geospatial data infrastructure: the problem of developing metadata
TRANSCRIPT
Geospatial Data Infrastructure: The Problem of Developing Metadata for Geoinformation in Africa
Dr. Tsehaie Woldai
International Institute for Geo-information Science & Earth Observation (ITC) Hengelosestraat 99
P.O.Box 6 7500 AA, Enschede
The Netherlands Tel:(+31)-53-4874279; Fax:(+31)-53-4874336
ABSTRACT We live in an age of instant information gratification, where increasingly the public in Africa views access to information as a key to their ability to understand and make the right decision. But as has been pointed out repeatedly, there is no guarantee that the quality of information is sufficient in theory or practice to guide decision making, and that the data as presented can be understood without establishing any context to it. Quite often, planning without facts is common; poor decision is familiar because the people who have to make it are ill informed or unaware of who holds the information or how to get hold of it. Even if they have identified what they want, the information cannot be cross- referenced and combined because the data does not use common references for geographical or administrative areas. The need to provide the Geographic Information System (GIS) community with fast, reliable, and up-to-date information has become a challenge for all geoinformation producers and users in Africa. These emphasize the need for geospatial data infrastructure (GDI) in Africa. Developing a proper metadata is the cornerstone of any GDI. In this paper, some of the problems envisaged into the development of the metadata in Africa are outlined and discussed. Keywords Geo-information, GIS, Geospatial Data Infrastructure, Africa, Metadata GEOSPATIAL INFORMATION (GI) AND MANAGEMENT IN AFRICA - INTRODUCTION In the last 30 or more years, several organizations in Africa have closely followed and participated in a number of geoinformation initiatives that has also swept many Developing Countries. Geoinformation is vital for improving the economic productivity of a country’s human and natural resources. Environmental and social benefits can also accrue from the use of geoinformation [1].
The African GI Legacy The Pre-1980 approaches towards remote sensing technology in Africa can be summarized as a) supply and b) technology Driven with ‘put the data in the computer, we will figure out later what to do with it’ and ‘stop updating the system, the project is over’ attitude [2]. This approach rarely met the needs of the end users. It also fell short from reaching the decision making process due to poor linkage with national institutions. There was a clear imbalance between the information produced and the national capacity to absorb and use it. Processing & Interpretation was done outside Africa and only the final product was delivered in analogue form. Most of the fieldwork data was never delivered and can hardly be traced. In countries like Kenya, Tanzania, Uganda, Ethiopia, Sudan for example as much as 90% [3] of the information collected has no geospatial reference. The datasets collected then does not conform to any set of quality standards. These imply that the datasets useful if combined, cannot be reproduced and its integration are at best difficult, and at worst impossible. From 1980 to 1990, proponent of the technology advocated for: demand driven, application oriented and problem Solving approaches. Unfortunately the data availability did not translate into greater use and greater use of data did not necessarily improve environmental sustainability. The demand driven approach was again a Piecemeal Approach -- the categories of users were not well identified, nor have their specific needs well surveyed [2]. In this period, many problem- and application-oriented studies were undertaken. • Maps in analogue format however, were the model of
supply of geosciences data and information. • Field photographs, interpretation results, laboratory
analysis, field notes, field data, unpublished maps and reports were poorly documented.
• Inconsistency, duplication and standardization problems persisted. Most analogue data were poorly georeferenced.
From 1990 to 1995, the expansion of GIS in different parts of Africa and the use of this technology by various organizations can be considered as encouraging. Organizations once confined to analogue map-making slowly migrated to digital map delivery. World-wide improvement in software, increased storage capacity and low hardware costs enabled GIS and associated technology on desktops in many parts of the continent. When looked critically however, its hitherto contribution to support development efforts in a coordinated way is still questionable. Nor is the amount and type of geo-data that made available to the users significant. This helps one at least to understand that the system is tied up with a number of critical problems that have hampered the possible application of GI in support of spatial decision support at various levels. GIS application in many of the African countries, was at its infancy stage. Even in those countries that look advancing to the corporate stage, their efforts are entangled with various impediments, of which lack of technical manpower was stern. • GIS, by most was used in the search for landuse,
agriculture, mineral resources, for scientific research, for land-management decision making, engineering design, for assessing geological disasters, for groundwater exploration, etc. The surveying methods however, remain largely mono-disciplinary and are focused on map production.
• Despite the complex task of acquiring data from the Earth surface by human observation, only a fraction of the knowledge acquired in the field are represented.
• Many of the hierarchically arranged part-whole and topological relationships between geospatial objects are not systematically captured. As a result only a fraction of the acquired knowledge was spatially represented, often in generalized and abstracted forms (Woldai & Schetselaar, 2002). This was because objects associated to a particular theme (e.g. geological units, soil units) are to variable extent covered by objects from another theme (e.g. vegetation), such that their delineation as coherent mapping units involves substantial interpretation of their continuation in the near-subsurface.
• Also there was no method to objectively classify geospatial objects and their relationships. The accumulated knowledge and experience of the surveyor bred within a particular theoretical school, inevitably results in subtle differences in weighing criteria to classify objects. This often results in a particular mapping style, which may further be affected by advancing geosciences theories and the evolving working hypothesis.
• Despite these aspects of subjectivity in natural resource or earth resources mapping and years of
effort that went into it, only one interpretation was published. This data usually was and is still only structured in the mental archives and models of the surveyor or investigators and therefore lost forever when he or she retires from the organization (Woldai & Schetselaar, 2002)).
The years 1995 to present are crucial to the development of GI in Africa. The advancement in Information Systems /Information Technology (IS/IT) has made possible the acquisition of myriad of information that once was unthinkable to acquire. Numerous geographic data were made available that are attributable to the growing of a number of related public and private institutions in most parts of the continent. Several technological innovations contributed to this endeavor: • The increase in spatial resolution of data acquired by
newly developed Earth orbiting sensors provides cost-effective access to framework data and mapping bases.
• The introduction of computers and microelectronic equipment and telecommunication services (which gave access to Internat facilities) in some has paved/ or is still paving the way for an avalanche of information, not only for scientific research, but also for providing insight to a broader public and for planning or for policy purposes. The possibilities to query, retrieve, process and analyze informations obtained via the Internat have aggrandised the interest of both data users and producers in some countries. The Internet has made it possible for end-users to more readily gather local geographic data germane to their own needs, draw data from library depositories elsewhere, develop the information products they need and use the data for decision making processes.
• Besides IS/IT, innovations and advances achieved in Geoinformatics, GIS technology and the concepts of managing the Geo-information Infrastructure (GII) have provided tremendous advantage to various application fields in general and regional development planning in particular. GIS technology includes a range of tools and methods that not only preserve spatial context, but include modeling operations that make use of spatial configuration, such as proximity and adjacency. In this regard, GIS has offered a great capability for analysing, integrating, modeling and presentations of spatial data, which in turn can be a good output for efficient and effectave plan formulation, evaluation as well as rational decision making.
OPPORTUNITIES AND CHALLENGES IN GEOSPATIAL DATA INFRASTRUCTURE (GDI) In most countries in Africa, long history of settlement, backward methods of agricultural practices, ever íncreasíng populatíon pressure coupled with recurrent drought have contributed to the devastating environmental
degradation, poverty and regional imbalances in socio-economy. These again threaten the racial harmony and social stability for long time, so to speak. In such grim situation, where population pressure outpaces agricultural production, farmland fragmentation is stern, the alarmmg rate of environmental degradation exacerbating the resource base, exerting efforts to reverse the situation is inescapable. This basically requires an efficient and effectave regional development planning system that can support development decision making. Efficiency of the planning system in turn needs accessible, affordable, adequate, accurate and timely spataal and non-spataal information. Having or getting a relatively reliable and up-to-date data basically forms the hub of any planning system. Such a demand from the regional planning domain and potential supply from the Information Technology (IT) put a room for injecting the idea of Geospatial Data Infrastructure (GDI) as a remedy and wheel towards good information management and governance. In its broadest terms the need for more data than anyone can afford alone, the need for data outside ones jurisdiction, redundant data collection efforts and assocíated high costs and an interest for efficient and effective use of information are the driving forces to call up on the application of Geospatial Data Infrastructure (GDI) in different application fields. The need to facilitate and promote the sharing of data once collected is at the heart of GDI concept [4]. In general therefore, if designed and implemented properly, GDI can provide a much better informatíon ground on which the regional development plans and subsequent effective decissions can be based on.
Geospatial Data Infrastructure (GDI) – Definition Geospatial Data Infrastructures (local, regional or national level) is defined to encompass the networked geospatial databases and data handling facilities, institutional, organizational, technological, human and economic resources that interact with one another and underpins the design, implementation and maintenance mechanisms that facilitate the standardization, sharing, access to and responsible use off geospatial data at affordable costs for a specific application domain or enterprise. [4]. Core data is that which is strategic in nature. It is often produced, maintained, published, distributed and safeguarded by National Survey Agencies [5, 4]. Its specification is best done in consultation with the user community. Specifically for core data, it has to do with determining the content and density of attribute values for a suitable and affordable dataset [5]. Its characteristic may also include being thematic level and poly-thematic, of national context and obtained directly from survey data or indirectly inferred by interpretation, integration or analysis. Moreover, by simplifying the definition, the possibility of implementing an infrastructure at different levels for a specific application domain has been enlightened which in turn tipped any interested body to start it simple and build it in steps. In Figure 1, the different GDI component parts and how different elements in it are linked to form a functioning system is presented. According to [6], all these components are parts of a system, working in an environment, where cultural, legal, financial and educational situations of the society have roles.
Figure1. A system view of the GDI component (modified after [6])
The reason For GDI In Africa In general, government at all levels (local, provincial, national) requires unrestricted and efficient access to reliable, timely, up to date fundamental geoinformation to govern. Who collects the (national) Geoinformation is a matter of efficiency and local circumstance. It could be the private sector under contract to government or government itself. In all cases government controls the standards and specifications, pays for the data development out of tax revenue and therefore remains the owner, which secures unrestricted access at all times. Governments have an obligation to facilitate access and promote the broadest possible application of fundamental Geoinformation, among other things by means of well-considered pricing policies. This includes an obligation to provide the description of the data to enable all users, including the private sector and civil society organizations to make a judgment about fitness for use. Geospatial Data Infrastructures (GDI) is the mechanisms through which this obligation can be met [4]. In the last two years we have seen several GDI initiatives in Africa [7, 8, 9, 10, 11, 12, 13]. The reasons behind such initiatives are straight forward: • To unlock the potential hidden in data and stimulate
economic activity, • To reduce duplication of effort among agencies • Make geographic data more accessible to the public by
encouraging the use of standards, • Improve quality and reduce costs related to GI • To facilitate value-added services by enabling
combination of data from multiple sources, and • To increase the benefits of using the wealth of
disintegrated data, and establish key partnership with states, cities, academia and the private sector to increase data availability.
For all these to happen the formulation of a good metadata is the cornerstone. The Need For Metadata The proper documentation that could answer questions regarding the content, quality, accessibility, and other characteristics of the geospatial data enforces the need for good metadata. Metadata are descriptions of dataset - a “Data about Data” [14, 15, 16]. A dataset is a convenient grouping of data, or individual observations, so that the summary of the information will be meaningful to prospective users [17]. It tries to answer the basic questions Who? What? When? Where? Why? And How? regarding every facet of the data that are being documented {http://biology.usgs.gov/]. Figure 2, shows a summary of the metadatabase content.
An international initiative to develop metadata standards is given by the International Organization for Standardization (ISO) [18]. It provides a schema for describing digital geographic datasets using a comprehensive set of mandatory and conditional metadata elements. These elements support four major uses: Discovery of data - Metadata elements selected to enable users to locate geospatial data and allow producers to advertise the availability of their data. Determining data fitness for use – Selected metadata elements help users determine if a dataset meets their needs by understanding the quality, accuracy, spatial and temporal extents, and the spatial reference system used. Data access - Metadata elements that describe how to access a desired dataset and transfer it to own site. Elements selected to provide the location of a dataset (e.g. through a URL) in addition to its size, format, price and restrictions on use. Use of data - Metadata elements selected to show users know how to process, apply, merge and overlay a particular dataset with others, as well as understanding the properties and limitations of the data. For harmonizing metadata standards, a minimum mandatory set of metadata items is recommended by ISO [18]. These are: Metadata Language Code. Metadata Characterset [default = "ISO 10646-2"]. Hierarchy Level Scope [default = "Dataset"]. Dataset Language Code, Dataset Characterset [default = "ISO 10646-2"]. Abstract, Category, Dataset Citation (Title & Date). Dataset Contact (Responsible Party Name/Organization & Responsibility Type). Important elements in the realization of the metadata include: • Proper Inventory of all geospatial datasets that exist
within various organizations. How do they exist? Georeferrenced? Are they standardized? Do they follow the same format? What are they based? How reliable are they?
• Set a clear catalog such as, bibliographic document for project documents to be held in library catalog or placed in a repository and cataloged following the established standards. The catalog provides structure and a means of access. The reputation of the data supplier or archive manager gives some assurance of quality; and
• Documentation of the data.
Figure 2. Example of metadatabase content [33]. EXPERIENCE AND IMPEDIMENTS TOWARDS THE DEVELOPMENT OF METADATA FOR GI IN AFRICA Over time, many governments and organizations in Africa have made major investments in collecting spatial data. The datasets collected are national resources that are fundamental to good decision–making. Despite the blessing drops some fruits, the following problems in developing metadata for GI can be outlined: Problems Associated With the Legacy Data • Most pre-1980 and even some 1990 onwards data are
only available in analogue paper media. The latter restricts details and volume of data, which can be put on a map. In most cases, few copies were made and as such were limited in circulation and use. Besides, they lacked proper geo-referencing.
• Inconsistency in the production of geographic information exists resulting in different coding and classification systems, different scaling, format and projections.
• Lack of official digital baseline maps -- the consequence of these is that the various datasets collected cannot be compared, integrated and modeled. Integrating data from different sources brings erroneous results. The overlay of rivers and topo-maps acquired by different agencies for example, often result in rivers crossing contour lines and even watershed boundaries. Similarly, city maps overlaid by river or road data often shows the river or the roads running over the buildings.
• Many of the fundamental datasets recorded in the field (e.g., field photographs, interpretation results, field notes, data collected from other studies) and in
laboratory (e.g., laboratory analysis) are either lost, unavailable or residing in inaccessible formats, such as notebooks or reports disaggregated from their positional attributes and fragmentarily distributed within the syntax of human language (Woldai & Schetselaar, 2002). Multiple use and reuse of field data was difficult as it is not readily available in suitable format. Each surveys data was treated separately while continuation of survey should facilitate densification of observation points or increase resources attribution.
• Standards are needed for mapping practices and for easy sharing of geospatial information. Unfortunately, most mapping practices followed no standards despite many incentives towards this goal. Getting countries or organizations to share their data is a critical challenge.
• Duplication of efforts, costly equipment and datasets emanating from stand-alone heterogeneous systems whereas the other side is suffering from dearth of information is still there.
• Security of the data holdings is still inadequate. All resources are stored in central location such that recovery in case of calamity would be difficult. Besides, enormous amount of original documents have been destroyed due to poor storage facilities or are in the shelves of various Ministers or high officials unavailable to the wider user communities.
• Minimal data exchange/sharing. Improved analysis and decision making-as well as the cost-effective use of relatively expensive data-must spring from genuine cooperation and a willingness to share results. Although paper maps are usually available in many African countries, reluctance to share digital data and
particularly digital maps is common. To date, the only widely available digital maps for Africa are at 1:1 000 000. But analysts need larger scale-that is, more detailed-maps and data to assess environmental conditions and trends and to propose solutions to environmental degradation at the national and sub-national levels.
Policy and Coordination Problems • Lack of meaningful co-ordination among ministries,
organizations and agencies prevails as the neglected Achilles heel to the regional development planning effort of much Governments In Africa. Institutional coordination in most countries is still absent. Many researchers and users of the GIS technology suffer from isolation.
• Accountability and transparency was lacking on the part of the employees. This makes employees view the data they collect as personal property. As a consequence data and information is lost due to poor data management policies.
The problems described above are part of the daunting problems facing most of the African countries with some the idea of geoinformation achieving far from expectations. A well-structured and integrated geospatial and socio-economic information is still missing. What To Do With the Legacy Data? Most of the legacy data collected so far in Africa are either in analogue or in digital form. The raw analogue data have to be converted to digital source and from the latter products and services could be derived through abstraction, processing, plotting and visualization. Valid interpretation across community boundaries is likely to depend largely on the background knowledge of the human interpreter. This is not available, nor likely to become available, to the computer. Language is a powerful tool to reconcile different viewpoints, and a basic for communicating background knowledge both of large concepts and of details of a single object [20]. Written explanations therefore, are needed in close association with spatial and data objects at every level of details [21]. The actual challenges fuelled by an increasing interest to use and work with a number of GI sources call for an urgent standardization effort as an inescapable precondition. Integrating data from various sources is hardly possible without the necessary standards that would harmonize the systems in a meaningful way. One thing is clear -- a major problem in the setting of the metadata, is the issue of money; the cost to convert the existing collection of data to conform to the standard to be adopted. Standardization of data is very serious problem. For different users to cooperate and achieve their objectives there needs to be a common working ground to stand on.
The complexity of spatial data handling, the presence of diversified meaning to similar features or similar meanings to diverse features requires some sort of arrangement that can enable interested bodies to meet their objectives. The information society in Africa, therefore, has to have standards in various aspects of GI and GI related activities to successfully communicate and exploit the blessing of technology. The issue of standardization covers the central position in an attempt to implement any GDI programme. In this regard, according to Aalders [22], standardization can take place at different levels: • (Inter)nationa level for generic agreement between
parties; • Branch level for agreements between institutions of
their specific common application and data; • Internal institutional level, where interval procesces
are aligned through data and procedure definitions. Standardization is not an easy job. It is a tedious and time-consuming task. It requires decision on how the application sector classifies (or names) the geographic features of its interest, while taking into account the evolving standards in the field at global, regional or national levels [23]. Because information technology bridges nationaland disciplinary boundaries, standards must be consistent with those in related fields. Close collaboration with a range of other organizations is therefore essential. In the international level two major standardisation efforts are recognised that are focusing on the field of GI, by Comite Europeen de Normalisation (CEN)-CEN/TC 287 for European level and International Standards Organisation (ISO)- ISO/TC 211 to be applied at the global level. Another most widely known standard for metadata is the Content Standards for Digital Geospatial Metadata (CSDGM) adopted by the Federal Geographic Data Committee (FGDC) of the United States of Geological Survey. The CSDGM specify the information content of the metadata for a set of digital spatial data. The purpose of the content standards is to provide a common set of terminology and definitions for documentation of spatial data [24]. What To Do When There Is No/or Limited Legacy Data In those countries of Africa who have limited or no legacy data and where the availability of digital data is still a major issue, users of GI have low expectations, and are happy with any data and metadata they find. The data they use then are not a reflection of what is available but rather what they need. They have the possibility to inject GDI at an early stage. Besides, the metadata standards developed nowadays by others could with careful adjustments be used to serve their corporate interest. With these groups of GDI users, as the users become more experienced and the datasets available more abundant, then the demand will grow for more detailed, accurate, and up-to-date metadata,
as well as for an increasing number of datasets. More experience about the datasets that exist will stimulate interest in finding more information at national and sub-national level to obtain more timely, geographically detailed, and thematically relevant data. Two major developments will foster the changes in focus: Development In Earth Observation Almost 30 years after the first Earth Observation Satellite (EOS) went to orbit, optical and microwave remote sensing such as, NASA Landsat MSS/Thematic Mapper, SPOT, IRS, ERS and JERS still remain the most popular and the most used remotely sensed data in many scientific researches and productions in Africa. The number of scientific publications and maps covering many applications, although as mentioned above in disintegrated fashion, outweighs the purpose of this paper. New Developments. Earth observation in the past was highly mono-sensor, present and future. A glance at the present activities of the major players in the Earth observation field from the technological perspective, NASA, ESA, etc. learns that long term missions comprise of complementary but far better sensor quality, higher spectral/spatial resolution and better calibration. Potential applications for one-meter satellite imagery, such as IKONOS, in a GIS environment are limitless. The imagery can serve as detailed base map upon which thematic map layers can be overlaid, or it can be used as an up-to-date data source from which various geological features, land cover, soil degradation, hydrology and other activities related to elevation features are extracted to populate multiple GIS layers [25]. With the operational use of sensors with higher spectral resolutions, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), the quantification of the composition of earth surface materials becomes feasible. ASTER data also serve to obtain maps of land surface temperature, emissivity, reflectance and elevation. One of the most important aspects is that ASTER data is currently accessible (so far, free of charge) to the public; a trend unheard in space data acquisition. The European Space Agency (ESA) Envisat mission involves a laser altimeter, a SAR interferometry system (ASAR), an imaging spectrometer (MERIS) etc. An important issue within the context of ESA is the Global Monitoring for Environment and Security (GMES; part of a larger framework of three such monitoring systems, the G3OS) initiative. Data collected by airborne spectrometers have already demonstrated that it is possible to identify certain types of exposed mineralogy, to label the minerals present and to determine the fractions of the minerals occurring in small,
sub-pixel units. Thus, provided that the non-uniqueness in the solutions obtained from spectral unmixing methods can be constrained, a new type of maps, indicating "mineral abundance at surface", can now be made (Woldai & Schetselaar, 2002). Pioneering studies so far carried out using SAR interferometry (InSAR) have already being earmarked as a new development in understanding our earth and its dynamics. InSAR can provide with unprecedented precision, high-resolution images of earthquake-prone areas, topographic data (DTM's using stereopairs of radar images with differing viewing angles) and a map of coseismic deformation generated by an earthquake. The precise monitoring of surface deformation allows accurate zoning, mapping and prediction of volcanic eruptions, landslides and ground subsidence. Differential interferrometry allows one to measure surface movements with sensitivity of the order of a few centimeters over large surfaces [26]. In most African countries accurate topographic base map and digital terrain model (DTM) of the area under investigation is missing [27]. In any GIS work therefore, this problem remains a handicap. An exciting development towards solving this acute problem is envisaged from the new Shuttle Radar Topographic Mapping (SRTM) acquired by Space Shuttle Endeavour in February 2001. The SRTM instrument captured allows one to create very detailed topographic maps of the Earth's surface using interferometry. This radar system gathered data that will result in the most accurate and complete topographic map of the Earth's surface that has ever been assembled. Already immense data covering most of Africa is processed open to African researchers and end users to accurately obtain knowledge of the shape and height of the land, and to assess: flood, soil degradation, deforestation and reforestation, landscape changes in Africa (Woldai, 2002a). Future Trends. Turning to the future, spaceborne remote sensing offers a more challenging task to the geoscientific community. Three new data types and their technologies are about to become a commonplace. These include: • Multi-attribute imaging radars having multiple
frequencies and polarizations. • Highly detailed digital elevation models (DEM) of
anywhere in the world, allowing sophisticated modeling and visualization of the landscape and processes acting on it.
• Imaging spectrometry or hyperspectral imaging systems, such as the planned Australia’s ARIES-1, using sensors with 100's of spectral bands providing spectroscopy and compositional information about earth surface materials based on the principles of spectroscopy. This brings the exciting new
possibilities of not just discriminating the materials but actually identifying it and putting a label to the major mineral components present in every pixel of an image.
Development In GIS Technology Modern image processing facilities and methodologies of digitally formatted data has revolutionized the interpretation of large-scale planetary landscape scenes. Personal computers can nowadays handle large amounts of remote sensing data, providing access to universities, resource-responsible agencies, small environmental companies, and even individuals. From the perspective of the user data integration is one of the strongest element of GIS. The zonation, integration and modeling of various geoscientific data should supply planners and decision-makers with adequate and understandable information within a relatively short period of time. Desktop-GIS with full-fletched image processing capabilities is now being used for a wide variety of applications ranging from environmental assessment to marketing. For mineral exploration desktop-GIS provides the means to statistically analyze and classify geochemical data, enhance geophysical images, determine spatial relationships between features, and produce charts, tables and maps to report the analysis. Pattern recognition, feature extraction, texture analysis by mathematical morphology, and a variety of unsupervised and supervised classification techniques (including neural nets) represent techniques of information extraction increasingly used in the earth sciences. Integration modeling by favourability functions has provided the mathematical framework for predictive spatial data analysis, a developing but still relatively unexploited area of GIS analysis [28]. Computerized field data capture using GPS, palm-top and laptop computers, field spectrometers and other field sensors, are becoming critical inputs to systematic spatial data analysis of maps and images. They anchor to ground truth much of the pre-processing of images to obtain spatially and spectrally corrected images for further processing. Digital resources mapping applications have also rapidly evolved over the years. Data that are digitally input directly in the field is preferable because they reduce error and save time in the data processing and interpretation stage. The importance of digitizing information directly in
the field to reduce error and duplicity in the map production process cannot be underestimated. There have been several attempts to make digital field mapping software since the mid 1980’s [29, 30]. The mapping tools include a pen stylus, which serves the purpose of a full set of colour pencils in combination with digital topographic maps or colour ortho-photos on the screen of a portable computer for positioning. Additional digital tools include sub-meter accuracy GPS, laser range finders, digital cameras and visible/infrared (IR) spectrometers [31]. Knowledge About What Information Exists For geospatial data to meet the stated objectives and purposes, it has to be organized in such a way that it can handle the required data sets, rules, regulations and related aspects. In any application field, the types of shareable data have to be known and be identified to apply it. Two classes of core products (Figure 3) outline the different categories of spatial data that can form the metadata structure. These include: Foundation data are baseline data in nature, providing essential base information upon which other organizations can create datasets by overlaying with other data. These include: data that can show geographic reference systems, topographic data sets that can serve as geometric references, common codes, etc on which other thematic data sets can be built on. Specific products are framework and application-specific data. Several government agencies and /or industry groups require a consistent national coverage in order to achieve their corporate objectives and responsibilities. Framework data include theme specific data sets such as, land use, land cover, vegetation, etc. Though not as extensively as the foundation data sets, they are also required by many organizations to produce other derived data sets, which are important for spatial decision making. To the application-specific data include data collected for a very specific duty, and particular application area, like pollution measurements, water chemistry, etc. [23]. The latter, concludes that data sharing opportunities decrease from Foundation, Framework, to Application data sets in the respective order. Therefore, identifying the most sharable data is one area of concern while dealing with metadata development. Besides, identifying the agencies or organization mandated or not to supply these categories of data is the core of the metadata initiative.
Figure 2 Categories of spatial data that can form the metadata structure [4]. Both products retain a characteristic of being standard in production. With respect to processing level, specific products may require a higher level of analysis of the basic data or special presentation. For each domain a set of basic and specific products may be defined. Value added is non-standard customized product targeting a specific user group. Commissioned products are the property of the commissioning customer with user-defined specifications under special funded programs. Knowledge on Where Geoinformation Exists There are two geoinformation users in Africa: Those which produce the foundation data; basic spatial and non-spatial information and, those which produce theme specific geoinformation. In the first instance, the basic GI producers are those that are mandated at the national level for collecting, processing and disseminating GI and other related data at large. These include land administration authorities, Surveying and mapping authorities, (municipal) planning departments, hydrological and topographic surveys; organizations traditionally involved in the production of Geoinformation data in the form of maps and reports. These organizations provide data that governments need in order to govern. Their task is tied to the foundation data and as such deal with: the national positioning system, the national digital topographic template, digital elevation model, geographic names, administrative units, common codes, etc. It is an open secret that the national Geodetic/Topographic Surveying organization assuming monopoly, are bestowed with the
task of producing the baseline data that can serve most other GI productions. Administrative boundaries are often produced and maintained by the national statistical organization. The fact that such organizations are successful in satisfying the growing demand for simple and manageable GI base information is however, questionable. Except for South Africa and to a certain extent countries like Côte d’Ivoiré and Ethiopia, Surveying and Mapping Organizations have failed to supply digital GI products, which most other organizations and individual users can easily use it. The problem is manifold. On the one hand, in countries like Benin, Cameroon, and Congo and to a certain extent, Botswana, Ethiopia, Tanzania and Zambia, the baseline data can't satisfy the growing demand for digital base information despite having the legal rights and cover to monopolize the activity. On a second thought, most current products, mostly maps, are not even geo-referenced and as such not convenient for easy application. Moreover, the correctness of the existing topo-maps are questionable since updating the produced analogue outputs are difficult while some areas of their country are not yet covered totally. This really put a big hole in their usefulness and support for development decisions. The case with the cadastral offices or Statistic Administrations is not different, although disseminating the indicated products is not their prime objective. Surprisingly, if anyone wants to carry duties at a very lower administrative level the only possible data one can get is mostly the boundary information. Still the quality,
especially the positional accuracy remains displeasing. What is more astonishing is that most such organizations in Africa haven’t extended their services outside the capital cities and their environs. In fact, most of the organizations surveyed within the South African Development Communities (SADC) have no branches at the regional levels. One can imagine how long could it take to cover a single region with only the national set up. Moreover, it is hardly possible for them to focus on GI products that can be supportive for regional development endeavors. It is not only the question of coverage and focus but if one wants to use the already available GI baseline data, one has to go as far as to the capital of the country where the main offices are located. In other words, this has to do with the fragmented chain of command and most of all to do with the weak accessibility to their products in that one needs to reach them physically from whatever location might one be. To the framework and theme specific Geo-data producers’ category belong ministerial offices, authorities, commissions and project offices. Included in this category are civil society organizations such as community networks for disaster prevention, environmental control groups and local education and knowledge institutions Most of these institutions use the baseline information from the various Surveying & Mapping Organizations, Hydrological Authorities, Meteorological Institutions, Statistical Administrations, etc. to come up with their own value-added outputs. Depending upon their thematic responsibility (e.g., geology, landuse, land cover, vegetation, etc.), they produce and use geo-data of different nature on an ad-hoc basis (rather than taken as a regular duty) primarily to fulfill their jurisdictional. Unlike the GI basic users, most of these institutions, their bureaus and departments have a chance of getting more up to date data on their subject. Confined to their institutional mandates and concentrated on meeting their own internal information need, they have no mechanism to facilitate data access to other interested users. Therefore, unless it is a luckily informed user, no one can easily know what type of data they have, no matter how valuable their data are. GI IMPLEMENTATION PROBLEM Contrary to past experience where data becomes an issue to introduce a technology, in this paper emphasis is primarily laid to the will of Governments first before arguing whether the introduction of GDI is important or a country should strive towards a proper metadata or not. Past GI development in Africa is a lesson to the future. When it comes to GI technology in Africa, the writer in his 20 years of experience in the continent has seen Governments accepting new initiatives without analyzing its consequences. In this respect, organizations, institutions, centers blossomed when money from outside (e.g., donor country, World Bank, NGO’s, etc) prevailed
and whether when money dried serving nobody. Mini GI empires developed which competed and misused the scarce resources. First and foremost, if Africa is to benefit from the GDI initiatives, and if geospatial data are to be properly inventoried, catalogued, documented, standardized, updated and shared without restrictions indefinitely it all boils to:
Political will Political will Political will
When there is a will there is a way. The writer believes that the application of remote sensing and GIS in Africa didn’t succeeded the way it should be because of the absence of a firm political stand on the side of governments. After all, the technology is a tool that will facilitate the mechanism for collecting and processing the data. Metadata standards are already devised by several organizations that can serve as a basis. GDI development and proper metadata set-up needs a champion at the highest political level [23]. Mere involvement without visible and concrete commitment that allows Africa to derive benefits from the GDI initiative is not enough. From the experience of the past 30 years and those of other continents, African decision making bodies have great challenge and responsibilities as leaders of their respective countries, if the current gains in GDI are to be sustained. There is no guarantee that the technology is going to benefit society unless there is a political will at the highest echelon of Governments fully committed to: • Take the initiative as its own and involve its citizens. • Invest money (partially or fully); supply the necessary
logistics with or without outside support for a long time to come.
• Invest in its people (Education, training and awareness building in centers of higher education and aiming at the critical mass is the solution)
• Put policy/legislation/etc. to enforce any activities inside
• Share GI data. Without these issue in place, the GDI initiative is doomed to fail. Proponent of GDI will stress more to the technology or to the data part to emphasize their case. The writer is of the opinion that there are many opportunities and challenges (see above) available to compensate that even if a country starts with nothing. The implementation of a proper metadata in Africa requires a solid infrastructure based on policy, guidelines and administrative arrangements, technical standards, fundamental datasets, and a means by which spatial data is made accessible to the community. Besides the needs to physical technology results, there are complicated issues dealing with changing pre-set mentalities to some form of working environment. To work together in harmony and promote responsible use, providers, users and
coordinating bodies in the government and private sector need a stable institutional framework. These are policies, guidelines and administrative arrangements for the working of the infrastructure. It needs much greater effort to diffuse new way of tackling problems than possessing the physical gadgets that are relevant for it. Economic Issues This is to do with how to justify in the political circles and in economics terms government investments in the implementation and running/maintenance of the Infrastructure [23]. Especially in countries where almost all users and providers (potential stakeholders) are government and government related organisations and where the credibility and justification of production and dissemination programs of geospatial information against other programs that compete for the same limited budgets is necessary, the role of the political architects form the hub of the inter-organisational coordination efforts. In general, in drawing proper policy instruments, facilitating grounds for awareness creations, and in lubricating the activity with the necessary financial input, the rule of higher officials and governors is inescapable. Past experience in GI technology in Africa has clearly demonstrated several pitifalls: • In nearly all-African countries, geoinformation
activities are planned, implemented and monitored by different arms of Government (Ministry of Agriculture, Mining and Energy, Directorate of Surveying and Mapping, to name a few). They all specialize in various production aspects of surveying and mapping has their own topographic & mapping facilities on piecemeal basis fragmented from the wider national issues. Emerging RS capabilities spawned uncontrollable new agencies also, whose product have been poorly integrated with existing ones. The consequence of these is evident in the overlay of efforts, duplication of costly equipment and satellite data, which often induce competitions of scarce human and financial resources.
• Short-term financial and macroeconomic issues took precedence over long-term renewable resources. So far as money was coming from somewhere the technology flurished otherwise there was no long term committments to the technology. Applications were customized to support specific decision-making process. As a result organizational focus remains by nature very narrow.
Metadata development is not only limited to the establishment of physical structures bot also includes issues of data collection, delivery, system maintenance, which encompass various human and organizational elements. Every aspect and each step needs enormous amount of financial and material resource. A substantial proportion of the initial cost has to come from the Governments. Preparation of the required data itself is an
expensive duty. In principle, all the benefits have to be put in some sort of monetary scale to justify the project. The problem at point is, some of the stated benefits are hardly possible to put them on economie scale. It is not only the non-quantifiable benefits and costs that usually make cost-benefit-analysis complex, bot its application in different locations/countries can also add fuel to the issue. Anyway, for African countries the cost can be astronomic and prohibitive unless approached in a stepwise fashion..
Internal And External/Social Culture Issues As technology finds practical use, economic, political, social and ethical accountability become issues that determine basic designs of database and collection and processing of the geographic information. Fears that arise due to introduction of technology that would result in opposition need to be addressed internally and externally. As new systems or modifications to the existing ones may cause restructuring, giving additional tasks or the reverse, concern for such an aspect has due point.There is bound to be changes in organizational structures and power centers. In the past, this has always created a wave of protests in many organizations involved in geoinformation technology in Africa. IF this new initiative is to succeed in Africa, then a great commitment is required on the part of the top management in effecting the changes. Organizational Arrangements. The success of creating an efficient and proper metadata for a country will depend upon different bodies that are providing and using data and information. The outputs from a number of organisations could be in a varying scale, area and quality. Unlike past African experience, when different specialised expertise come to work together in an environment of such disparities, among all things, a common ground has to be laid, on which every stakeholder can base itself on, and bound to a commonly agreed standard and procedure as well as arrangements. Roles of each participating organisation in the common endeavour also have to be specified since the effort of establishing and subsequent maintenance of a metadata requires genuine partnership in one way or another. Institutional Issues, Policies, Regulations And Guidelines. As the need for metadata use in Africa increase, the institutional problems surrounding it become all the more pressing. Setting the country metadatabase will bring together different actors for the common purpose to serve each other in a different environment not comparable to the analogue environment. The success will depend on proper institutional arrangements. These are not an `easy to deal' matters. All aspects of organisational arrangements, policy issues, financing (economical) and political aspects are included in it to make the system work effectively to the desired goal. To work in harmony and promote responsible use, providers, users and coordinating bodies in the government and private sector need a stable institutional framework is necessary.
Policies are plans of action by the government as to what is adopted. Regulations deal primarily with the place of public data producers in the machinery of Governments. Guidelines deal with general rules or instructions. The roles of all stakeholders (private and public) in the entire development, and maintenance of the system as well as their responsibility in data collection, dispatching and access to data have to be specified. The use of spatial information as a corporate resource implies an understanding of who owns the data and what rights can and should be retained over their use [32]. As it stands, in most African countries getting baseline data or theme specific data from specific organizations is a daunting task. This is particularly so for those coming from outside government institutions. Thematic datasets, reports or seminar proceedings are in most cases classified as ‘state secrets’ adoring the shelves of some officials, making it hard for any outsider, let alone one asking with legal documents to fetch the data out of their pocket. May be for most, the absence of any regulation how once produced data can be transferred to the third body served as a good cover. In a nutshell, the constrained cooperation is not always attributed to lack of absence of clear directives or regulations, but sometimes, even in most of the cases, it is affected due to serious vision crunch towards public right for government information, to put it mildly. Pricing Policy Particularly important to the whole initiative is the pricing policy. This is an unknown terrain to most African GI communities. Pricing levels that are product/service specification e.g. access, customization or use restrictions will determine cost conditions. In fact questions like, would data be freely given to any citizen? Would there be no restrictions placed on its re-use other than to gain permission from the custodian to copy and use the data in commercial products, acknowledge copyright in the data and take responsibility of liability from derived products. Should there be fees to cover marginal costs (staff costs, material consumed, accounting, postage and other direct distribution costs)? In this section one need to make one basic remark. Both at the national and the regional levels the role of the private sector in producing Geoinformation is almost nil. Nor is there a strong organization whose main objective is linked with GI. The role of the private sector so far in relation to GI is limited to supply of hardware and software and related training facilities to some extent. Manpower Development Investment in training people to use the technology, to collect, manipulate, and interpret geoinformation often receives leap-service. African policymakers need to be engaged in the process through awareness training,
briefings, and policy dialogue. Retaining technical expertise should be a priority within African institutions using geoinformation to drive planning and decision-making at local, national, and sub-regional levels [1]. Manpower development is the cornerstone of GDI and there is no alternative to it. Publicity Mechanism There is no publicity mechanism to report what is available or to conduct a customer’s survey to know their needs. In the case of the Ethiopian Mapping Authority (EMA), Surveying General of Zimbabwe, and the Mines and Geological department of Kenya for example, Users have to travel personally to these organizations to get help or report any matters they think are of interest to their tasks. A well-structured metadatabase need publicity so that people are aware of what is available? Where? And how? CONCLUSION Different Nations in Africa, stratified by their degree of development, have different point of view of how to use and manage their resources. In its broadest term, the different Information Communities have different meaning to IT, and for that reason, have different approaches of producing, accessing and managing Geoinformation at the national level. They operate on a stand-alone, extreme sectoral basis where they lack inter- as well as intra-organizational links. A National Geographic Information Community is composed of organizations and loosely connected users, e.g., cartography community, cadastral, geology, agriculture, natural resources, etc. all working in isolation, poorly linked and duplicating their efforts. With jurisdiction sentiments and data secrecy culture prevailing in the countries, it is hardly possibly to consider the existing systems and approaches adopted by the various communities as reliable sources that can channel information to the regional planning domain. This situation put a great impediment on the nation's effort to tackle development problems in a systematic and reliable spatial information foundation. Efficiency of the planning system needs accessible, affordable, adequate, accurate and timely spatial and non-spatial information. Information sharing in turn needs an efficient route that can give possible access to the needy. The potential route can be achieved and accessed through the implementation of a well structured GDI as a remedy and wheel towards good information management and governance. The development of a proper metadata in a GDI environment however is not without problems. Although Africa does not suffer from information “glut” yet: • The legacy database available suffers from
inconsistency, duplication and lack of official and well-structured digital baseline maps.
• There is no mechanism to understand the quality, accuracy, spatial and temporal extents, and the spatial
reference system used. Determining the data fitness for use is not in-place.
• The complexity of spatial data handling, the presence of diversified meaning to similar features or similar meanings to diverse features requires some sort of arrangement that can enable various interested users to meet their objectives. Standardization of data is a serious problem.
• The geospatial data available are mostly in analog paper media with security of data holdings still inadequate.
• Reluctant to share data and particularly digital maps is common.
• There is no center or mechanism to know where the framework and application-specific data are? Nor is it clearly visible to know who owns it or what has one to do to get it.
• Most of all, the implementation of a proper metadata in Africa requires a political will at the highest echelon of Governments; a solid infrastructure based on policy, guidelines and administrative arrangements, technical standards, fundamental datasets, and a means by which spatial data is made accessible to the community. Without such commitment, the past thirty years of IT in Africa should be the lesson and a proof that such initiative is doomed to fail.
REFERENCES 1. Gavin, E.J.O. (2002). Draft For Review: Geo-Information
Supports Decision-Making In Africa - An EIS-AFRICA Position Paper, EIS Africa, pp.10.
2. Woldai, Tsehaie (2002a). Invited Paper: The Status of Environmental Information Systems in Sub-Saharan Africa, Developments and Technology Transfer in Geomatics for Environmental and Resource Management, ISPRS Commission VI Workshop, Dares Selaam, Tanzania
3. Woldai, T., 1995, Survey and mapping in Sub-Saharan Africa – Which way further? Invited paper, UN-Outer Space Affairs Division (OSAD), United Nations Regional Conference, Senegal, West Africa
4. Groot, R. and McLaughlin, J., (editors), 2000, Geospatial Data Infrastructure: Concepts, cases and good practice. Oxford University press.
5. Groot, R., 1998, The role of national mapping agencies in the development of National Spatial Data Infrastructure. Paper presented to the International Conference of spatial information Science and Technology in Wuhan
6. Sharifi, A. & Groot, R. (1993). GIS Infrastructure: An Essential Element of Successful Development and Transfer of GIS Technology. Paper presented to the 14th Asian Conference on Remote Sensing (ACRS), 10-17th October 1993. Tehran.
7. Bassolé, A., Brunner, J., Tunstall, D. 2001. GIS: Supporting Environmental Planning and Management in West Africa. A
Report of the Joint USAID/World Resources Institute Information Working Group for Africa.
8. Ezigbalike D., S. Faïz, Q.C. Selebalo, S. Z. Zhou (2000): "Spatial data Infrastructures: Is Africa Ready?” Fourth Spatial Data Infrastructure Conference, GSDI4, Cape Town, South Africa.
9. FGDC, 1997. Building the National Spatial Data Infrastructure, Newsletter of the Federal Geographic Data Committee, No 1, Reston, USA.
10. UN-ECA, 2001. The future orientation of geoinformation activities in Africa. A Position Paper, Development Information Services Division (DISD), United National Economic Commission for Africa, Addis Ababa, Ethiopia
11. Gavin, E.J.O., Gyamfi-Aidoo, J. 2001. Environmental Information Systems Development in Sub-Saharan Africa: approaches, lessons and challenges. EIS-AFRICA.
12. Global Spatial Data Infrastructure: http://www.gsdi.org
13. Environmental Information Systems Africa: http://www.eis-africa.org/
14. ANZLIC (1996). ANZLIC Guidelines: Core Metadata Elements Version 1. Policy document of ANZLIC Working Group on Metadata.
15. -----------(1997). Core Metadata Elements for Land and Geographic Directories in Australia and New Zealand, The Australian New Zealand Land Information Council.
16. Kildow (1996). The value of Metadata (a NSDI Policy document), U.S. Fisheries and Wildlife Service.
17. British Geological Survey Home Website: http://www.bgs.ac.uk/dfid-kar-geoscience/r7199/management/data_res.htm)
18. International Organization of Standarization Home page http://www.iso.org/iso/en/ISOOnline.frontpage
19. British Geological Survey Home Website: http://www.bgs.ac.uk/dfid-kar-geoscience/r7199/management/dis_meta.htm assessed 14/1/2002)
20. Kent, W. (1978). Data and Reality, North-Holland Publishing Company, Amsterdam, 211pp.
21. Loudon, T.V. (2000). Geoscience after IT, Part M. Business requirements drive the information system, and provide coherent frameworks. Epilog, Computer & Geosciences, 26, Elsevier Science Ltd. Pp. A123-A132
22. Aalders, H. (1999). Standards for GII. In: J. Crompvoets, U. Pijnenborg & A. Bregt (1999) Spatial Datasets. Reader 1999-2000, WAU.
23. Groot, R. (1997). Spatial Data Infrastructure (SDI) for Sustainable Land Management, ITC Journal, 1997-3/4.
24. FGDC (1998). FGDC Newsletter, Spring 1998, Vol. 2, No. 1.
25. Woldai, Tsehaie and Schetselaar, Ernst (2002). Design And Implementation Of “Factual” Databases To Support GIS/RS Analyses of Earth Systems For Civil Society, Developments and Technology Transfer in Geomatics for Environmental and Resource Management, ISPRS Commission VI Workshop, pp. 117-124, Dares Selaam, Tanzania
26. Massonnet, D., Rossi, M., Carmona, C., Adragna, F., Peltzer, G., Feigl, K. & Rabaute, T., 1993. The displacement field of the Landers earthquake mapped by radar interferometry. Nature: 364, 138-142.
27. Woldai, T. (2001). Application of remotely sensed data & GIS in assessing the impact of mining activities on the environment, Proceedings – 17th International Mining Congress & exhibition of Turkey. Ed.: E. Unal, B. Ůnver & E. Tercam, IMCET 2001, Ankara, Turkey, pp.75-84.
28. Chung, C.F. and Fabbri, A.G, 1993. The representation of geoscience information for data integration. Nonrenewable Resources 2, 159-169.
29. Brodaric, B. and Fyon, J.A., 1989, OGS Fieldlog: a microcomputer-based methodology to store, process and display map-related data. Ontario Geological Survey, Open File report 5709, 73 pp.
30. Brimhall, George, 1998, Direct Digital Field Mapping Using Pen-Based PC Computers Supported by Differential Global Positioning Systems and Laser Range Finders: Geological Society of America Annual Meeting, Abstracts with Program, v.30 (7), p. A-256, http://www.geosociety.org/cgi-bin/annual-meeting-abstracts-query.pl.
31. Kramer, J.H., 2000, Digital Mapping Systems for Field Data Collection. Kramer, J. H., 2000, Digital mapping systems for field data collection. In: Soller D. R. (ed.) Digital mapping techniques 2000-Workshop proceedings. U. S. Geological Surveys Open-file policy document 00-325. http://pubs.usgs.gov/openfile/of00-325/.
32. Dale, P. (1991). Land Information Systems. In: P.Longley, M. Goodchild, D. Maguire and D. Rhind (eds.). Geographic Information Systems Principles, Techniques, Applications and Management. John Wiley & Sons, Inc., New York, pp. 85-99.
33. Croswell, P. L., 2000, The role of standards in support of GDI. In: Groot, R. and McLaughlin, J., (editors), 2000, Geospatial Data Infrastructure: Concepts, cases and good practice. Oxford Uni-versity press.
