تجسم داده های جغرافیایی فضایی در علم، فن آوری و نوآوری

This paper provides a range of alternatives for analysts when dealing with geo-spatial data addressing activities in science, technology and innovation. There are two sets of theory which frame the debate concerning science, technology and innovation, and which drive further methodological advancements. The power of a good visualization in providing insight to decision-makers is well known. Visualizations complete a full cycle of decision-making involving analysis, design, action and then further monitoring. We advance the paper by assessing available geographic information in science and technology databases. The paper then systematically outlines current best practices and alternatives for visualizing geographic data. Different geographic map options provide different possibilities for the display of data. We show some of these options in the paper. Future research is needed into both the available tools and techniques, as well as a more in depth specification of the kinds of decision support needs that exist and have a geo-spatial component.

Over the last two decades, there has been a renewed and growing interest in the study of innovation at a regional level. This has been named ‘the new regional science’ [1] and [2]. Along a different line, there also has been a growing interest in the study of social and economic networks and their influence on innovation [3] and [4]. Separate from these developments in these respective scientific fields, there is an ever expanding amount of data becoming available to the analyst. In particular with the rapid rise of the internet over the last decade, researchers interested in innovation have gained access to a wide variety of new data sources. Moreover, more traditional data sources like science and patent databases have been improving the amount of data they provide, for example by adding detailed affiliation and funding data to their records. This paper explores how these new data sources can be of use to researchers studying innovation. The two research fields which frame the debate concerning science, technology and innovation drive further methodological advancements. In particular, the new regional science highlights the importance of the spatial character of innovation with its emphasis on physical distance, localized spillovers, and the local embeddedness of firms and other organizations. This thus necessitates that the researchers explicitly take into account the geospatial aspects of their data, which raises a wide variety of questions related to visualization and analysis. Similarly, the social and economic network literature is moving towards studying the dynamics of network formation over time, more granularity in the character of links between nodes, and accounting for the level of analysis [4]. This also necessitates additional data collection and analysis capabilities. This paper provides a range of alternatives for analysts when dealing with geo-spatial data addressing activities in science, technology and innovation (STI). We address the theoretical role of regions and districts in innovation policy. We then discuss an evolving body of analytical methods for addressing theory and delivering useful policy advice. These analytical methods may be implemented using a range of tools. We discuss open source scripting languages and libraries in this paper. We begin with a brief survey describing how and why geography shapes and structures innovation systems. From this survey we advance a set of requirements or needs for improved information systems for supporting policy. In Section 3, we confront the policy need with a survey of the available data. Section 4 details the design options available to analysts seeking to introduce visual and spatial quantities into their innovation analyses. Section 5 provides specific examples illustrating the potential range and applicability of visualization and geographical information support for innovation policy. Section 6 contains our concluding remarks, including a discussion on some of the major limitations of geo-visualization.

This paper started from two related observations. The first observation is the increasing availability of geospatial data in various science and technology databases. The second observation is that there are two divergent sets of theories on economic and innovative activities that do make claims related to geography. It is suggested that there is a need to study the heterogeneous character of local regions and the networked characteristics of innovation creation, diffusion, and utilization. The rise of computational support for map making in the form of GIS systems has altered the way in which maps are being conceptualized. A map can be understood as a spatial model and is composed of points, lines, and areas. Color coding, textures, and symbols can be used to further structure the map. Nowadays, there are a wide variety of tools and techniques available to the analysts to explore the geospatial component in addition to or in combination with standard science and technology indicators. These tools range from advanced GIS systems that have to be bought, to a wide variety of free open source solutions. These open source solutions contain fully fledged GIS systems, various programming languages that contain libraries for geo-visualization, and online tools like GeoCommons and Google earth. Various examples of the kinds of visualizations that can be made using these various tools have been shown. They illustrate both the variety of tools that can be used as well as the variety of visualizations that can be made. Given that a map is a spatial model [40] comparable to text [41] and [42], there are various interpretative issues associated with the use of maps. First, and most importantly, just as it is easy to lie with statistics [64], it is just as easy to lie with maps [43]. In handling and creating maps, it is crucial that the analyst is explicit on which data has been used, how it has been transformed and filtered, prior to generating the display. Second, maps can only show data, they do not provide information on cause–effect relations or on process outcome relations. This is a crucial point to be aware of, for cause–effect relations might be suggested by maps. However, the user of maps should be aware of the fact that different theoretical accounts can be compatible with the same map. That is, the cause–effect relations that a viewer might infer from a map are in part due to prior theoretical concepts and ideas on the part of the viewer. Third, since maps can only show data, a careful choice in the selection of data is necessary. For example, if one is interested in the emergence of networks, longitudinal data is needed. Moreover, the maps can only show the state of the network for a particular point in time, necessitating either the use of a movie or a series of maps to reveal the dynamics over time. Fourth, the same underlying data can produce different looking maps, depending on the choices made by the analyst. Together, this implies that it is advisable to produce a variety of different maps based on the same underlying data. The various new sources of geospatial data and the evolving tools for displaying this data have various implications for a scientist interested in regional systems of innovation and/or in social and economic networks. First, the ability to generate a variety of different maps can help in getting a more comprehensive overview of the data. Each map, through its visualization can reveal something slightly different about the underlying data. Second, the use of maps should not preclude the use of other methods and techniques. In particular, maps can be used as part of a first explorative analysis of a region and can help in designing targeted more in depth research actions, including surveys, case studies, or interviews. The increasing granularity offered by for example ISI and Scopus on affiliations of authors can further help in focusing and steering research. Third, the researchers should remain careful in distinguishing between the co-location of organizations, their local collaborations, and the wider embedding of these organizations in a region. In short, a high concentration of publishers in a geographic area does not imply a regional system of innovation. The increasing availability and use of geospatial data also has implications for the support of decision making. First, maps are just another visual display and as such can only inform and support decision makers, rather than replacing decision making. Moreover, the fact that the same data can be used to produce different maps and that the same map can produce different insights depending on prior commitments on the part of the viewer imply that great care is needed on the part of decision advisers and decision makers in the handling of maps. In this sense, maps are not different from other visualizations that can be used to display statistics and the same cautionary points about the use of statistics also apply to the use of maps. Future research is needed into available tools and techniques as a more in-depth specification of the kinds of decision support needs that exist and have a geo-spatial component. In light of these needs, targeted research into effective visualizations for these needs becomes possible. Moreover, this can pave the way for offering standard geo-visualization functionality in the software used by analysts.