SIODIVERSITY BATA MANAGEMENT aes: eeatiak AOCUNICAL 2) _ GUIDELINES | for a 3 ea NATIONAL INSTITUTIONAL SURVEY ' in the contex: of ihe Convention ou Biclog:cai Diversiiv WORLD CONSERVATIO ‘MONITORING CENTRE The mission of the World Conservation Monitoring Centre is to provide information on the status, security and management of the Earth’s biological diversity. BIODIVERSITY DATA MANAGEMENT (Document 2) GUIDELINES for a NATIONAL INSTITUTIONAL SURVEY in the context of the Convention on Biological Diversity United Nations Environment Programme March 1995 Digitized by the Internet Archive in 2010 with funding from UNEP-WCMC, Cambridge http://www.archive.org/details/guidelinesfornat95wcmc i ACKNOWLEDGEMENTS This document is one of a series of four researched and compiled by the World Conservation Monitoring Centre, Cambridge UK with 80% funding from the Global Environment Facility (GEF) through the United Nations Environment Programine (UNEP), Project GF/0301-94-40 (GF/0301-94-06). The need for the development of a package of tools and materials to support national information management for the Convention was identified and the project promulgated by Mark Collins (Director, WCMC) and Robin Pellew (former Director of WCMC). Principal authors were Donald Gordon and Chris Magin. Contributions and critical review were received from a number of WCMC staff and consultants, including Christine Carey, Ian Crain, Gareth Lloyd, Gwynneth Martin, and Jake Reynolds. The document has benefited, as well, from review and comment from NGOs, UNEP, and experts in a number of countries including Colin Bibby of Birdlife International, and others who participated in a consultation meeting hosted by UNEP in Nairobi in October, 1994. Graphical concepts were developed by Gwynneth Martin, Ian Crain and Don Gordon and executed by Ian Kime of "Constructive Solutions". Document organisation, integration and input was by Laura Battlebury. Ian Crain was the project manager and responsible for overall design and editing. APROX HEE . TR ott (cd Danae Dee Abo Teh Fo ee. ia. Sei Fa, yreaeriteeyty sae =~ ladle) 24 mont poli SOS ae my agit) APE BAGO. ontieye Reeser T tne enna’ anata Baws), ill veel (eo. Writ woneenttal eho tata, ont yal, boat aly PRONE ir revi WIPES rater Atay gi Ot. sare pama yom ata Sibley SURE RF Shahi bas stout ts .yedeagy VP. ei) with) ant. ere ietg tf lab taliicw) ssw aod a W. re ie siete} Sclaiiel tito. Sap € = gla ia ens er Coa cal y onti., SE oe WAVE) eee iow a De ris Leni’? Metin peal << vi cit washihiza sn 3 Re eee! “iy Sys axiomiga mene” No = — 4 3 g Z Water Land Tenure & Property Policy & Planning TYPES OF BIODIVERSITY INFORMATION Cultural Factors Legal | Anthropological nomi Pte HABITATS Marine eae eae tal Vegetation INSTITUTION TYPE In-Country Multilateral eg WB National Statistics Bureau Provincial State Government Bilateral eg ODA University/ College Research Institute Scientific Council National Resources Biomedical Private Business/Commerce/Industry Cross-Sectoral eg World Bank (WB) National/ Federal Government: Village/Local Community Groups Zoos & Aquaria Botanical Gardens & Herbaria Corporate Sector: Development Aid: 4 CATALOGUING BIODIVERSITY INFORMATION HOLDINGS 4.1 Approach A major output of the institutional survey is a systematic catalog of which institutions hold what information, and in what format. As described previously these data are collected by questionnaire or other means to consolidate the information into a standard format, facilitated by site visits and/or national/regional/local workshops (see Conduct of the Survey, Section 2). The questions in Part 2 of the questionnaire (see Annex 2) covering "Dataset Information" are the most relevant to the cataloguing process. Guideline 17 Data on biodiversity information holdings should be collected using a standard information collection form via direct (eg site visits, workshops), and/or indirect (eg posting of questionnaire) approaches. 4.2 Compilation and Presentation of Data It is likely that a considerable number of biodiversity datasets will be identified in the institutions surveyed. To facilitate the processing and extraction of information it will be necessary, at a minimum, to produce a hard-copy directory of findings (see Section 2.6). Guideline 18 Produce a hard-copy catalog or directory of biodiversity information holdings (datasets) identified. 4.2.1 Production of Directory The project Availability of Biodiversity Information for East Africa used the "merge" facility in a word processing software package to incorporate dataset descriptions into a metadatabase. Merge files are able to combine specific information entered as records in one file with general information entered in a separate file (for example, layout information). The merging of the file containing records with that containing the layout information can be used to produce a directory of findings, generating a separate sheet(s) for each institutional biodiversity dataset identified. This largely automates and greatly simplifies directory production. The choice of software package used in each country, however, should depend on the availability of in-country support and the systems most widely used nationally. Guideline 19 Use a standard software package (such as a word processor) to compile and format survey responses electronically to produce a directory of nationally-available biodiversity datasets. 4.2.2 Directory Contents The hard-copy version of the institutional survey is essentially a reproduction of survey responses. Each response should be reproduced as a separate entry (ie one per institutional dataset held). The directory should contain the following elements: @ table of contents @ introduction giving an overview of the aims of the institutional survey Guidelines for a National Institutional Survey - Document 2 23 explanation of how to use the directory catalog of institutional data holdings, ie details of each institutional dataset alphabetical listing of institutions surveyed glossary index. A directory entry from Availability of Biodiversity Information for East Africa is included in Annex 1 as an illustration of a potential directory template. Guideline 20 The template in Annex 1 can be used as a guide to structuring individual directory entries. The directory contents outline suggested above can be used as a guide to structuring the directory itself. 4.3. Metadatabase Construction In order to facilitate the national and international exchange of datasets and assist in querying the metadata obtained during the institutional survey, countries may decide to construct an electronic metadatabase of their biodiversity information holdings. This should be viewed as an adjunct to the institutional capacity survey, not necessarily an integral part of it. Many such initiatives are currently being developed around the world, and countries are strongly advised to follow the recommendations below if they wish their metadata to be nationally and internationally compatible. Guideline 21 The creation of a permanent updateable electronic catalog of national biodiversity datasets is recommended. If such a metadatabase is constructed, Guidelines 22 through 27 should be followed. 4.3.1 Metadatabase Contents The model questionnaire provided in Annex 2 of this document is based on the metadata format standard that WCMC is establishing (in collaboration with other international organisations) for the recording and exchange of environmental metadata. The standard defines the metadata of importance relating to the data that the institution manages. The model questionnaire contains questions on the information management capacity of the institution, found in the "Institutional Resources" section of Part 1 of the questionnaire. Answers relating to information management capacity are of importance for the institutional survey, but are not usually included in the metadatabase. As a rule, the metadatabase concerns itself with the actual information that an institution manages (and very brief background details about the institution such as its address and title) and not with the resources that it uses to manage that information. Guideline 22 Restrict the contents of a metadatabase to a description of institutional datasets and institutional summary. The inclusion of data on institutional resources is not usually incorporated. 24 Guidelines for a National Institutional Survey - Document 2 4.3.2 Metadatabase Formats In order to facilitate the exchange of data, it is important that the metadatabase format (ie the structure of data entries) and terminology conform to internationally accepted standards. This will facilitate both cooperation and data-sharing between similarly-oriented national institutions and their counterparts in neighbouring countries, and with organisations with international (as opposed to national) scopes. An outline of WCMC’s proposed metadatabase formats is given in Annex 7. Further details of currently accepted metadatabase formats and that proposed by WCMC are given in accompanying Guidelines for Information Management (Document 3). If a metadatabase is to be developed, metadatabase formats should be discussed at the outset of the project and considered in the context of how the survey is to be conducted (eg using written questionnaire, informal group meeting etc). Guideline 23 Care should be taken to ensure that metadatabase formats are compatible with international standards in order to promote data-sharing potential. The proposed metadatabase format outlined in Annex 7 can be used as a guide. Guideline 24 The decision to develop an electronic metadatabase should be taken early on in project development and considered in tandem with the survey approach(es) to be used. 4.3.3 Metadatabase Data Entry The questionnaire results can be directly inserted into a Relational Database Management System (RDBMS) application that has been designed and built on the basis of the metadata standards defined in Annex 7. Database tables may be constructed for each of the entities Institution, Dataset and Member, with table fields corresponding to the attributes as defined in the format definition. WCMC have built their own metadatabase using the INGRES system, but any RDBMS could be used to build a similar system. For the exchange of metadata with other organisations (eg other NBUs), a metadata exchange format is provided in Annex 7. This is a definition of metadata contents, format and syntax, enabling the latter to be unambiguously recorded. The syntax used is based on that defined by the US National Aeronautics and Space Administration (NASA) in its Directory Interchange Format (DIF) (World Data Center, 1991). This syntax allows the contents of the metadatabase to be output into a standard electronic text report which can be unambiguously understood by other organisations adopting the same format. By following the syntax precisely (ie putting in field titles and values exactly as defined), it becomes possible for an organisation to "auto-ingest" metadata. Thus, rather than the metadata exchange being manually typed into the system, the electronic metadata file can be read in automatically. Guideline 25 Data should be entered into the metadatabase using definitions provided in Annex 7. i Guidelines for a National Institutional Survey - Document 2 25 4.3.4 Metadatabase Updating The institution responsible for maintaining the outputs of the institutional survey (see Section 2.8.1), should appoint a metadatabase manager with the explicit duty of keeping metadata current and accurate. The duties of the manager will focus primarily on maintaining the contents of the three core levels up to date (Institution, Dataset and Member). An appropriate update period is one year, the procedure commencing at a specified time each year. Keeping institutional metadata up to date is not an onerous task, often requiring little more than simple checks (possibly over the telephone) with relevant dataset managers. New institutions that appear or are "discovered" will need to be dealt with using the original questionnaire/site visit approach, before being added to the country metadatabase. The Dataset and Product levels are best handled by printing the contents of the metadatabase, sending these to the individual institutions, and asking them to verify their datasets and - products and to supply information on modifications/additions in questionnaire format. Guideline 26 Ensure that a mechanism is established for regular updating of the metadatabase. 4.3.5 Metadatabase Documentation Whichever metadatabase format is decided upon, clear, concise documentation is essential. This should be produced in the form of a "User’s Guide" which should give the technical specifications of the metadatabase and instructions on how to enter records and perform simple searches. Guideline 27 Produce a User’s Guide to assist users of the metadatabase. 26 Guidelines for a National Institutional Survey - Document 2 5 ASSESSING INSTITUTIONAL LINKAGES 5.1 Approach A significant output of the survey is enhanced understanding of the flow of biodiversity information between institutions, within and outside the country. It is clear that many different types of data are needed for decision making concerning the conservation of biological diversity and sustainable use of its components. A single institution will not have the resources, expertise or mandate to collect, manage or assess all the required data. Thus, it is important to identify both where and how the different sources of information are brought together, and what barriers might exist to the integration process. By careful comparison with the Data Flow Model (Document 1), the linkages between institutions may be compared to the conceptual framework required in support of the CBD. This exercise may reveal collaborative deficiencies which hinder the integrated biodiversity programmes required under the Convention. 5.2 _ Linkage Information Collection For any institution, the first level of information required is: @ from which institutions (within and outside the country) are data obtained @ to which institutions are data supplied @ with which institutions are there linkages which do not involve data transfer. The third category above refers to linkages which involve the sharing or exchange of expertise, technology, policies, strategies, and so on, aS opposed to the exchange of biodiversity data. It is possible to obtain this information by means of a questionnaire, such as part 1, Section 3 of the model questionnaire in Annex 2. It is useful to divide linkages into institutions in the country and external institutions. These linkages, particularly the third group, may be difficult to define initially, and may not all be known to a single individual in the institution. For this reason, a better picture can probably be formed via group discussions during site visits conducted by the Project Team (see Section 2.5.5). In combination with discussions, the questionnaire approach should result in a list of linked institutions in the form of a table as follows: Guidelines for a National Institutional Survey - Document 2 27 Institution Name: Linked Institution In-country/ Data Data Non-Data External Provider User Linkage ee De ee | tm pp un fed | neni stae Amcitwceriah aie wel Dua!boiiM ner! .ait no | ame a Pree See eee Ree eho) EO ial elles | Institution "Z" Institution "1" Legend: IC = In-country E = External M = Major m = Minor Table 5.1 - Table of Institutional Linkages The columns could be simple "check marks", but it would be preferable to distinguish between major or frequent data providers (and users) and minor or infrequent providers (and users). In the example of Table 5.1, the notation of M for major and m for minor has been used. For each linkage it is also desirable to record the following details: ® administrative arrangements for movement of data (eg informal or formal, are charges made) @ an indication of volume and frequency of data transfer © physical format of the data transferred (eg documents, maps, computer media, electronic) @ if by computer media what format or standard is used. For this type of detail there is likely to be such a wide variation that a questionnaire design to elicit meaningful information is difficult. These details are best obtained through discussions with the responsible staff member during a site visit and noted in narrative form. The above points give a general indication of the topics to be covered. Guideline 28 Aided by a questionnaire or check-list, tabulate in a standard format the data and non-data linkages between the surveyed institution and other national and external institutions. 28 Guidelines for a National Institutional Survey - Document 2 5.3 Information Compilation and Presentation 5.3.1 Institutional Level The first level of information supplied will enable the compilation of lists or tables such as Table 5.1, indicating whether the institution is a provider, a user, or both. Note that if any national institution is listed it should have been included in the survey, ie the responses received may indicate omissions in the original scope of institutions surveyed and any such omission should be rectified. A diagrammatic way of presenting linkage information concerning an institution is also useful. In Figure 5.1, institutions are represented by boxes containing the institution name. Inflows of data from data providers are depicted as arrows pointing towards the surveyed institution, whilst arrows directed towards external institutions represent outflows of data to user institutions. Lines without directional arrows represent non-data linkages. Line types can be used to indicate the degree of linkage. For example, dashed and solid lines can be used to represent minor and major rates of data transfer respectively. EXTERNAL INSTITUTION INSTITUTION | INSTITUTION Ww | x Nara INSTITUTION v4 LEGEND: Major data linkage -_-_—-——> Minor data linkage —= Non-data linkage Figure 5.1: Institutional Linkages Diagram In the example of Figure 5.1, institutions W and X are major users of data; Y is a minor user of the surveyed institution’s data; institutions X and Y are major providers of data; and the surveyed institution has non-data (eg policy or technology) linkages with institutions X and Z. In addition, data is received from an external institution (a separate symbol may be ee Guidelines for a National Institutional Survey - Document 2 29 used to distinguish external institutions). Guideline 29 Identify the linkages of each institution in diagrammatic form using the model of Figure 5.1. 5.3.2 National Level The diagrammatic approach gives a clear picture of each institution’s linkages from the perspective of the surveyed institution. There will be one such diagram per institution. To usefully analyze the information into a national perspective it is necessary to consolidate the information into one overall view. One approach to this is to summarise linkages in a cross tabulation, such as appears in Figure 5.2. Institutions are listed on both axes, with column entries illustrating which institutions are identified as Suppliers of data, and row entries illustrating those Receiving data. Figure 5.2 shows that institution A supplies data to institutions B, C and D (3 S-entries in the first column), and that it receives data from the same three places (3 R-entries in the first row); institution B supplies data to no-one but receives data from institution A; and so on. Note that each cell in the matrix should be either blank or have two corresponding "Receives/Supplies" entries (the institutions involved in the data transfer having both identified the interaction). This permits cross-checking of the information obtained, and possible follow-up questions to mismatched institutions. In the sample of Figure 5.2 there are two such anomalous situations: institution C indicates that it is a user of D’s data, but institution D does not indicate that it provides data to C, and institute A apparently receives data from institute B, but the latter does not identify the provision of data to A. Receivers Suppliers [iteeAtes [noes [eee | oar] DES | Legend: SS: institute in this column is a supplier (provider) of data to the institute in this row R: institute in this row is a receiver (user) of data from the institute in this column Figure 5.2 National Institute Linkage Cross-Tabulation 30 Guidelines for a National Institutional Survey - Document 2 The resulting tabulation can help identify which institutions are primary suppliers (many entries in the column for that institution) and which might be primarily data integrators (many entries in the row for that institution). Again a graphic representation can be very expressive. A convention similar to that in Fig 5.1 above may be used, with the addition of a dot indicating which institution identified the linkage, and arrows depicting the direction of data flow. Each linkage (line) should be identified by both institutions (a dot at both ends of the line). The example shown in Figure 5.3 is based on the same scenario as was the cross-tabulation in Figure 5.2, with the addition of institution E which has non-data linkages to A and a minor data exchange with B. Note the two cases of unmatched dots. Such diagrams will provide a good overall picture of biodiversity information management in the country, and be an aid to identifying missing and inappropriate linkages. Guideline 30 Summarise national biodiversity information linkages in tabular and diagrammatic form as indicated in Figures 5.2 and 5.3. Clarify and rectify anomalous situations identified in the diagrams. LEGEND: a cate acme Data flow Non-data linkage SS SSS > > Minor data linkage Figure 5.3: National Institute Network Diagram i Guidelines for a National Institutional Survey - Document 2 31 In the course of discussions with an institution, it may become apparent that some linkages are desirable but have not been achieved. There are a number of possible reasons for these missing links including: access procedures and regulations security and legal concerns charges for data lack of knowledge of how to access data lack of technology to access data. These desirable linkages should be identified and tabulated along with a discussion of the barriers to their formation. Guideline 31 Identify previously unknown linkages, unachieved but desirable linkages, plus the nature of the barriers to linkage formation, as part of the site visit process. Note that the emphasis in this section is strictly on linkages and little is revealed as to the content of the data transferred. This, by implication, is best determined through the process of cataloguing information holdings described in Section 4. 32 Guidelines for a National Institutional Survey - Document 2 6 ASSESSING INFORMATION MANAGEMENT CAPABILITIES 6.1 Approach To assess the information management capabilities of an institution, basic information on the technical, human and financial resources are needed. Further, there is a need for a general picture of how these resources come together to deliver "information management capability". Two institutions may have similar funding, equipment and numbers of staff, but their capabilities may be very different because of mandate, workload, degree of specialisation, or administrative practices. Some quantitative analysis may be possible, but subjective analysis is also suggested, using information on institutional resources, how data is used in the institution, and the portfolio of projects accomplished. 6.2 Data Collection The information required falls into two main categories, related to the level of technology in use and the expertise level of staff. 6.2.1 Human Resources An institution will fail to perform its role without well qualified staff, and thus the most important determinant of its overall capacity is the quality of its employees. For a more thorough discussion of human resource issues in capacity building, refer to the accompanying Document 3. An assessment of human resources can be made during the survey by quantifying the number of staff, particularly professional staff, and their level of training and expertise in their respective fields. Special attention should be paid to qualifications and skills in applied information technology. Both academic training (degrees and further degrees) and on-the-job experience should be included. Questions of this nature are also incorporated in the Institutional Resources section of the model questionnaire (see Annex 2). Guideline 33 Obtain basic information on the number and quality of the human resources of the institution using a simple questionnaire design augmented by discussion during a Site visit or meeting. 6.2.1 Technical Resources A preliminary sketch of the institution’s technical resources can be accomplished as part of the survey process. Institutions should be asked to provide information on: @ number and type of computer hardware (eg personal computers, work stations) © operating systems in use (eg DOS, Windows) e@ software relevant to biodiversity information management (eg GIS, desk-top mapping, modelling, statistical analysis, spreadsheet, word processing, and database management packages) Dene eee ee Guidelines for a National Institutional Survey - Document 2 33 @ electronic communications (from local networks to "global" systems such as electronic mail and other Internet services). Suggested questions to elicit this information are included in the Institutional Resources section of the model questionnaire (see Annex 2). Guideline 32 Obtain basic information on the hardware, software and communications assets of the institution using a simple questionnaire design augmented by discussion during site visits and/or workshops. Note that it is not necessary to compile a detailed inventory specifying each piece of equipment. General totals by classes are sufficient, such as: 3 IBM-PC 386 5 IBM-PC 486 2 Sun workstations 1 A3 flatbed scanner 1 A3 inkjet plotter Again, software can be summarised by listing the names of commonly used packages without attempting an exhaustive list. Suggested headings are: word-processors spreadsheets statistical and modelling packages database management systems graphics packages GIS and desk-top mapping packages other applications software. It may often be the case that detailed software and hardware inventories are already available as routine administrative products in the institution. If that is the case these will suffice, subject to confirmation during the site visit or meeting. 6.2.3 Financial Resources The financial resources of an organisation, particulary those resources which can be applied to biodiversity information management, are an important factor in determining capability. This is an area which should have been addressed in some detail in locations where a Country Study has been completed. since complete guidelines for evaluating investment in biodiversity are included in the Country Study Guidelines document. However, it may still be necessary to estimate the financial resources available for biodiversity information management in the institution, and this may be quite difficult, depending on the particular accounting structure employed. It is therefore best to approach this problem via discussion during a site visit, and perform an approximate assessment based on these discussions. 34 Guidelines for a National Institutional Survey - Document 2 Guideline 34 Assess level of institutional financial resources available for biodiversity information management via discussion with senior officials of the institution. 6.3 Information Compilation and Presentation 6.3.1 Institutional Overview In the model questionnaire (see Annex 2), data on the computer technology used by an institution and the level of its human resources are compiled into a series of summary tables and checklists. To effectively summarise the information for an institution (ie cover the range of questionnaire results), a series of similar tables may be necessary, each being refined following site visit discussions. Some small improvements can be made to assist interpretation, for example: @ software checklists may be modified in light of the responses, ie common packages listed under "other" might be shifted into more specific categories @ the number of staff at a given level of expertise could be entered as a percentage in a further column. As indicated in the introduction to this section, non-quantitative (subjective) assessments are important. For this reason, a summary report should also be prepared, based on analysis during the site visit. This report would consider the special strengths of the organisation in relation to national biodiversity information strategy, particular attention being made to what specialised information management skills are possessed which might be of value to other partners; the existence of well documented exemplary projects; and possible contributions in terms of the sharing of data and expertise (see Annex 3 for a model table of contents). Guideline 35 Prepare a report for each institution outlining organisational strengths, exemplary projects, and possible contributions to the national biodiversity information system. The process of undertaking an institutional survey, especially where site visits feature prominently, provides a good opportunity to identify areas of weakness in institutional capacity, among these the need for additional human resource development and technology. While it is not the primary purpose of the survey, these observations on the needs for capacity building should be recorded during the process, and will provide a useful basis for developing institutional strengthening strategies (see also Section 2.5.2). Suggestion Report in narrative form major institutional requirements for capacity building, particularly in terms of human resource development and technology transfer. Guidelines for a National Institutional Survey - Document 2 35 6.3.2 National Overview A summary of the above information is required for national overview. One possibility is to establish a simple database into which the institutional descriptions are entered. This information could then be presented in a variety of different ways as follows: © to determine the total information management resources of all institutions surveyed @ to tabulate which institutions use which hardware and software @ to tabulate the type of resources in the different institutions. Such a database (refer to Section 4.3.1) could reveal common practices in software usage (de facto standards), institutional strengths and gaps, and also facilitate answers to ad hoc queries. Further, background information such as institutional function and project portfolio could be integrated with the resource database for more general assessments (see 6.4 below). Suggestion Maintain basic institutional resource information in a simple, easily updated, database. 6.4 Assessment The existence of adequate hardware, software, and human resources does not necessarily guarantee capability. An assessment of the latter therefore requires an analysis of institutional competence, by inspection of projects accomplished, reports and papers published, and so on. This can be achieved best through the completion of a site visit and review of the institutional summary report. The institutional resource database described above may be used to group institutions with respect to their potential for information management capability. Three broad levels (high, medium and low) are suggested for each human or technological resource area. In terms of human resources, "high" may imply a sufficient number of highly qualified staff broadly covering the discipline, and "low", an insufficient number of staff with specific skills only. In the technology area, "high" may imply many networked computers and peripheral devices, and "low", non-networked, obsolete, or absent technology. The meaning of these levels will vary considerably from country to country and are intended purely to assist with internal institutional assessments. The relative role played by the institution in terms of information transfer (as determined by the analysis of linkages (Section 5) is also a key factor. Institutions with high ratings in both human and technological resources, will probably be key centres in a national biodiversity network, and should thus be given priority in follow-up support. Nevertheless, attention should also be paid to institutional objectives, evidenced by the nature of projects undertaken. These factors may reveal valuable capabilities in organisations which appear to have low-to-medium resource levels. As capacity building efforts increase, institutional strengths may change rapidly. For this reason, it is important to update institutional information regularly after the completion of the initial survey. Before the survey team is disbanded, a process should therefore be put in place to achieve this, for instance by means of annual inputs of data from participating institutions. Scheduling and funding mechanisms will require careful attention. Annex 5 provides a model table of contents for the final national report. 36 Guidelines for a National Institutional Survey - Document 2 Guideline 36 Summarise overall national institutional strength by reviewing both quantitative and qualitative information gathered in the survey. Use this information to identify the key national institutions for biodiversity information management. : Guideline 37 Implement a process to keep institutional information up-to-date. ee ES EEE Guidelines for a National Institutional Survey - Document 2 37 7 REFERENCES Burley, C. 1994. CIESIN Metadata Entry Form Instructions. Consortium for Earth Science Information Network. Pinburg, U. 1992. Catalogue of Data Sources (CDS) for the Environment: Analysis and Suggestions for a Meta-data System and Service. European Environment Agency (EEA). UNEP 1990. INFOTERRA Thesaurus of Environmental Terms, 3rd edn. United Nations Environment Programme, Nairobi. UNEP 1993. Guidelines for Country Studies. United Nations Environment Programme, Nairobi. WCMC 1993. Availability of Biodiversity Information in East Africa. World Conservation Monitoring Centre. 38 Guidelines for a National Institutional Survey - Document 2 ANNEX 1: SAMPLE DIRECTORY ENTRY Makerere University Faculty of Science, Zoology Museum Tel No: Fax No:+256 41 530412 (c/o Wandegeya Post Office) E-mail: Telex: Function of unit/institution: Department: has operated as a depository for specimens used in teaching and for practical demonstration. It is now being developed as a reference point and national repository for animal specimens. Title or subject of dataset Mammals 1 DESCRIPTION OF INFORMATION HOLDINGS Title or subject of dataset: Mammals. Information manager/contact name: Mr Robert M. Kityo, Museum Curator. Form of dataset: Physical specimens/other. Size and description of holdings: 1,543 physical specimens; a printout of some Ugandan Mammal specimens (1,197 records) in holding at Field Museum of Natural History (Chicago). Objectives of dataset: Has functioned as a teaching collection. But is now being developed as a reference source for the National Biodiversity Data Bank of Makerere University. Localities covered: Uganda. Countries covered: Uganda. Biomes covered: Tropical humid forest/tropical dry woodlands/ mountain and highland. Ecosystems covered: Savanna/rainforest. Description of information held: The bulk of the information is in the form of dried skins and/or skeletal materials. These however also mostly cover small sized animals. Mammals are also stored as pickled specimens. Completeness, limitations and gaps: Information not exhaustive, it reflects research interests of people that have gone through the department. The mammals collection has a good representation of the rodent species in the country but not for other groups. The materials are mostly taken from areas that were easily accessible by the researchers. oo Guidelines for a National Institutional Survey - Document 2 39 2 INFORMATION MANAGEMENT Where dataset is located: How dataset was acquired/built: How information is managed: hardware: operating system: software: Date information collected: Are data being actively maintained: Are data part of an ongoing project: Details of project/contract: If computerised - 3 ACCESS Access conditions: Further details on access conditions: Outside access through: Further details on outside access: Documentation of information holdings: 40 Zoology Department Museum, Makerere University, Kampala, Uganda. 1) Local collection of specimens and mammal materials by the academic staff and students. 2) Through active efforts of collecting specimens by the manager from different parts of the country. Card file/catalogued/other. Over 90% catalogued; in the process of computerising the whole collection. 1961-1970, 1971-? 1989-1993. Yes. Yes. National Biodiversity Data Bank, Makerere University Institute of Environment and Natural Resources. Limited. Limited access because it is not a widely known dataset outside of the Zoology Department. Collection is open to students of the University and interested outsiders; access by appointment. Museum Curator. At present only catalog, card index and specimen cards. Plans for future on-screen documentation within 1.5 years. Guidelines for a National Institutional Survey - Document 2 ANNEX 2: MODEL QUESTIONNAIRE: NATIONAL INSTITUTIONAL SURVEY DOCUMENT 1: INSTITUTIONAL INFORMATION 1 INSTITUTIONAL DETAILS Name of institution and Acronym: Name of department or unit and Acronym: Type of institution (eg Government, NGO): Postal address: Physical address (if different from above): Telephone no: Fax no: E-mail: Telex: Core business of unit/institution: (eg capacity building, research) Main current activities/projects: Keywords: Contact person and status: Date questionnaire completed: Cee ee ee ee S Guidelines for a National Institutional Survey - Document 2 41 2 INSTITUTIONAL RESOURCES Human resources: Staff total - specify number of core/total Breakdown of professional staff by level of education/experience and by discipline (See Table 1) Areas of outstanding institutional expertise: Areas of outstanding individual expertise (give names): Human resource needs: ee ee eee 42 Guidelines for a National Institutional Survey - Document 2 uoljesiue310 Sururexy (va ‘9Sq) (019 Gud snouasIput I Joyjoue 0} Arepuosas ewojdiq 90189q ‘OSW) 2013p 8a ‘1910 qUQUIPUOseS -1sOq | /feotuyoay ayenpein ayenpelsjsog aur[diosip Aq pue adualszedxa/uoneonpa Jo jaaa] Aq JJv}S [BUOISsayoid Jo UMOPYyeaAIg =] IIqBI, Computer hardware: IBM-PC (personal computer) Specify level (eg 386, 486) Apple Macintosh Peripherals (eg digitising tables/plotters, printers, other) Specify type Computer operating environment: O DOS O Windows Macintosh UNIX [Se fS)) {=} Other - specify Computer operating environment needs: Applications software: Database Management System (DBMS) - list those in use (eg FoxPro, dBase) Geographic Information System (GIS) - list those in use (eg ARC/INFO, IDRISI, MapInfo) 44 Guidelines for a National Institutional Survey - Document 2 Word processing - list those in use (eg WordPerfect, Word) Statistical and modelling packages - list those in use (eg SPSS, SAS) Graphics packages - list those in use (eg Harvard Graphics, CorelDraw) Other applications - list those in use Application software needs: Electronic communications: Local Area Network (LAN) Wide Area Network (WAN) a) E-mail via Internet or commercial provider (eg CompuServe, FidoNet) O Full Internet connection (eg World Wide Web, Telnet, Ftp, WAIS, Usenet) Electronic communications needs: Any other user needs: en Guidelines for a National Institutional Survey - Document 2 45 3 INSTITUTIONAL LINKS Up to 10 institutions from which data are obtained regularly: NATIONAL EXTERNAL NATIONAL EXTERNAL 46 Guidelines for a National Institutional Survey - Document 2 Up to 10 institutions with which non-data linkages are established: (eg exchange of expertise, policy or advice) NATIONAL EXTERNAL Guidelines for a National Institutional Survey - Document 2 47 48 Guidelines for a National Institutional Survey - Document 2 DOCUMENT 2: DATASET INFORMATION 1 DESCRIPTION OF DATASET (complete one copy for each dataset) Note: For purposes of this survey, a "dataset" can be a single file, but more commonly will consist of a collection of thematically related files which can be conveniently described as a group, such as "Forest ecology data from the XX region". It is not intended that each individual record, map, report, GIS coverage or small electronic file be separately listed and described. 1.1 Name or subject area of dataset: 1.2 Objectives of dataset: 1.3 Keywords: 1.4 Name of information manager: 1.5 Form of dataset: Size of information holdings: 0 Bibliographic collections 0 Physical specimens (eg herbarium sheets) O Field records Maps Tables Reports Sf) Se) = GIS holdings (eg national wetlands coverage) oe ——e—————————eE—————————EE—EE———— Guidelines for a National Institutional Survey - Document 2 49 O Database information (electronic records) O Word processing files O Remote sensing data (specify sensor type, eg AVHRR MSS, TM, SPOT, aerial photography) O Other - specify 1.6 Location of dataset: 1.7 How the information is being managed: O All computerised O Partly computerised ( %) O Card file O Catalogue O Other - specify 1.8 How the dataset was acquired/built: 1.9 If computerised, software used to manage dataset: (eg Excel, dBase, FoxPro, Ingres, Oracle, ARC/INFO) 50 Guidelines for a National Institutional Survey - Document 2 2 INFORMATION COVERAGE 2.1 Area of covered (provide a map where possible): (eg local/regional/national/international/global) 2.2 Themes covered: 2.3 Maintenance of the information: Active (yes/no): Part of an ongoing project/contract (yes/no/details): 2.5 Time period that information covers: (eg 1914-1949) Start day/month/year: Stop day/month/year: 2.6 Completeness, limitations, and gaps in the information: 3 INFORMATION ACCESS 3.1 Conditions: 0 No outside access/use a Guidelines for a National Institutional Survey - Document 2 51 oOo Limited access (please give details) oO Freely available (at any time?) oO On payment of funds (eg cost of recovery; commercial sale) Oo Other - specify 3.2 Outside access through: O Published material O Diskette/tape O On-site O On-line - specify network(s) oO Other - specify 3.4 Documentation of information holdings: (eg descriptions available, user guides, on-screen documentation) 3.5 Other organisations known to hold biodiversity information: (names and addresses) Title and position of person completing this form: Please return as quickly as possible to: 52 Guidelines for a National Institutional Survey - Document 2 ANNEX 3: MATRIX FOR IDENTIFYING INSTITUTIONS MANAGING BIODIVERSITY 2 a | o Plasm/ nae Germ Tissue Culture nae ee | TYPES OF BIODIVERSITY INFORMATION } ° a oz = -} INSTITUTION Continued... PH dl sce ak Resources 3 3 Demography Land Tenure Planning | & Property — Anthropological Cultural Factors TYPES OF BIODIVERSITY INFORMATION peass| HABITATS Freshwater Marine & Coastal Vegetation ANNEX 4: MODEL TABLE OF CONTENTS: INSTITUTIONAL REPORT 1 2 Institutional Details Biodiversity Dataset Holdings Dall! Description of Dataset(s) 2.2. Information Coverage 2.3. Information Access Information Management Capabilities 3.1 Technical Resources 3.2 Human Resources 3.3. Financial Resources Available for Biodiversity Information Management 3.4 Organisational Strengths and Competencies Institutional Linkages 4.1 Data Supply and Provision, and Non-data Linkages 4.2 Gaps and Weaknesses Needs Assessment (optional) Institutional Summary eee Guidelines for a National Institutional Survey - Document 2 55 56 Guidelines for a National Institutional Survey - Document 2 ANNEX 5: MODEL TABLE OF CONTENTS: FINAL NATIONAL REPORT PART 1: SUMMARY OF FINDINGS 1 Introduction 1.1 The Project Context 1.2 Chronology of Project Development and Implementation 1.3 Methodology Adopted 2 Analysis and Summary of Results 2.1 Biodiversity Dataset Holdings: Coverage, Gaps, Accessibility 2.2 Information Management Capabilities: Overview of Technical, Human and Financial Resources Available 2.3 Institutional Linkages: The National Picture 2.4 Needs Analysis (optional) 2.5 State of National Biodiversity Information Management: A Summary 3 Project Conclusions 4 Recommendations for Future Action ANNEX 1 Information Brochure ANNEX 2 Questionnaire(s) ANNEX 3 = Synopsis of Workshop Proceedings ANNEX 4_—_ Case Book of Selected Institutional Reports PART 2: CATALOG OF SURVEY ENTRIES 1 Introduction 2 Use of Catalog 3 Explanation of Catalog Headings 4 Questionnaire/Survey Entries 5 Alphabetical Listing of Institutions 6 Glossary 7 Index Guidelines for a National Institutional Survey - Document 2 57 nn 58 Guidelines for a National Institutional Survey - Document 2 ANNEX 6: TARGET INSTITUTIONS IDENTIFIED IN EAST AFRICA KENYA African Centre for Technology Studies African Wildlife Foundation Department of Resource Surveys and Remote Sensing Douglas-Hamilton Associates - Ecological Consultancies East African Natural History Society East African Wildlife Society Game Ranching Ltd. Genebank (KARI) International Centre for Research in Agroforestry (ICRAF) KENGO Kenya Forestry Research Institute (KEFRI) - Entomology Kenya Forestry Research Institute (KEFRI) - Pathology and Mycology Kenya Marine and Fisheries Research Institute (KMFRI) - Computer Section Kenya Meteorological Department - Data Processing Section Kenya Trypanosomiasis Research Institute Kenya Wildlife Service (KWS) - GIS Unit Kenya Wildlife Service (KWS) - Scientific Services, Computer Department Kenya Wildlife Service (KWS) - Veterinary Department National Council for Science and Technology - Biological and Physical Sciences National Environment Secretariat National Museums of Kenya - Centre for Biodiversity National Museums of Kenya - Coastal Forest Conservation Unit National Museums of Kenya - Department of Herpetology National Museums of Kenya - Herbarium National Museums of Kenya - Invertebrate Zoology National Museums of Kenya - Indigenous Food Plants Programme National Museums of Kenya - Kenya Indigenous Forest Conservation (KIFCON) National Museums of Kenya - Mammalogy Department The Kora Research Project Wildlife Conservation International World Wide Fund For Nature (WWF) East African Regional Office TANZANIA Animal Disease Research Institute College of African Wildlife Management Fisheries Division - Ministry of Tourism, Natural Resources and the Environment Frontier Tanzania - Coastal Forest Research Programme Horticulture Research and Training Institute - Ministry of Agriculture Institute of Resources Assessment - University of Dar es Salaam Institute of Traditional Medicine Malihai Clubs of Tanzania - Research and Training National Environment Management Council - Documentation Centre National Land Use Planning Commission National Museums of Tanzania Guidelines for a National Institutional Survey - Document 2 National Tree Seed Centre Catchment Forestry Project - Ministry of Tourism, Natural Resources and the Environment Serengeti Wildlife Research Centre Serengeti Wildlife Research Institute Sokoine University of Agriculture Tanzania Commission for Science and Technology - Information Unit Tanzania Fisheries Research Institute Tanzania Forestry Research Institute Tropical Pesticides Research Institute - Agricultural Entomology Section Tropical Pesticides Research Institute - National Herbarium Tropical Pesticides Research Institute - National Plant Genetic Resources Centre University of Dar es Salaam - Library University of Dar es Salaam - Demographic Training Unit University of Dar es Salaam - Department of Botany University of Dar es Salaam - Department of Zoology and Marine Biology Wildlife Department - Ministry of Tourism, Natural Resources and the Environment UGANDA Budongo Forest Project Department of Environmental Protection - National Environment Information Centre Department of Environmental Protection - National Wetlands Conservation and Management Programme Forest Department - Natural Forest Conservation Project Game Department Forest Department - Nyabyeya Forest College Institute of Tropical Forest Conservation Kawanda Agricultural Research Institute Makerere University - Zoology Department/Museum Makerere University - Veterinary Microbiology Makerere University Biological Field Station Makerere University - Herbarium Makerere University Institute of Environmental and Natural Resources - National Biodiversity Data Bank Ministry of Agriculture, Animal Resources and Fisheries - Botanical Garden Ministry of Lands, Housing and Urban Development - Department of Lands and Surveys Ministry of Public Health - Institute of Public Health Mount Elgon Conservation and Development Project Namulonge Agricultural Research Institute National Agricultural Research Organisation - Fisheries Research Institute Natural Chemotherapeutics Research Laboratory Uganda Institute of Ecology Uganda National Parks/Game Department - Wildlife College, Lake Katwe 60 Guidelines for a Naticnal Institutional Survey - Document 2 ANNEX 7: MODEL METADATABASE FORMAT For the purposes of conducting an Institutional Survey, WCMC has evaluated a number of different existing environmental metadata formats, primarily the European Environment Agency (EEA) Catalogue of Data Sources (CDS) (Pinborg, 1992), the UNEP Global Resource Information Database (GRID) Metadatabase (UNEP, 1992), the Consortium for International Earth Science Information Network (CIESIN) Catalogue Service (Burley, 1994), and the UNEP Harmonization of Environmental Measurement (HEM) HemDisk (UNEP, 1994). Each of these addresses certain requirements, but also leaves other requirements unfulfilled. The metadata exchange standard proposed here is based on these existing or developing metadatabase systems, supplemented with additions to meet the requirements of biodiversity information management. A three-layer metadata model is proposed (see Figure A6.1), based on the hierarchy of entities: Institution > Dataset > Member. Additional entities can be added to this core as necessary. For instance, some institutions may wish to add a "Personnel" entity in order to record information on individuals in the institution, which then can be linked to the three core entities. INSTITUTION Name Type Geo-location Ee a AN ea ne DATASET | PERSONNEL | Name Name I Type ! Position Geo-location | Skills I a ee ee ee ee ee d MEMBER Name Type Geo-location Figure A6.1: Metadata Entity Hierarchy Guidelines for a National Institutional Survey - Document 2 61 The Institution is defined as a recognisable organisation that stores and maintains information of relevance to the Convention on Biological Diversity. The Dataset is defined as a collection of data and accompanying documentation maintained at an Institution. A collection of data refers to one or a series of Data Members which relate to a specific theme or geographic region. A Dataset entity occurs under that name in the UNEP-GRID metadatabase (UNEP, 1992), and under the name "Directory Entry" in the CIESIN metadatabase (Burley, 1994). The Member can be regarded as equivalent to a data file, paper report, or map, and must be a component of a particular Dataset. Thus Members are the lowest level "concrete" entities that can be distributed by an institution. There are many different types of Member, for instance reports, paper maps, GIS coverages, and database files. One way to accommodate such variety is to abandon a structured format and describe members using free text. However, this means that Member metadata can have widely varying degrees of completeness and little standardisation. These guidelines recommend the definition of a Member format that incorporates as much structure as possible, whilst still permitting all types of Member to be recorded. For the purposes of the institutional survey, information will need to be collected on the top two levels of the hierarchy (Institution and Dataset). The collection of metadata for the lowest level (Member) is not essential for the purposes of the survey and is not included in the questionnaire. This level is provided in the metadata format so that the National Biodiversity Unit (NBU) has the later option of recording and storing metadata at this level of detail (possibly within a metadatabase system). The remainder of this annex provides sample metadatabase entries and field definitions for Institution, Dataset, and Member metadata. Example of a completed Institution metadatabase entry Institution _ID: 0001 Name: World Conservation Monitoring Centre Acronym: WCMC Type: Non-governmental Theme: Information Services Keywords: biodiversity; conservation; information Postal_ Address: 219 Huntingdon Road Postal_Code: CB3 ODL City: Cambridge Country: United Kingdom Contact_Person: Jo Taylor Contact_Status: Telephone: 44-1223-277314 Fax: 44-1223-277136 Email: Internet: info@wcemc.org.uk 62 Guidelines for a National Institutional Survey - Document 2 Information Officer Update Date: Mission: 1994-09-01 To provide research, information and technical services so that decisions affecting the conservation and sustainable use of biological resources may be based on the best available scientific information. Field definitions of Institution metadata Institution_ID: Definition Format Status Example Name: Definition Format Status Example Acronym: Definition Format Status Example Type: Definition Format Status Example Theme: Definition Format Status Example Internal identification by which the institution is catalogued within the metadatabase. Institution ID numbers are assigned automatically by the system every time a new institution is added. This ID is not used in metadata exchange among organisations and as such is not an official part of the metadata format definition, but part of the metadatabase system definition. Integer of length = 4. System generated. 0001 Official name of the institution. Maximum 50 characters. Mandatory. World Conservation Monitoring Centre. Short name of the institution. Maximum 15 characters. Optional. WCMC. The organisation type, selected from one of the following: governmental; non- governmental; commercial; academic; inter-governmental; United Nations. Maximum 20 characters. Mandatory. Non-governmental. The primary function of the organisation, selected from one of the following: Research; Consultancy; Information Services; Campaigning. The selection of a primary function keyword is not intended to wholly define the scope of the organisation. Detailed description of the function of the organisation can be expanded on in the "Mission" section. Maximum 30 characters. Mandatory. Information Services. Guidelines for a National Institutional Survey - Document 2 63 Keywords: Definition Keyword(s) by which the institution can define its activities and areas of interest. Used for searching by the metadatabase. Format Use terminology lists where possible (eg Pinborg, 1992; UNEP, 1990; WDC, 1991). Several terms may be entered if separated by semicolons. Status Optional. Example biodiversity; conservation; information. Postal_ Address: Definition Postal address of the organisation (within city location). Format Maximum 50 characters. Status Mandatory. : Example 219 Huntingdon Road. Postal_Code: Definition Official postal code of the organisation. Format Maximum 15 characters. Status Optional. Example CB3 ODL. City: Definition City location of the organisation. Format Maximum 30 characters. Status Mandatory. Example Cambridge. Country: Definition Country location of the organisation. Format Use standard United Nations country names. Maximum 30 characters. Status Mandatory. Example United Kingdom. Contact_Person: Definition Primary contact person or department for further information on the organisation. Format First, Middle and Last Name. Maximum 40 characters. Status Mandatory. Example Jo Taylor. Contact_Status: Definition Position or status of the contact person within the organisation. Format Maximum 30 characters. Status Optional. Example Information Officer. 64 Guidelines for a National Institutional Survey - Document 2 Telephone: Definition Format Status Example Fax: Definition Format Status Example Email: Definition Format Status Example Update _ Date: Definition Format Status Example Mission: Definition Format Status Example Telephone number to reach the contact person. Hyphen-separated codes with all the required numbers for international dialling, ie CountryCode-AreaCode-TelephoneNumber. 2 Maximum 30 characters. Optional. 44-1223-277314 Fax number to reach the contact person. Hyphen-separated codes with all the required numbers for international dialling, ie CountryCode-AreaCode-FaxNumber. Maximum 30 characters. Optional. 44-1223-277136 Electronic mail address to reach the contact person. Network > email address (note that the network name is required, such as: SPAN, Telemail, Internet, NSI/DECnet, BITNET, OMNET, CompuServe). Maximum 50 characters. Optional. Internet > info@wcmc.org.uk Date of when this metadata entity was last updated. YYYY-MM-DD. Mandatory. 1994-08-30 A brief summary of institution’s mission, goals and activities. Maximum 250 characters. Optional. To provide research, information and technical services so that decisions affecting the conservation and sustainable use of biological resources may be based on the best available scientific information. Example of a completed Dataset metadatabase entry Dataset_ID: Name: Acronym: Theme: Keywords: Institution_Name: Institution_Contact: 0036 African Protected Areas GIS AFRICAPA Terrestrial ecosystems protected areas; wildlife World Conservation Monitoring Centre Ian Barnes Guidelines for a National Institutional Survey - Document 2 65 Start_Date: Stop_Date: Update_Date: 1992-02-21 Geo_Coverage: Continental Continent: Africa Region: Country: Sub _ Natl: Minimum Longitude: -17.50 Maximum Latitude: +37.10 Maximum Longitude: +51.30 Minimum Latitude: -34.80 Abstract_Filename: /gis/docs/afr_pa_gis.wp Field definitions of Dataset metadata Dataset_ID: Definition Internal identification by which the dataset is catalogued within the metadatabase. Dataset ID numbers are assigned automatically by the system every time a new dataset is added. This ID is not used in metadata exchange among organisations and as such is not an official part of the metadata format definition, but part of the metadatabase system definition. Format Integer of length = 4. Status System generated. Example 0036 Name: Definition The name given to the dataset or activity being described. The title should be descriptive enough to allow the reader to make a reasonable decision as to whether the data may be of interest. Format Maximum 50 characters. Status Mandatory. Example African Protected Areas GIS. Acronym: Definition Short name (acronym) for the dataset, if there is one. Format Maximum 15 characters. Status Optional. Example AFRICAPA. Theme: Definition This is the theme or parameter being measured by the dataset. The keyword entered is the most general, and should, if possible, be taken from the standard terminology lists. Format Use INFOTERRA terminology list (UNEP, 1990). Maximum 31 characters. Status Mandatory. 66 Guidelines for a National Institutional Survey - Document 2 Example Keywords: Definition Format Status Example Terrestrial ecosystems. Keyword(s) are additional terms that describe and characterise the dataset. Used for searching by the metadatabase. Use terminology lists where possible (eg Pinborg, 1992; UNEP, 1990; WDC, 1991). Several terms may be entered if separated by semicolons. Optional. protected areas; wildlife. Institution_Name: Definition Format Status Example Primary institutional holding the stored data or coordinating centre of the activity. A link may be set up from this field to the "Name" field of the Institution metadata level. Maximum 50 characters. Mandatory. World Conservation Monitoring Centre. Institution_Contact: Definition Format Status Example Start_Date: Definition Format Status Example Stop_ Date: Definition Format Status Example Update_Date: Definition Format Status Contact person for technical support, information about the technical content of the data, access to the data, and how the data are stored (this field doubles for the NASA DIF Technical_contact field (WDC, 1991). First, Middle and Last Name. Maximum 40 characters. Mandatory. Ian Barnes. The beginning date for a temporal dataset (eg satellite data collected over a period of weeks, months or years). YYYY-MM-DD. Optional. 1986-06-31 The ending date for a temporal dataset (see above). This date can also be used for datasets which are periodically updated, such as climatic data. If left blank, the data collection is assumed to be on- going. YYYY-MM-DD. Optional. 1986-08-31 Date of when the dataset was last updated. YYYY-MM-DD. Mandatory. Guidelines for a National Institutional Survey - Document 2 67 Example 1994-08-30 Geo_Coverage: Definition Format Status Example Continent: Definition Format Status Example Region: Definition Format Status Example Country: Definition Format Status Example Sub_Natl: Definition Format Status Example For geo-referenced datasets, this is the coverage area selected from one of the following: global; continental; regional; national; sub-natl. Maximum 15 characters. Mandatory for geo-referenced datasets. Continental. For geo-referenced datasets, this is the name of the continent in which the dataset occurs. Use INFOTERRA terminology list (UNEP, 1990). Maximum 30 characters. Mandatory if "Geo Coverage" field is continental, regional, national, sub-natl. Africa. For geo-referenced datasets, this is the geographic region in which the dataset occurs. Use INFOTERRA terminology list (UNEP, 1990). Maximum 30 characters. Mandatory if "Geo Coverage" field is regional, national, sub-natl. Tropical Africa. For geo-referenced datasets, this is the country in which the dataset occurs. Use United Nations standard country names (English language version). Maximum 30 characters. Mandatory if "Geo Coverage" field is national or sub-natl. Tanzania. For geographically-referenced data, this is the name of the sub-national area which is covered by the dataset. Free-text area names. Maximum 30 characters. Mandatory if "Geo Coverage" field is "sub-natl". Serengeti Minimum _ Longitude: Definition Format Status Example 68 For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Minimum_Longitude refers to the western-most longitude point covered, in signed decimal degrees. Floating point length = 8. Mandatory for geo-referenced data. -17.50 Guidelines for a National Institutional Survey - Document 2 Maximum Latitude: Definition Format Status Example For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Maximum_Latitude refers to the northern-most latitude point covered, in signed decimal degrees. Floating point length = 8. Mandatory for geo-referenced data. +37.10 Maximum Longitude: Definition Format Status Example For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Maximum_Longitude refers to the eastern-most longitude point covered, in signed decimal degrees. Floating point, length = 8. Mandatory for geo-referenced data. +51.30 Minimum Latitude: Definition Format Status Example For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Minimum_Latitude refers to the southern-most latitude point covered, in signed decimal degrees. Floating point of length = 8. Mandatory for geo-referenced data. -34.80 Abstract_Filename: Definition The full path name of the file containing the abstract text for the dataset. This is composed of unstructured text containing information about the dataset that cannot be recorded in the other metadata fields. Significant information should be included, such as the objectives of the data collection or study, scope, methodology, and major findings. Also included is a general discussion of the thematic contents of the dataset. Further fields to consider: Quality: Definition Format References: Definition Format Information about any quality procedures followed in producing the dataset or any other indicators as to the quality of the data. This includes a description of any known gaps or anomalies. Indicators include, but are not limited to: frequency of use; processing and quality assurance procedures; frequency of updates; number of peer reviewed articles; and any prior user-feedback. Free text. Key bibliographic references pertaining to the metadata entry. Use any bibliographic style, but be consistent. The style required by the Journal of Geophysical Research (JGR) is suggested. Maximum 2000 characters (25 lines, 80 characters per line) free text. ne ee Guidelines for a National Institutional Survey - Document 2 69 Example Kolenkiewiecz, R. and Martin, C. F. 1982, Seasat altimeter height calibration, J. Geophys. Res., 87 (C5), pp.3189-3198. Example of a completed Member metadatabase entry Member_ID: Dataset Name: Name: Type: Keywords: Start_Date: Stop_Date: Update_Date: Geo_ Coverage: Continent: Region: Country: Sub_Natl: Minimum Longitude: Maximum Latitude: Maximum Longitude: Minimum Latitude: Final_ Process: Process Source: Access_and_ Distrib: File_Size: File_Medium: Comments: 0012 African Protected Areas GIS Serengeti GIS Raster GIS GIS; ARC/INFO 1994-08-30 Sub-natl Africa Tropical Africa Tanzania Serengeti +33.80 -1.45 +35.20 -3.15 ARC/INFO export with no compression ARC/INFO coverage on VAX disk Public 3400 Various media Digitised from the 1:100,000 map "Serengeti National Park", 1987 Field definitions of Member metadata Member _ID: Definition Internal identification by which the member is catalogued within the metadatabase. Member ID numbers are assigned automatically by the system every time a new data member is added. This ID is not used in metadata exchange among organisations and as such is not an official part of the metadata format definition. However, it is part of the metadatabase system definition. Format Integer of length = 4. Status System generated. Example 0012 Dataset_Name: Definition Name of the dataset to which this data member is attached. A link may be set up from this field to the "Name" field of the Dataset metadata level. Format Maximum 50 characters. Status Mandatory. 70 Guidelines for a National Institutional Survey - Document 2 Example Name: Definition Format Status Example Type: Definition Format Status Example Keywords: Definition Format Status Example Start_Date: Definition Format Status Example Stop_Date: Definition Format Status Example World Conservation Monitoring Centre. The name given to the data member being described. The title should be descriptive enough to allow a reader to make a reasonable decision as to whether the data may be of interest. The name is a one-line description of a member, and should tell the user what is unique about this particular member/data file that distinguishes it from all other members of the same dataset. It may state the version in a series of data files, a special process, resolution or scale of a data file. Maximum 50 characters free text Mandatory Serengeti GIS The type of the member, selected from one of the following: report; tabular data; image; paper map; vector GIS; raster GIS. A ’raster’ member can be a raster map or classified (categorised) satellite image, whereas an ’image’ member is either raw satellite data or non-categorised, non-discrete data (eg vegetation indices). A ’vector’ member can consist of points, lines (arcs) or areas (polygons). Maximum 20 characters. Mandatory. Raster GIS. Keyword(s) are additional terms that describe and characterise the data member. Used for searching by the metadatabase. Use terminology lists where possible (eg Pinborg 1992; UNEP, 1990; WDC, 1991). Several terms may be entered if separated by semicolons. Optional. GIS; ARC/INFO. The beginning date for a temporal data member (eg satellite-based data collected over a period of weeks, months or years). In most cases of non- temporal data, it will be the same as the "Start_Date" at the Dataset metadata level. YYYY-MM-DD. Optional. 1986-06-31 The date on which the final process was executed. YYYY-MM-DD. Optional. 1986-08-31 Guidelines for a National Institutional Survey - Document 2 71 Update_Date: Definition Format Status Example The date when this metadata entity was last updated. YYYY-MM-DD. Mandatory. 1994-08-30 Geo_ Coverage: Definition Format Status Example Continent: Definition Format Status Example Region: Definition Format Status Example Country: Definition Format Status Example Sub_Natl: Definition Format Status Example For geo-referenced datasets, this is the coverage area selected from one of the following: global; continental; regional; national; sub-natl. Maximum 15 characters. Mandatory for geo-referenced datasets. Sub-natl. For geo-referenced datasets, this is the name of the continent in which the dataset occurs. Use INFOTERRA terminology list (UNEP, 1990). Maximum 30 characters. Mandatory if "Geo Coverage" field is continental, regional, national, sub-natl. Atlantic Ocean. For geo-referenced datasets, this is the geographic region in which the dataset occurs. Use INFOTERRA terminology list (UNEP, 1990). Maximum 30 characters. Mandatory if "Geo Coverage" field is regional, national, sub-natl. SE Asia. For geo-referenced datasets, this is the country in which the dataset occurs. Use United Nations standard country names (English language version). Maximum 30 characters. Mandatory if "Geo Coverage" field is national or sub-natl. Brazil. For geographically-referenced data, this is the name of the sub-national area which is covered by the dataset. Free-text area names. Maximum 30 characters. Mandatory if "Geo Coverage" field is "sub-natl". Serengeti National Park. Minimum Longitude: . Definition 72 For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Minimum_Longitude refers to the western-most longitude point covered, in signed decimal degrees. Guidelines for a National Institutional Survey - Document 2 Format Floating point length = 8. Status Mandatory for geo-referenced data. Example -17.50 Maximum Latitude: Definition For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Maximum_Latitude refers to the northern-most latitude point covered, in signed decimai degrees. Format Floating point length = 8. Status Mandatory for geo-referenced data. Example +37.10 Maximum Longitude: Definition For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Maximum_Longitude refers to the eastern-most longitude point covered, in signed decimal degrees. Format Floating point, length = 8. Status Mandatory for geo-referenced data. Example +51.30 Minimum Latitude: Definition For geo-referenced datasets, the four coverage fields indicate the spatial extent of the dataset. Minimum_Latitude refers to the southern-most latitude point covered, in signed decimal degrees. Format Floating point of length = 8. Status Mandatory for geo-referenced data. Example -34.80 Final_Process: Definition A one line description of the last processing step used to create the data member. Format Maximum 50 characters. Status Optional. Example ARC/INFO export with no compression. Process Source: Definition Description of the data file or other product used as input to the final process. Should enable users to determine the exact origin of the final data member. Format Maximum 50 characters. Status Optional. Examples ARC/INFO coverage on VAX disk. Printed reports sourced from UNEP. Access_and_Distrib: Definition A one word description of the dataset specifying its access and distribution rights, selected from: public (files in the public domain which can be freely Guidelines for a National Institutional Survey - Document 2 73 distributed); limited (files in the public domain but not for all users due to format, size considerations etc); source (files requiring source permission); in-house (files which are proprietary and cannot be distributed at all outside of the data centre). Format From selection (maximum 10 characters). Status Mandatory. Example Public. File Size: Definition The file size for each data member (electronic data files only) in its final storage format, in kilobytes rounded to the nearest integer. Format Integer of length = 4. Status Optional. Example 340 File Medium: Definition Type of medium on which the data file is stored at the institution. Include any special characteristics about the storage medium such as media (eg paper, hard disk, magnetic tape), and capacity. It should be noted that the storage medium may differ from that used for distribution. Format Maximum 50 characters. Status Optional. Example 270 Mb Seagate hard disk, 1.44 Mb 3.5" floppy disk, paper report. Comments: Definition This field may be used for a variety of purposes, typically to provide details on the data member not accounted for elsewhere. These might include the member’s processing history or origins, the reason why the data member was initially acquired or created, the name and scale of a source map, or the projection used for a GIS product. Format Maximum 250 characters. Status Optional. Example Digitised from the 1:100,000 map "Serengeti National Park", 1987. Metadatabase Updating Keeping the Institution metadata current should not be unduly laborious and can probably be verified by checking the validity of the contents with a phone call to the contact person at the institution. New institutions that appear or are "discovered" will need to be dealt with using the original questionnaire/site visit approach and then adding them to the country metadatabase. The Dataset and Member levels are best handled by sending a printout of the contents of the metadatabase to each institution, asking them to verify their entries and supply modifications and additions using the questionnaire format. 74 Guidelines for a National Institutional Survey - Document 2 Annex 7 References Pinburg, U. 1992. Catalogue of Data Sources (CDS) for the Environment: Analysis and Suggestions for a Meta-data System and Service. European Environment Agency (EEA). UNEP 1990. INFOTERRA Thesaurus of Environmental Terms (3rd ed.). UNEP, Nairobi. UNEP 1992. The Grid Meta-Database (MDb) Entity-Attribute Definitions. UNEP-GRID, Geneva. UNEP 1994. An Introduction to HEM and the HEMDisk (ed. Crain, I.K.). Office of Harmonization of Environmental Measurement. UNEP, Munich. World Data Center 1991. Directory Interchange Format Manual (version 4.0). World Data Center, NASA. Guidelines for a National Institutional Survey - Document 2 75 76 Guidelines for a National Institutional Survey - Document 2 ANNEX 8: LIST OF ACRONYMS & ABBREVIATIONS CBD Convention on Biological Diversity CDS Catalog of Data Sources (EEA) aS CIESIN Consortium for International Earth Science Information Network DIF Directory Interchange Format EEA European Environment Agency GEF Global Environment Facility GIS Geographical Information System IUCN World Conservation Union NASA National Aeronautics and Space Administration (US) DIF Directory Interchange Format (NASA) NBU National Biodiversity Unit NGO Non-Governmental Organisation RDBMS Relational Database Management System UNEP United Nations Environment Programme GRID Global Resources Information Database (UNEP) HEM Harmonization of Environmental Measurement (UNEP) WCMC World Conservation Monitoring Centre WOCE World Ocean Circulation Experiment NB See also the index of acronyms and abbreviations in the Resource Inventory (Document 4). en ee eS Guidelines for a National Institutional Survey - Document 2 77 9 alee ‘ ‘Tota WORLD CONSERVATION . MONITORING CENTRE World Conservation Monitoring Centre - 219 Huntingdon Road iy Teaee Cambridge CB3 ODL on. United Kingdom Seige Telephone +44 223 277314 Fax +44 223 277136 the Earth: TUCN-The World Conservation Union, UNEP- United Nations Programme, and WWF-World Wide Fund for Nature. erly >