The second point relates to value, the basis on which economists interpret the characteristics of cultural capital that distinguish it from other capital goods. In common parlance the concept of an asset connotes worth, frequently thought of simply in financial terms.
Cultural capital is no different—it generates economic value, and does so both in its stock form a historic building can be sold and as a flow tourists pay to visit a site.
Economics and Culture. This concept seeks to capture the range of nonmonetary values attributable to cultural phenomena. In the case of heritage buildings, sites, and so on, the concept of cultural value is cognate with that of cultural significance or heritage values as understood in the heritage profession, as I will soon discuss. It should be noted that proposing the existence of a concept of value that is not measurable in financial terms, as is essential in the economic definition of cultural capital, requires a broadening of outlook among economists schooled in the strict neoclassical tradition.
In the standard model of an economy comprised of profit-maximizing producers, utility-maximizing consumers, and perfectly functioning markets, the value of a good or service is fully representable, in principle at least, in monetary terms.
It is assumed that no matter what the motivation for demand, if an individual values something they will be prepared to pay for it, and their willingness to pay can capture all dimensions of their underlying preferences, including those derived from aesthetic or other cultural judgments.
Introduction of the concept of cultural capital into the economics of heritage has drawn on the parallel concept of natural capital in the economics of the environment El Serafy Citation: El Serafy, Salah. New York: Columbia University Press. Washington, DC: Island. A particular parallel relates to sustainability. The management of natural capital can be understood within the paradigm of ecologically sustainable development, where economic, social, and environmental values are interpreted within a holistic system World Commission on Environment and Development Citation: World Commission on Environment and Development.
Our Common Future. In the same vein, it can be seen that sustainability provides an overarching framework for interpreting the management of cultural capital, allowing the articulation of a concept of culturally sustainable development mirroring that of its environmental counterpart Throsby Citation: Throsby, David.
A further advantage of this theoretical synergy between natural and cultural capital is that methodologies to assess the value of environmental assets have proved to be directly transferable to valuation processes in the economics of cultural heritage, as we shall see further in the next section. Although there may be some variation in the detail of different approaches to valuing cultural heritage assets from an economic perspective, the fundamental distinction between economic and cultural value alluded to above holds, whether applied to asset stocks or the services they provide.
That being so, we can divide our account of valuation procedures according to these two value elements. We turn first to economic value , which can be defined using methods of economic analysis and is expressible in monetary terms—the values that individuals are prepared to pay for in one way or another.
The categories into which the economic value of heritage can be divided correspond to three identifiable ways in which individuals experience heritage—use, nonuse, or as a beneficial externality. Use value accrues to individuals, households, or firms through the direct consumption of heritage services. It may be experienced, for example, through the ownership of heritage assets, or the enjoyment of the services of a heritage asset living in a heritage house or working in a historic building.
Such values are reflected in market processes, and can be observed in various financial transactions. Direct use value of heritage also accrues to tourists visiting cultural sites, measured by variables such as entrance fees. The second aspect of individual valuation is the nonuse or passive use values , which are experienced by individuals but are not reflected in market processes, since they are derived from attributes of cultural heritage classifiable as public goods.
Research in environmental and ecological economics over the last twenty years or so has identified three categories of passive use value that are equally relevant to heritage: existence, option, and bequest values. The third type of value of cultural heritage experienced by individuals stands somewhat apart from the above two categories, although it entails both use and nonuse characteristics. It derives from the fact that heritage may generate positive spillovers , or externalities.
Heritage buildings, for example, give rise to a beneficial externality if passersby gain some transient pleasure from observing their aesthetic or historic qualities.
For example, pedestrians in Milan may enjoy the sight of the Duomo as they walk through the adjacent piazza. In principle the economic value of such a benefit could be estimated, although in practice it seldom is.
But the fact remains that positive spillovers are an identifiable and potentially significant value of heritage that accrues to individuals. In regard to measurement, the assessment of use values should be straightforward, since they are derived from financial transactions that can be observed or estimated.
Much attention has been paid to the more problematic estimation of nonuse values in applied research in the economics of cultural heritage, adapting methods from other fields. The approaches in use can be classified into revealed-preference and stated-preference methods.
The former rely on inference from observed behavior, such as the use of real estate prices to estimate whether the heritage qualities of domestic dwellings in a certain area have an effect on their sale price Moorhouse and Smith Citation: Moorhouse, John C.
Thus, assessment by economists of the nonmarket benefits of cultural heritage has concentrated overwhelmingly on stated-preference methods using contingent valuation or, more recently, discrete-choice modeling.
Stated-preference approaches involve asking people to indicate their willingness to pay for the benefits received, or their willingness to accept compensation for their loss. The investigation may take place under quasi-experimental conditions, or more commonly may be administered through sample surveys of individuals.
For instance, the nonuse value of a local heritage site might be assessed using contingent valuation by means of a survey of a sample of residents of the area Cuccia Citation: Cuccia, Tiziana. A discrete-choice experiment yields a wider range of information compared to that obtainable from a contingent valuation exercise.
Research Report 2. Ritchie, Franco Papandrea, and Jeff Bennett. Some payment requirement is usually included such that willingness to pay for the various attributes or for the site as a whole can be inferred. Discrete-choice surveys are readily administered online and can thus command relatively large sample sizes. They do require complicated experimental design, but nevertheless these sorts of assessment methods are destined to find wider application in the future. What conclusions can be drawn about the usefulness of these economic assessment methods in the practical world of heritage conservation?
Some form of economic evaluation of a conservation project is very likely to be relevant, if not essential, if the project is seeking to secure funding or to justify funding already received. The great majority of heritage projects are initiated for cultural reasons rather than for economic gain.
Nevertheless it is likely that all projects will generate some benefits whose value can be represented in financial terms. All assessments are likely to include some monetary measurement of direct use values. In addition, as a component of an overall judgment on the economic worth of a project, it may be desirable or necessary to demonstrate in economic terms that the nonuse benefits have been or are likely to be significant. However, the sorts of economic assessments described above require expertise and resources.
Even if the latter are available, the former may be in short supply. We turn now to the assessment of cultural value. Other illustrative examples in this volume were taken from, for the most part, state litera ture or reprinted from periodicals. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Ask any person on the street what heritage management is about and you will hear a variety of answers.
Heritage management is partly about preserving the legacy of the past that is in the custody of memory institutions such as archives, Skip to content Author : E.
Often technology works best alongside process and operational innovations that have nothing to do with writing code. One way we successfully partner with communities is to prioritize quick wins early on. If we can fix something at very low cost to our team, even if it has absolutely nothing to do with the project at hand, we can very quickly demonstrate value to the people we are trying to help who, at times, can be hostile to change or innovation.
This is an exercise in building trust and a shared sense of purpose. We are in the room to help. We are not here to take away your job, or data, or value. There is a great deal of fear that comes along with municipal innovation. Fear of change, fear of loss, fear of irrelevance. That is a dynamic that we have to grapple with. By making sure that we build solid relationships and emphasize mutual benefit, we demonstrate that we have no interest in taking away power.
We are not building you solutions in an isolated chamber; rather, we are designing and building technology in collaboration to make things work better.
Can you give us a concrete example of something you might do to build this kind of trust and demonstrate value even before you start the actual project? The anatomy of a good partnership while working with government distinct from working with a nonprofit or university is highly contingent on the health of the relationships you build and the ability to manage power effectively. One of the most important strategies I use is to identify a champion of our work. Any technology project will fail if you do not have someone at a sufficiently high level who will provide the political cover or social capital required for success.
This is particularly the case if you are trying to introduce a completely new type of work into whatever agency or department you are entering. Having the buy-in and the support of a person at the highest level possible proves effective when you are trying to make big changes. That may sound like a no-brainer, but it is quite important. The second strategy is having a champion at a much lower level, which means making sure to involve people who are actually going to be impacted by the project on a day-to-day basis.
This actor is important on a number of levels. We also need to make sure that the person responsible for actually managing that work is on our side too. We develop dialogue and a human relationship. And ultimately the project is successful because we had buy-in from the person at the desk level as well as the higher authority buy-in that gives us permission to make big, sweeping changes.
In the past, you have worked with universities, and you have described how anchor institutions can be important to a successful partnership. Can you talk a little bit about how these collaborations between institutions and community organizations work in practice?
Do you have insights on how to make these collaborations successful? At my time with LocalData, we focused on a number of projects that served multiple audiences, typically pursuing better data about the condition of blighted properties or creating data where none existed. We saw some patterns repeat among the partners we worked with: governments that wanted to build reliable administrative datasets to be used for policy-making and budgeting; community-based organizations that were motivated to close information gaps on quality-of-life issues to fuel activism and fundraising activities; and universities anchor institutions that sought to provide graduate students with an opportunity to apply social science research methods to real-world scenarios.
In working toward these related but distinct goals, we formed partnerships across all three stakeholder groups. This partnership model—a university, a community-based organization, and a government body—proved highly effective in building a lasting community around data and technology. In , Detroit was scattered with thousands of vacant properties. Many of these abandoned homes negatively impacted quality of life for remaining residents, especially for reasons of arson and public safety.
Community groups were feeling frustrated with the lack of public response to this crisis of vacancies. People were mobilizing locally to save their neighborhoods by collecting their own data in low-fidelity ways.
Neighborhood associations would do walking tours and write down information that they thought was important to foundations that fund neighborhood cleanups or safety patrols. They might use this data as evidence to bring to police departments or to point to public health concerns at specific intersections. As neighborhood organizations were collecting data, government agencies local and federal were also collecting data, typically for regulatory purposes: The tax collector gathers information about condition of properties because they have to by law.
The Census Bureau relatively infrequently gathers information about property vacancy for regulatory reporting. Detroit was also under a great deal of political pressure to respond to the major public health problem impacting the community. There was a sense that something needed to be done, but there was little reliable data available to work with. Local universities were also active—these are institutions that provide a great deal of historical context and research capacity to understand complex problems from many different angles, and they are connected to groups of willing young novices in the field.
We typically partnered with university planning departments because they had graduate students eager to practice what they were learning. I will also say this was not and is not the norm. Governments do not usually work with communities to collect or produce administrative datasets in an official capacity.
Universities may partner with a community-based organization or a nonprofit on a capstone, but rarely do they work with governments to produce datasets with any authority. The inclusion of community-based organizations allowed for the voices of residents to be embedded within the information itself. Even more so, universities actually do provide the rigor that is rooted in social science research.
Universities know how to design a survey well, and they will enforce quality standards in the process. The final benefit of this partnership model is community-building.
You are describing data collection almost as a democratic practice, reinforcing accountability politics and shared dialogue about what the problems are, which does this beautiful thing of melding local and expert knowledge into a kind of shared vision. There is a lot that can go wrong when you are involving multiple stakeholders in a really complicated task like collecting information about every single building in Detroit.
That is a lot of complexity. I think it works because it is productive. People want to work on things that actually have an impact. Nobody wants to spend their time volunteering or providing input for something that is not going to go anywhere.
There is a magnitude associated with forms of collective action that surpass individual actions like complaints and town hall attendance. We closed the time and space between input and outcomes so that everyone could very quickly see the impact of their volunteerism.
There is an immediacy to it that makes it feel really good to all parties. Are there other ways to support this kind of data and tech literacy for civic engagement?
Data and technology literacy has a great deal of potential even for those new to the field. If we look at the history of how technology and data analysis has evolved within urban planning, we can see one of the greatest success stories in pedagogy itself. We are now training new and professional urban planners about how data and technology are best applied in the field and, more importantly, how to create new tools instead of just how to use them.
This is becoming as common as learning GIS. While this is occurring in academic departments, there is also a great opportunity to blend urban data science and technology in fields outside of planning.
An easy path to doing so is to go back to this theme of working across disciplines. Within a university setting, this can be done by leveraging adjacent departments in computer science and information science.
There are whole pools of talented engineers looking for ways to apply their skills to real-world problems. Working across departments is a great way to introduce technology and data into your practice. Another resource available to professionals or academics are volunteer networks of programmers and data scientists who want to give back to their communities. These are groups like the Code for America Brigade, which are decentralized networks of volunteer programmers all over the country just looking for ways to support nonprofits or government agencies.
There are also emergent internship and fellowship programs for civic engagement, urban planning, architecture, and more. Now just a fun question about tools: what are some of your favorite tools for citizens and cities, and how might they be applied to the urban preservation agenda?
So I will home in on a few problems I think might be appropriate and some of the associated tools for the urban heritage space. One problem could be about collecting qualitative information: gathering public input in a meaningful but structured way. Oftentimes, when qualitative data is generated, it is done in a way that is not useful for analysis or policy-making.
So if we host a town meeting, and we get people to talk about what their preferences or priorities are or what they hold dear, how that information is captured and then used really matters.
Over the last few years, there have been quite a few applications that have been designed to gather and structure this type of qualitative information. One, called Textizen, is designed around SMS-based surveying. This company spun off from Code for America, and the idea was to break out of the confines of the traditional town hall structure to survey the public through advertisements in the built environment.
This could involve messaging on a poster to reach people while they are waiting for a bus or doing something else that does not occupy all of their attention. The idea is to meet people where they are and ask them about a particular policy, proposed change, planning decision, et cetera. That is one tool that many planning agencies use. Another tool that is novel in terms of qualitative data collection is CityVoice.
This is an open-source project that is, in many ways, similar to Textizen: it provides public polls and surveys, but through voice message as a primary medium. What should be here that is not? How should we improve this space for children to play in? Hearing a human voice is powerful. A recorded memo lends itself well to sticky qualitative information. Hearing a voicemail is a really easy way to engage immediately and naturally. The compelling technical advantage is that CityVoice then structures that data.
You receive a transcript and useful quantitative analytics on very qualitative information. Another area that may be of interest is regulation. Historic preservationists may be motivated to protect or stop certain policies or regulations that might impact the preservation of places that citizens care about.
Madison is a really useful tool for public comment on proposed legislation. This tool invites the public to comment on proposed legal language. It is an open forum used primarily to draft open data policies. Another important part of this work may be around storytelling and discovery. There are all sorts of ways to do that well, and there is plenty of out-of-the-box software that can help to tell a story. Much of how urban planners tell stories is through the use of GIS and online maps.
I have been pleased to see the field move into the development of narrative and context, placed strategically near and around data and maps. One tool many planners use is called Story Maps an Esri product.
They have made it really easy to build a website that involves data-driven maps and charts that offer narrative. It is easier than ever to publish data online and visualize that information in a chart or map.
Besides Esri the incumbent GIS software provider , there is CARTO, which is an emergent mapping platform and something that a relative novice can use and get up to speed really quickly on. Mapbox is a little bit more geared toward the expert cartographer or programmer; however, it is really sophisticated mapping software and relatively easy to learn.
The last opportunity is emergent data sources. Though we have discussed tools available to us in June , I want to emphasize that the landscape of new and existing tools will only continue to change and change rapidly. The real opportunity is to find and use emergent datasets. With the creation of new industries and with our economy changing, we are beginning to see how things like the gig economy and on-demand services like Uber, Airbnb, or Instacart are not only changing the way that the public uses the city but changing the information that we have to make decisions about the city.
Suddenly we have proprietary companies that are producing an immense amount of data that could be really powerful in shaping decisions about the places where we live. So whether it is using new sensors that are installed by municipal parks departments or historic preservation alliances to understand use or disuse of certain places, or simply using Google Street View to capture and archive what is there today that might not be there tomorrow, there is an enormous amount of opportunity in emergent data sources.
I would highly encourage preservationists to be comfortable with, be curious about, and try to anticipate what those data sources are that may be meaningful.
Get comfortable using APIs and using data so that we can extract meaning and value from new information feeds and use it for the goals that we have in urban heritage. Is there any other advice you would give to those working in urban heritage who want to start using these powerful tools and possible collaborations? In planning there is a natural avenue to get excited about technology: mapping and geospatial data.
With technology-savvy planners, one common progression I see is people who learned GIS in planning school and then later become comfortable with databases. GIS is a visualization layer on top of a database. Now there is a growing group of urban planners who are comfortable doing basic Structured Query Language commands. Many researchers are also comfortable using SQL commands because if you store a lot of data, you likely need to query it.
As planners build a competency around SQL or other basic database commands, they may begin to store those as functions that they want to run over and over again. Often this is just to save time. Planners get more curious about building a competency and an interest in programming. I would not say that every urban planner or every preservationist should become a programmer. But what I would advise, and what pedagogy is starting to encourage, is to develop a basic literacy so that if preservationists want to start using data in a serious way or need to use technology, they are literate enough to hire experts and embed them into their practice, whether that is at a university, in a private firm, or in the public sector.
The second bit of advice is to not be afraid of technology. Learning something new can be intimidating, but I would invite folks who feel that way to understand that this was once all new to us as well. There is an enormous amount that anyone can learn and that is accessible to everyone.
That is the power of the Internet. All of this information is available and accessible online for free. That is how the Internet was designed.
It is our Library of Alexandria. Not fearful. Consider this an invitation. The technologists who work in pursuit of the public interest are very invested in helping and in building your capacity, and we are excited about that. We want you to learn, and we need you to make sure our work is relevant and rooted in the expertise you bring to the table.
To many who work in the field of historic preservation or who study its concerns, it is a challenge to find and tap data sources in order to reexamine long-sought and protected building conservation programs and policies. We need data to examine what these policies have achieved, to identify and measure their outcomes or face their failings. But the data we need—while in some cases not so easy to acquire—is out there. To others in preservation and allied fields, however, the issue of the need for data takes on another dimension.
Access to essential and accurate information about people and their neighborhoods is critical to community-based preservation, planning, and policy activities that advance a more equitable and sustainable city. Without the ability to gather and understand some of the most basic data—from datasets that inform on land use questions to demographic information—community residents and other local stakeholders are at a major disadvantage when it comes to understanding the potential impacts of city-led plans for their communities.
Data is crucial to a broad range of community issues, including the denigration of community character and aesthetics due to new development and the loss of urban heritage due to other changes in the neighborhood. Despite the current proliferation of public data outlets and open data initiatives—and their potential to help communities assess their needs and assets and advocate for change—the reality is that resource-strapped, grassroots, community-based organizations often lack the capacity to collect, manage, analyze, and portray data.
Many are only on the receiving end of selective information about their own neighborhoods, rather than positioned to access and interpret that information—and propose ways to act on it—for themselves. The imbalance in who has the ability to assess a community asset or need is cause for concern. This imbalance is a significant factor in a number of inequities that rob communities of self-determination: government agencies and professionals feel—and therefore typically act out of—a sense of ownership over the information that is used in developing programs that will have an impact, whether positive or negative, on communities.
What, if anything, is being done to democratize data? The NDP addresses the challenge of data inaccessibility by removing the expensive barriers of proprietary software, hardware, and datasets and by minimizing the educational and training requirements often needed to master and use data. By placing the tools of participatory and equitable planning directly into the hands of community members, the NDP empowers them to plan for the future they want to see.
In thinking through these difficult issues, community advocates need greater access to information and resources in order to build their capacity and address the growing inequality observable in our city. As a well-established, respected, and trusted technical assistance provider, the Pratt Center is able to provide data-gathering, analysis, and visualization services, traditionally in the form of finished products such as illustrated reports and static maps.
But these services are still limited by the financial constraints of grassroots organizations and the diminishing role played by philanthropy in highly localized community advocacy efforts. What is unique about the NDP effort is that it includes a free community training series and online training videos that provide community groups and individual NDP users with skills to interpret and incorporate data as they develop responsive, impactful community-serving programs, design advocacy campaigns, and share critical narratives from their community.
Pratt Center trainings teach grassroots organizations how to access key datasets and how to visualize the data in maps for use in everything from funding proposals to community plans to public testimonies. In addition to empowering citizens to use public data, we are exploring ways to gather or create data on community assets to add to the portal. In addition to these important community assets, every New York City neighborhood has hundreds, if not thousands, of places of importance and value to neighborhood residents: cultural hubs like arts spaces, green markets, and ethnic grocery stores and restaurants; economic resources like nonprofit workforce centers and local businesses that extend credit to residents; historic and aesthetic assets such as locations of significant community events and architecturally distinguished buildings.
City agencies do not typically collect or provide data on either the more traditional or the more expansively defined community assets.
If they do—as in the case of religious institutions, for example—the data is limited to location and does not offer vital information such as the capacity the institution adds or the services it provides to its community. Essentially, public data on such assets does not speak to why they are assets; further, publicly accessible data for less traditional community assets simply does not exist. That lack handicaps the ability of communities to paint a full picture of the strengths and weaknesses of their neighborhoods and to accurately identify and evaluate the local resources they can marshal to support problem-solving and planning.
In our work with community-based organizations to gather community feedback about housing, environmental, or economic issues, intercept surveys have both engaged residents in conversations about the community and uncovered the lived experience that often defines and describes the strengths, challenges, and opportunities within a community as well as or better than public datasets can. When the data created by on-the-street surveys is digitized and analyzed, findings often illuminate local conditions in revealing and surprising ways.
While this data is useful for bringing locally generated facts to bear on city plans and for assisting communities to assess problems and identify their own solutions, it is both difficult to gather and seriously underutilized—the data is captured in spreadsheets and reports and perhaps is essential for negotiation with city agencies, but it is stored in formats that do not lend themselves to deeper or comparative analyses.
At the Pratt Center, we are starting to explore methods for layering this type of data into the NDP so that it can be shared among community groups struggling with the same issues. The NDP could also serve as a platform for comparative analyses over time so that Pratt and other citywide advocates can view conditions across the city when developing policy solutions.
This aspect of the NDP effort may have the most relevance for heritage conservation. Dozens of communities in New York City have conducted surveys of their historic and cultural built assets, and local, community-based historic preservation advocacy organizations are repositories of the data. Professional preservation researchers and consultants have assisted in the gathering of archival information, historical maps, and images and in the documenting of historic blocks and buildings.
But much, if not all, of this information is static: contained in privately held digital files or paper archives. Even when published in reports, the data gathered by groups across the city is not easily shared or updated, hampering its usefulness and in some cases its validity. Citizen preservation advocates would also benefit from tools and training that make it easier for them to research a broader range of physical conditions in their communities, beyond the basics of what was built and when.
Hausman ed. Marquis-Kyle and M. Peacock et al. Ricketts and A. Salamon ed. Schuster and J. David Throsby There are no affiliations available.
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