Gonzales-Chan, Sarah A. Rice — Mon, 24 Nov 2003 21:51:23 GMT

2003 Dublin Core Conference: Supporting Communities of Discourse and Practice—Metadata Research & Applications Seattle, Washington September 28–October 2, 2003 Dublin what? You may be wondering, “What is Dublin Core? And why would you need a whole conference about it?” The end of September and beginning of October brought representatives from various countries around the world to a sunny and warm Seattle, Washington, host of the 2003 Dublin Core Conference. It was a nice, unexpected change to arrive in Seattle with lots of sun and warm weather...just enough for many first-time visitors to Seattle to enjoy until the more usual clouds came to settle in. What is Dublin Core Metadata? In the early days of the web there were several institutions very interested in sharing information about networked resources. Along with Online Computer Library Center (OCLC), several representatives from various aspects of library science and information publishing gathered to establish a semantic protocol to describe resources for information sharing. This initial meeting in 1995 in Dublin, Ohio, established the foundation for what is known as the Dublin Core Metadata Initiative (DCMI). Today there are 15 elements that represent the simplified set of Dublin Core's metadata. Dublin Core (DC) has recently become incorporated as part of many international metadata standards, globally adopted by CEN Workshop Agreement CWA 13874 as the National Information Standards Organization (NISO) Standard Z39.85-2001, and as a draft with ISO as DIS 1583. Initially the meetings were a series of opportunities for the working groups to meet face to face annually around the world. These workshops comprised tutorials, discussions on refinements and changes to the metadata elements, and workshops. Only recently have peer-reviewed papers, poster sessions, and, this year, pre-conference workshops been included to promote advancements in the scholarship and application of metadata, and more specifically the Dublin Core Metadata standard. The conference opening this year brought together the various committee chairs, who acknowledged the different members involved in putting the conference together. There were kind words for Stuart Weibel, the former DCMI director, who came to the stage for a few words, the opportunity to take photos of the whole crowd and the chance to reflect on how the past year has advanced DCMI. Metadata Primer and Metadata and Search, the two day-long pre-conference workshops that kicked off the conference, were enthusiastically attended. —Lisa Chan “The overview given in the Metadata Primer laid the groundwork for those who were not fully familiar with all of the aspects of metadata and Dublin Core.”Pre-Conference Workshop: Metadata Primer This session covered some of the basics of metadata. Following is a summary of the terms discussed in the Metadata Primer, their meaning, and how they relate to metadata or Dublin Core. The overview given in the Metadata Primer laid the groundwork for those who were not fully familiar with all of the aspects of metadata and Dublin Core. Metadata: Information about information; information or names we come up with to encapsulate and define information to understand it and to use it.

Metadata lives in databases, spreadsheets, or XML (extensible markup language) structures. Databases have tables, fields, and values. Metadata in XML has elements, attributes, and values. XML is good for providing a tree structure to metadata. It offers a different way of looking at information rather than a spreadsheet.
Metadata can identify, manage, and describe. It makes information usable by others (both machines and humans).
Dublin Core Metadata provides a standard wrapper for a resource—a rich description. It provides information such as what a resource is and what's in it.
A metadata schema creates the rules by which certain metadata are used on an information collection.
An XML schema provides rules around Dublin Core elements. An XML instance is what you type (the value).
Uniform Resource Identifiers are strings of letters in a networked address. A URL is an example of a URI for the web. Other strings can be used for other applications.
XML transfers the structure of information via the web.
A namespaces is the declaration of a system used, and points to a resource that provides a “key” or decoder to decipher the system.
RDF, or Resource Description Framework, supports a system of relationships between objects, allowing for the management of meaning, not just data. RDF is a particular type of metadata.
Application Profile is a metadata schema that is created or tailored for a specific use. It looks like a list of metadata schemas in the top of XML RDF file notation. It also lists elements and their explanation or description.
Registries are databases of metadata schemas.

After completing this workshop, most attendees were well-versed in metadata, its uses, and some of the issues to be addressed at the conference to follow. —Sarah Rice Pre-Conference Workshop: Metadata and Search This pre-conference workshop was a great mix of industry experts, presentations of case studies, and vendors talking about their wares. Hosted by the DC-Global Corporate Circle working group, many of the presenters came from corporate settings. The most dynamic and charged portions of the workshop were the questions and answers regarding the whole lifecycle of metadata establishment, quality, tools, workflow, and usage. Many of the concerns voiced during these question and answer sessions echoed concerns that have been raised at previous IA Summits on value-added service, ROI, and marketing/selling value. It was not surprising that such concerns related to information architecture, and better information practices, would spill over into this type of forum. Notes from the workshop: http://www.dublincore.org/groups/corporate/Seattle/ —Lisa Chan Opening Plenary Mary Lee Kennedy, Director of the Knowledge Network Group, Microsoft The opening plenary was an interesting overview of the inner workings of Microsoft's Knowledge Network. Mary Lee Kennedy, the director of the Knowledge Network group, presented on the work the group has done to bridge employees' information needs through an integrated enterprise information architecture. Kennedy discussed the group's mission to connect employees with the people and information they need in order to do their jobs. The organizing principles of their mission include:

The right quantity and quality of information
Relevance and sufficient context of information
A mechanism to establish trust in the information authority
A way to identify who else has knowledge
The ability to gather information from many starting points in the system
The ability to learn about a new resources as it is relevant and available

Through the rest of her presentation, Kennedy described actionable projects and processes that have made these principles a reality at Microsoft. The company has been able to incorporate aspects of this system into SharePoint, a Microsoft knowledge and content management solution. As she wrapped up her presentation, Kennedy acknowledged some challenges the Knowledge Network group has experienced that showed limitations of their organizing principles and better context to the information and better retrieval of information. Many aspects of this project have been documented in previous conferences, such as IA Summit 2001. —Lisa Chan Encoding DC in (X)HTML, XML, RDF Andy Powell, UKOLN The purpose of this tutorial was to introduce to attendees new to Dublin Core options for encoding the metadata standard into (X)HTML, XML, and RDF. Adam Powell reviewed some basic information regarding DC, though the tutorial was based on the assumption that attendees were familiar with the proper usage of DC. Powell briefly reviewed the concept of the “abstract model,” which was further discussed at the Infrastructure Working Group. Powell noted that your choice of encoding basically depends on the application that will be using the metadata. Without making any judgment on the encoding scheme, he reviewed how DC would be set up in each encoding type and offered caveats, limitations, and tips for how it would be handled. He gave lots of great examples in the presentation and provided some sample code in the appendix of his handout. Powell led the group through some of these samples, including simple errors that would be easy to miss when encoding DC. His recommendations for approaching the encoding were very helpful and very practical. —Lisa Chan Working Group: Global Corporate Circle Joseph A. Busch Global Corporate Circle Working Group has evolved as Dublin Core is implemented more often. Dublin Core guidelines are pretty well established, but they are not always clear to the average practitioner. This panel discussed what additional features would be necessary to apply Dublin Core to specific domains, a topic that is still largely open to discussion. The panel put forth some suggestions:

Individuals working with metadata in corporate environments should share elements and values for those elements. The panel noted that there is a need to manage both internal and external information.
Practitioners must be able to speak to applications developers, both internal developers and vendors. (There were a number of vendors at the conference trying to understand how Dublin Core is being used as well as their constituents and customers need.)
Best practices should be shared around how Dublin Core is being implemented in the corporate environment and what people have learned as they have taken on and accomplished these implementation projects.
It is important to define the unique needs of the corporate community that distinguish it from other communities who use and implement metadata.

Based on the panel's discussion, the group decided to:

Gather some best practices and use cases.
Sponsor a conference track for the next DCMI conference in a year.
Put together a workshop similar to the Metadata & Search workshop that was held at this conference.

At the end of the session, officers for the working group were identified and tasks were assigned. —Sarah Rice Smart Metadata Neil McLean, Metadata for education Gottfried Zimmermann, Metadata for appliances Wendy Chisholm, Metadata for accessibility Eric Miller, Metadata and semantics Stephen Stead, Metadata and ontologies This special session looked at a few ways DC has been used in non-traditional ways. Areas represented include education, museums, and hardware technology. These areas represent disciplines for which metadata, both simple and complex, has been used to help describe materials, describe transactions, and describe semantically linking resources. Neil McLean from IMS (Instructional Management System) Australia examined the use of DC not just from the context perspective of educational materials, but from the perspective of its potential use and the technologies that use it for learning. He also mentioned that there needs to be an examination of learning activities and how they relate back to the learning objects. McLean highlighted some issues related to better establishing metadata, including:

Expressing the complexities of material for both dynamic and static content.
Realizing that content has both a permanent and a transitive nature.
Noting that content and services are all different, and that people and content need to be expressed in the metadata.

The next presenter looked at the potential use of DC in a museum setting, in which objects are viewed from a conceptual reference. He proposed a more event-centric model, bringing together relational history and object models with the use of ontologies. The presenter mentioned that DC was limited because it could not support the dynamic nature of ontologies. By using RDF and ontologies, he hoped to dynamically create conceptual references among a body of museum objects as a way to provide a better context for the objects. Gottfried Zimmermann presented on the use of DC as the base metadata for physical hardware to enable various appliances to communicate with each other. The example he shared was a handheld device able to communicate with an ATM on an open protocol using DC as its metadata standard. Some of the value-add to this type of protocol was that various devices could openly communicate with each when the need came up, rather than relying on proprietary protocols limited to certain vendors and products. More information can be found about this draft ANSI (American National Standards Institute) standard here: http://www.ncits.org/study/docs/ita00006.htm. —Lisa Chan Paper Session: Use—Access, Needs & Users Sheila Denn, University of North Carolina Chen, National Digital Archives Program Francesconi and Peruginelli The focus of this paper session was on how user-centered design could inform the development of metadata systems. The papers ranged from user needs analysis, how systems were utilized, and how systems are changing to reflect what users need and want to support their work in education, legal research, statistical analysis, and historical archives research. Statistical Metadata Needs during Integration Tasks Sheila Denn from the University of North Carolina presented on the use of metadata to manage statistical data. The research project Denn spoke about involved government data with components for user interface, information management, and usability of the data for all users, not just information professionals. The project team had to address both experts of the data and typical end-users visiting the government website. The method for this project involved understanding users' needs by identifying use case scenarios, gaining domain knowledge on how the information could be used, understanding the coverage of the data, interpreting the data, and evaluating navigation and layout of information. The study found that there was not enough information to allow users to use the statistics properly in an integrated setting. For instance, data from various repositories were brought together to formulate a story. This data included the appropriate coverage of definitions, concepts, sources, location, time, units of measurement, and demographics. The project team discovered that discrepancies in these facets had an impact on analysis of information. The project team faced other challenges beyond data integration:

Information about the data was lacking.
There were no means of describing limitations for how data could be analyzed.
Users' knowledge was limited.
There were inconsistencies in interface design.
Data labeling was inconsistent.

The team aimed to use metadata, such as DDI (Data Documentation Initiative), to help wrangle the data. Over time they plan to include additional, domain specific elements to refine their metadata system. Paper: http://www.siderean.com/dc2003/301_Paper50.pdf More information: http://ils.unc.edu/govstat/ Functional Requirements of Metadata Systems: From User Needs Perspective Chen from Taiwan's National Digital Archives Program looked at three disciplines of current interest to her institution: arts, sciences, and biodiversity. Her organization is involved in the technical aspects of metadata and digital libraries. The program's project was to establish user-centered requirements to develop a metadata repository. These requirements, and the system they would produce, would align with four dimensions for users: the object, the experts, the lifecycle, and the use. The group realized that their needs went beyond a conventional relational database. Their mission was to identify the needs for a metadata system, bridge the relationship between content (creators, managers) and technology (tools, process, software, hardware), and determine how the two fit together as a unified system. From the group's perspective, there were practical operational relations that needed to be considered for the software, system, and users. From a series of interviews and questionnaires, they were able to establish a baseline for needs, as well as forge relationships with stakeholders. By analyzing the needs, they discovered six categories of metadata with 32 required elements. (More details can be found in their paper.) They were able establish this core set of metadata for the three disciplines. The group considered the required elements if they were absolutely necessary in more than a certain number of projects. The group is still trying to resolve some challenges, such as coverage of functions, gaps between system implementation and requirements, metadata systems integration with external sources of content, and the exchange or transfer of metadata across institutions. Paper: http://www.siderean.com/dc2003/302_Paper33.pdf Access to Italian Legal Literature: Integration between Structured Repositories and Web Documents Francesconi and Peruginelli presented the latest developments of the Institute of Legal Information Theory and Technologies, Italian National Research Council. The Institute is in the process of establishing a portal for both structured information and web documents. The portal serves as a repository of legal material that integrates the access and presentation of the information. Part of the group's process was mapping bibliographic records to Simple DC. They developed modules to populate web documents with Dublin Core. After the metadata was in place, they were able to build a fairly sophisticated classifier tool using Bayes' theory as a way of organizing information in the portal. Much of Francesconi and Peruginelli's presentation revolved around the measurements of success in correlating the documents based on this classifier tool. They used Dublin Core as a common view on the disparate data and content. They also looked to the Open Archives Initiative for gathering metadata from various legal repositories outside of the portal. Using Bayes' algorithms and the metadata standard, they were able to create a federated portal for legal content. Paper: http://www.siderean.com/dc2003/303_Paper23.pdf —Lisa Chan Metadata for the Project Management Community Dr. Robert Allen, University of Maryland, College of Information Studies Barbara Richards, Food and Agriculture Organization of the United Nations David Briggs, Boeing Company This group was initially brought together to discuss the possibility of formulating some metadata elements that could be used for project management. Three case studies were presented, and there was a discussion following. The session began with the premise that there might be some metadata for project management that could be defined and used across different information domains. However, as each presenter spoke, it became apparent that the metadata necessary for each project discussed was very closely tied to the subject domain (aerospace, engineering, and agriculture). It didn't seem practical to try and glean any similar metadata to try and leverage across all the projects. NASA The ultimate goals of the project were to have a single repository of projects, to support organizational learning and duplication of effort, and to manage resources. The NASA environment is highly distributed, with no single repository for project information. This presentation focused on the attempt to collect, in a single database, information about all projects at NASA. This was an impossible task; even collecting all projects just within the engineering group was a huge project. The task was difficult because of the complexity of defining a "project." Projects spawn other projects. Some projects last for months, some for years. There is a parent/child relationship to many projects. Also, security is an issue — there are many levels of secure access to sensitive information. In the NASA culture, there is a belief that if each project keeps its own information, it will better allow for control over the sensitive stuff. The presenter believes that this is actually not true. There was a concerted effort to educate the company about the idea of a central repository. A central repository with well-defined levels of access and clear definitions around sensitivity of and access to information was a more practical approach from both a resource management and a security perspective. Food and Agriculture Organization A central repository for all projects in the UN's Food and Agriculture Organization, from both developing and developed countries, provided to be immensely valuable, especially for developing countries. Each project captured methodology as well as lessons learned that could be used by other developing countries when planning a future project. Leveraging existing knowledge was key. The metadata required for this repository was presented. The overall message seemed to be that the needs of the intended audience drove what information was captured and how it was managed with metadata. Some references to Dublin Core metadata were made, mainly that it was used as a starting point and then augmented as needed for the project's information management needs. Boeing For Boeing, project management-related information was crucial for a number of reasons. First, government regulations required that information about all phases of a project be retained for the life of the project (which could easily be 70-100 years). There were also considerations around gathering and keeping information to use in any legal matters. One of Boeing's key challenges was a changing technology. Because the shelf-life of products is so long, technology can change multiple times within a single life span. There was a move, therefore, toward digitizing all information. It was a costly effort, but ultimately necessary because of the complexity of Boeing's information management issues. Conclusion The three presenters agreed that all projects, regardless of their subject domain, have some similarities. Projects are types of events, defined as an individual or collaborative enterprise, carefully planned with the purpose of achieving a particular goal. In this special session, the presenters noted that Dublin Core metadata served as a starting point for all these projects, but that further refinement or addition was required to meet the projects' complex information needs. The presenters also agreed that each project used a similar process for the development, identification, and application of metadata. The information covered in this session could be gathered and posted as a set of "best practices" for using DCM in a project management capacity. The group agreed that the similarities lie within the project methodology rather than similar metadata for the subject domain of a project. Gathering project methodology information around metadata would be of benefit to the greater community to provide learning around project management. Based on the discussion that followed the presentations, it seemed that most, if not all, projects were quite different in their goals as well as their subject domain. However, similar project methodology was used for all three projects. It might serve as a useful exercise to examine some of the popular project management software to glean some potential project metadata suggestions and compile those suggestions to be circulated within the special interest group for comments and refinement. The group could then present these suggestions to the larger Dublin Core community to provide a basis for some best practices for project management. —Sarah Rice Metadata Value Spaces Marcia Zeng, Kent State University Rachel Heery, UKOLN (UK Office for Library and Information Networking) Traugott Koch, Lund University NetLab, Knowledge Technologies Group More and more values are being used differently by different groups. The objectives for this discussion focused on two main questions: What should be explored? What's out there? There is current work on establishing some standards in different information domains, and current systems of use are already established. A single controlled vocabulary (CV) or thesaurus is not adequate for everyone's use. There's an overwhelming level of complexity that makes a single taxonomy unwieldy. Also, terms in different domains are used differently. It is important to match thesauri to users' terms, hence the need for multiple CVs and thesauri, even within a single organization or field of practice. Best Practices The session presenters recommend the use of controlled vocabularies, even when it is possible to have a very large vocabulary. The presenters suggested drawing from the following sources when creating a CV:

Established CVs or classification schemas (LCSH, Dewey Decimal, etc.)
Standardized vocabularies (DC: Type, format, language, etc.)
Name Authority Files (Thesaurus of Geographical names)
Controlled lists

One problem the group noted is that many established CVs are not created for networked environments. The presenters also discussed the need for extensibility and scalability in CVs. For syntax, there is the pre-coordination vs. post-coordination issue: Does the system match up terms for complex meaning, or do we leave that to the user doing the searching? The thing to remember, the presenters said, is that we are dealing with words, concepts, and their relationships. How we represent, standardize, and try to control them for organization purposes is constantly changing. —Sarah Rice Working Group: Education This working group is actually a neat cross-pollination opportunity for metadata and its use in education. While many in the audience came from the K-12 arena, there were definitely many who were involved in establishing relationships with other organizations also trying to tackle metadata for learning objects, learning activities, and content sharing. The main focus of this session was to discuss the purpose of the working group, which led to an agreement that the mission of the working group needed to be re-evaluated. Since the group had an application profile in development in collaboration with the IMS/IEEE Learning Objects Metadata initiative and other learning-related metadata, that group agreed to continue the discussions around this type of work. —Lisa Chan Poster Sessions Posters were a great way to engage with colleagues in the use and evaluation in the use of Dublin Core and metadata standards for information management. Topics presented on posters ranged from research methods to practical implementation techniques and best practices to an overview of how to learn from metadata usage. Papers related to the posters describing the research and implementation projects were also included in the conference proceedings. Links to abstracts related to posters: http://dc2003.ischool.washington.edu/program.html#posters —Lisa Chan “It will be exciting to see how Dublin Core metadata and other metadata standards start to share a common ground with the information architecture community.”Conclusions Overall the conference showed lots of enthusiasm in the use of standardized metadata for future inter-operability between institutions such as libraries, government agencies, and corporations. It was interesting to hear various DC people acknowledge that they needed more awareness of how DC was being used in non-traditional settings and ways, such as in corporations, with hardware, and in conjunction with other standards. It will be exciting to see how Dublin Core metadata and other metadata standards start to share a common ground with the information architecture community. Next year Dublin Core will be taking its show to Asia. See you in Shanghai, China, in the fall of 2004. Stay tuned for opportunities related to calls for participation. —Lisa Chan

Web Resources

Dublin Core
http://www.dublincore.org
Dublin Core 2003 Conference
http://dc2003.ischool.washington.edu
Dublin Core 2003 Proceedings
http://www.siderean.com/dc2003/search.jsp
More information about Dublin Core 2004 can be found at the main Dublin Core website .

Madonnalisa Gonzales-Chan wrangles the volunteers for Boxes & Arrows. During the day she is Metadata Services Manager at Stanford Graduate School of Business. Her primary role is to provide guidance on information management best practices for applications and websites developed at Stanford GSB. She is also involved in metadata and taxonomy development initiatives at GSB. Previous to Stanford, she was an Information Architect at AltaVista developing information and interaction architectures for AltaVista's LIVE! portal and search services. Some of her past work experiences include a short stint as a volunteer on the re-architecture of the San Jose Repertory website, Academic Technology Specialist for the English Department at Stanford University, and Systems Librarian at Innovative Interfaces Inc. Madonnalisa has a M.S. in Library and Information Science from the University of Illinois, Urbana-Champaign and a B.A. in English Literature from the University of California, Irvine. In her free time she moonlights as a karaoke singer, rides “shotgun” on the tracks of Laguna Seca Raceway, and dabbles in finding the meaning of life through calculus. Oh, by the way, don’t hesitate to ask her about her name.
Sarah Rice has her own consulting practice, Seneb Consulting, and has worked with clients such as Sun Microsystems, PeopleSoft, VeriSign and National Semiconductor. Her speciality is in information complexity and regularly applies information science principles and methodologies to reduce complexity in content-heavy information environments. She has a degree in Library and Information Science and has been practicing information architecture since 1995. Her website is www.seneb.com. When not practicing IA, Sarah spends her spare time chasing after two small kids and attempting to reduce complexity on a whole different level.

Using Adoption Metaphors to Increase Customer Acceptance

Sarah A. Rice — Wed, 05 Jul 2006 17:14:22 GMT

"Adoption metaphors have a lifecycle. They begin by introducing a new concept. They help us map something new to something we already understand and give us a framework in which to understand the new thing."

Metaphors are used every day. We are all familiar with them and what they are. They help us understand conceptual ideas, convey complex notions and have a shared understanding so that we can talk to each other using verbal shorthand. Take electronic mail, otherwise known as email as an example. Email seems so much like regular mail, except that there is no paper, no ink, no envelope, no postage stamp, and no postal carrier. There is, however, something familiar about composing a message and sending it to someone else.

What about the wildly popular Tivo’s metaphor? I applaud the decision to use a well-known comparison to explain what the product does: the video cassette recorder. Tivo does replicate many of the VCR’s abilities… and yet it offers so much more! We’re so overjoyed to be able to pause live TV that we overlook the fact that Tivo won’t play your video cassette tapes, let you transfer recorded shows from one machine to another, and it requires a monthly fee. Metaphors help us grasp new things, but they don’t necessarily account for all aspects of that idea. VCRs couldn’t pause live TV; regular postal mail couldn’t arrive at its destination 3.2 seconds after it had been sent. The main characteristics of the original metaphor allow us to understand the basics of the new; the rest we learn over time. Moreover, the original metaphor helps us easily understand why a product might be useful or necessary, which means we’re more likely to adopt it into our daily lives. Adoption metaphors have a lifecycle. They begin by introducing a new concept. They help us map something new to something we already understand and give us a framework in which to understand the new thing. After a while, the concept isn’t new any more, and people usually understand it pretty well without needing the original metaphor. The internet is a perfect example. Remember the term “Information Superhighway”? It was such a buzzword back in the 1990s. Although the internet had been around for a while, its introduction as an information superhighway helped frame the whole idea so that others could understand it. They could understand it because it was framed in terms of their daily lives. Do we still use the term “information superhighway”? Not much. Does this mean that we don’t use the internet any more? Is it gone from our minds the same way the term has gone away? Hardly! The internet is such a pervasive part of our culture now. It is everyday. It is mundane. It’s the exception rather than the rule to have no internet connection available to you. We are offered connections at work, at home, in coffee shops, through cell phones and in most public libraries.

The concept of the internet has been so well adapted into our culture, that it is now being used as a metaphor itself for other things. The language of the net pervades our everyday lives. For example, last week I was interviewing a woman who talked about a meeting she had with her supervisor because she needed to get up to speed on a project. Two years ago, she might have said that he informed her, he briefed her, he told her everything he could about what he knew on that particular topic. However, she said, “he downloaded it to me”. There was no computer in the room. No internet connection was involved. It was a verbal transaction, yet she invoked a metaphor that is widely recognized as being synonymous with online activity (the act of collecting or retrieving an electronic file from a remote location). Instead of an electronic file, it was ideas or thoughts. Instead of being retrieved from a remote server, it was retrieved from the supervisor’s brain. Instead of being received onto a computer, it was received into the person’s collection of thoughts. Instead of a file being “pulled” from a server and collected on one’s own computer, the information was “pushed” from one person and collected by another. As you can see, not all aspects of the metaphor fit precisely, but when she said “he downloaded that information to me,” I had no doubt what had happened between the supervisor and the direct report during the lifespan of that meeting.

With this example, you can see the lifecycle of an adoption metaphor, from its introduction, when it is a novel concept first being introduced to the public, to acceptance, when our understanding moves beyond the initial adoption metaphor and fully embraces the concept itself on its own merits. At that point, the metaphor has outlived its usefulness and is either discarded (information superhighway) or becomes mundane (download). You know the adoption metaphor has reached the pinnacle of success when the metaphor itself is used as a metaphor for other things (“where can I get “TiVo” for my radio?”). We don’t bother to refer to cars as “horseless carriages”, but we often use cars as metaphors for other things. Three quotes from recent articles: “Cops drive home seatbelt safety [in a 3-day game event aimed at high-schoolers] ” “Congress Revs Its Engine.” “Fitness Beginners learn how to go from zero to sixty with these workout tips.” Metaphors accompany every new technological leap. They help with the core concepts such as a blog (originally “web log”) to the interface itself in iconic button choices. When introducing something new into the marketplace, how do you choose the right adoption metaphor? How can you tell if it will work? Is it luck? Do you go with your gut and then “wait and see”? Happily, there are ways to analyze what metaphors people use to think about things. Systematic analysis at the beginning of a project can better ensure that you’ve got the right metaphor for your new product or service. In part 2 of this series, I will outline ways to analyze effectiveness of current metaphor use as well as ways to identify new or more impactful metaphors.

The following books and articles offer more information on conceptual metaphors:

DesCamp, Mary Therese, and Eve E. Sweetser. “Metaphors for God: Why and How Do Our Choices Matter for Humans? The Application of Contemporary Cognitive Linguistics Research to the Debate on God and Metaphor” Pastoral Psychology. 50.3 (2005): 207-238.
Fauconnier, Gilles, and Mark Turner. The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities. New York: Basic Books, 2002.
Lakoff, George, and Mark Johnson. Metaphors We Live By. Chicago: University of Chicago Press, 1980.
Rohrer, Tim. “Conceptual Blending on the Information Highway: How Metaphorical Inferences Work.” 1995.

MindCanvas Review

Sarah A. Rice — Wed, 18 Jun 2008 18:26:57 GMT

MindCanvas describes itself as a remote research tool that uses Game-like Elicitation Methods (GEMs) to gather insights about customer's thoughts and feelings. It was developed by Uzanto Consulting, a web product strategy firm. When I first learned about MindCanvas, I understood it to be an online card sorting tool. Happily, it's much more than that.

As a veteran IA consultant, I have used MindCanvas a handful of times during the course of different projects. I have also conducted card sorting exercises without the tool. I am thrilled to have a useful—and user-friendly—tool at my disposal. One of my main reasons for selecting MindCanvas was the reputation of one of its creators, Rashmi Sinha. She is well known and respected, and I felt assured that any tool designed by a fellow IA for IAs couldn't be all that bad. I was right.

MindCanvas provides open and closed card sorting capabilities, as well as a host of other UT tools: Divide-the-Dollar, Clicky, Sticky, Concept Test, and FreeList. Clicky and Sticky allow users to react to a wireframe or prototype by answering questions about images and content, or applying stickies (Post-it–like notes) with attributes to a visual image. FreeList and Divide-the-Dollar allow you to elicit product ideas and prioritize them by having participants list and rank the features they find most useful. All of these methods offer easy-to-use interfaces to help your research participants along.

Deciding which MindCanvas method to use is one of the more complicated parts of the tool. It's card sorting methods are good for validating a site's navigation or information hierarchy. You can also explore user needs and values and gather feedback on brand and positioning by using some of its more specialized UT methods. MindCanvas' website and supporting help wiki provide information on selecting the appropriate testing method for your website or product.

Using MindCanvas

The basic process for using MindCanvas is as follows:

After payment, sign an agreement to obtain a login and password.
Decide which method (i.e. Sticky, FreeList, etc.) addresses your research needs.
Create potential research questions and tasks based on the MindCanvas method you have selected. (I've used OpenSortand TreeSort).
Upload questions to MindCanvas' Workbench.
Test the research study and make changes until you are satisfied with it.
Send out the test site URL to your participants.
Monitor the study (i.e. see how many people have completed all the tasks).
When the study is concluded, send a report request to the MindCanvas team.
Receive the reports in visual form and download raw data from the MindCanvas site.
Embed reports into PowerPoint or Word document and review results with client.

I usually take several days to review the reports before showing them to my consulting clients. Doing so allows me to more easily explain the results. (Here's a pointer to anyone using MindCanvas: To view the results properly make sure PowerPoint is in "Slideshow" mode).

Strengths

MindCanvas has a couple shining strengths I'd like to illuminate:

An engaging, easy-to-use interface for your customers or end users. It's fairly self-explanatory and makes routine UT tasks fun.
Stellar data visualization tools once your study is completed.

User Interface

MindCanvas' interface is what sets it apart from other UT software I've seen. Its creators took their inspiration from the world of digital gaming to develop an interface that's engaging for the person using it, while gathering important data for researchers. Its card sorting methods employ a floating hand to deal cards, which are then sorted by users. Another method gives users virtual gold coins to vote for their favorite product features. These exercises are enhanced by accompanying sound effects. I've received numerous comments from users describing MindCanvas' exercises as "fun". They have also commented that while they don't understand how these exercises will help me build a better website or software interface, they still enjoyed the tasks and were pleased at the conclusion of the test.

The other online research tools I've reviewed offer more awkward interfaces. Sorting exercises take multiple steps or the online tasks are not intuitive and confuse research participants. I'm not interested in making my users become experts at online card sorting or other UT methods. I simply want to extract what they know or understand about a particular website or service.

According to Jess McMullin of nForm User Experience Consulting, "MindCanvas is unmatched as a remote research tool in its ability to provide creative methods for gathering data [and] engaging participants....."

Data Visualization

Another MindCanvas strength is its data output. Although you can obtain the raw data and analyze it yourself (assuming you have statistical software and know how to use it), the real benefit of MindCanvas is its easy-to-understand data visualizations, which showcase the results of your study. All my clients have received clear, easy-to-interpret answers to their research questions. The visualizations can be embedded into a PowerPoint slide or Word document, making them easily accessible. Your clients don't have to rely on your interpretation of the data; they can interpret the data themselves if they choose. Every client who has viewed MindCanvas' data visualizations has been impressed and wondered why it wasn't used all along.

Weaknesses

I've used MindCanvas a handful of times and encountered some weaknesses:

Study Size: If you have a large client with complex, statistically rigorous research needs, MindCanvas is not for you. It has a limit of 200 users per study. Two hundred is plenty for most of my research needs, but some of my clients want to go beyond that.

Data Sorting: If you have complex user segmentation needs, MindCanvas has its limitations. It allows you to perform a single data sort to identify user sub-groups. For example, it's easy to segment all male vs. female participants or all participants who are 21- to 50-years-old. If you need to segment 16- to 20-year-old females or men who only shop online (or any two parameters of your choice), you'll need a different tool. There are ways around these limitations: You can create two separate research studies to deal with different users, or you can build more complex research questions to solicit the answers you need in order to sort the data required. However, these solutions have limitations of their own, so there is a trade-off.

Pricing Structure: The current pricing structure is $499 per study, with each accompanying report $99. This is adequate for quick-and-dirty research to resolve obvious user issues, but the pricing structure doesn't scale well. For example, if you run a single study and want multiple reports for different audience segments, each $99 report adds up quickly. It can be difficult to budget up front before the research study is even developed, leaving the door open for cost increases. If a simple card sorting tool is all that you need, check out WebSort, which costs $499 for three months of unlimited use and automatically generates a dendogram. (Please note that MindCanvas offers much more than card sorting).

Data Analysis Bottleneck: Some of the back-end data analysis is done by a human, who works on a schedule. All data reports are generated once a week. If you get your report order request to Uzanto by the Tuesday deadline, results will be available by Thursday. This might not work with your tight project schedule, in which case, you're out of luck.

MindCanvas's Workbench

MindCanvas is currently offered in self-service mode. This means that you (or your researcher) need to become familiar with the finer points of MindCanvas' Workbench for constructing studies. The upside is that some parts are made easy, like being able to "copy" another study in order to create your own (a handy feature), or creating as many preliminary studies as you like before distributing the real thing.

Figure 1: Manage Activity

The downside is that some interface elements in the study creation console are a bit mysterious. For example, under Manage Study, it's unclear if the data has been downloaded 164 times or if there are 164 participants who have completed the study. The difference between Manage Study and Track Activity is also hazy. Manage Study allows you to specify where to send users after they have completed the study and limit the number of participants or the length of the study, while Track Activity informs you how many people have completed the study. The Download Tracking CSV gives you access to a text file with a list of all participant's URL information and their start and stop times.

Figure 2: Track Activity

The Workbench allows access to MindCanvas' powerful study creation module, but you can tell most of the design effort went into the end user's interface, not the study designer's. Luckily, there is a wiki available which answers a lot of questions and Uzanto consultants are very friendly and helpful with the occasional question.

Conclusion

The IA community can finally say that we have a tool designed for us. For so long, we've had to take existing tools and try to use them in ways not intended by their designers, sometime with frustrating results and having to develop clever and complicated workarounds. These issues are no longer a problem. It's a tool for us, made by one of us. It's about time!