Resource Watch Data Policy and Submission Guidelines
This is a guide to how we prioritize, source, and integrate data into Resource Watch.
Guiding Principles
Resource Watch strives to curate data that allow anyone to monitor the state of our planet and make better decisions for a more sustainable future. We seek to develop and acquire data that cover a diverse range of themes for a wide audience that are:
- Open: Data that can be freely used, reused, and redistributed
- Relevant: Data that help answer questions to address urgent, global challenges
- Reliable: Peer-reviewed or official government data produced by transparent, established methodologies
- Timely: Most up-to-date and complete information available
Which topics do Resource Watch datasets cover?
We are interested in a wide range of themes and issues related to natural resources, ecosystems, and human well-being. Examples of topics of interest include:
- Biodiversity
- Cities and Settlements
- Climate
- Commerce and Trade
- Conflict and Migration
- Economic Development
- Energy
- Extreme Events and Disasters
- Food and Agriculture
- Forests
- Governance
- Health
- Infrastructure
- Land Cover and Classification
- Oceans
- Population and Human Development
- Water
How does Resource Watch acquire new data?
The Resource Watch team works with topic experts at WRI and partner organizations to identify key datasets that can be used to drive a more sustainable future. Data on Resource Watch come from a variety of sources, including, research institutes, government agencies, academic institutions, intergovernmental organizations, civil society groups, and scientific journals and reports. To acquire new data, we
- Search and incorporate publicly available open data,
- Form partnerships to move data into the public domain,
- Fund the creation of datasets to fill key gaps, and
- Apply cutting-edge science and technology to produce new data.
What are the preferred dataset attributes on Resource Watch?
We assesses datasets across a number of quality indicators, including accuracy and completeness, relevance, timeliness, and geographic coverage. We are especially interested in datasets that fill gaps in our topical coverage, as well as datasets that are more recent or higher resolution than what we currently have. Preferred dataset attributes include:
- Relevant to development or natural resource management decisions,
- Peer-reviewed, transparent, and based on an established methodology,
- Global or the largest geographic coverage possible,
- Highest spatial resolution of its kind,
- Frequently updating or most recent data available,
- Long historical record, and
- Georeferenced or place-based.
How does Resource Watch make sure that datasets are up to date?
We use the several strategies to make sure that datasets on the platform stay up-to-date, such as automatic updates from sources with reliable data services, periodic inventories and manual updates for select datasets, reports from data sources, and crowdsourced recommendations and dataset feedback. If you know of more recent or newer data sources, please let us know.
What is the process for selecting new datasets to be part of Resource Watch?
The Resource Watch team uses the following workflow to evaluate, integrate, and review datasets to have them featured on the platform:
- Evaluate data based on our guiding principles and preferred dataset attributes,
- Work with data provider to establish permission to visualize and distribute the data,
- Document metadata,
- If needed, process, clean, reformat, and host data for visualization, or build software connectors to dataset sources,
- Select and create map layers and charts,
- Solicit quality control review on readability, consistency, and accuracy from WRI topic experts and respond to data quality issues, and
- Explore the possibility of writing a blog to show how the data can be used.
When there are multiple datasets covering the same topic, we generally select and host only the one that meets the most number of preferred dataset attributes. However, additional datasets may be included when their methodology or format differs in a way that can help answer different questions.
How are datasets processed and displayed on Resource Watch?
When necessary, we process datasets to allow optimal visualization and interaction with the datasets on the platform:
- For country-level vector or tabular datasets, only data for the 193 United Nations (UN) member states are visible.
- For country-level tabular datasets, regional or global summary entries are removed.
- For datasets with historical records, tables are converted to long-form data frames, where each row is one time point per subject, so that tables can be more easily queried for graphing.
For multidimensional datasets, we often display a subset of the dataset on the map. We use the following guidelines for creating map layers:
- The most recent data and as far back as possible,
- The greatest coverage, and
- The most important indicators of the subject.
Resource Watch allows users to access the full dataset and additional information with links to original data sources and downloads.
What type of metadata does Resource Watch require?
For each dataset, we provide the following information.
- Public Title: Readable nontechnical name of dataset
- Technical Title: Title with technical specifications
- Source Organizations: Attribution for the dataset
- Function: A brief description of how to use the data and what they represent
- Learn More: Link to data description page from the source
- Download from Source (optional): Link to download data from the source
- Description: Description or abstract of data objectives, methodology, and other key specifications
- Cautions: Limitation on methodology, inconsistency (e.g., input), geographic coverage, content coverage, and other use cases
- Geographic Coverage: Geographic coverage (e.g., global, select countries)
- Data Type: Data format (raster, vector, tabular)
- Spatial Resolution: cell size (rasters) or unit of analysis (e.g., national, subnational, etc.)
- Date of Content: Date or time period that the data represent
- Frequency of Updates: How often the data are updated
- License: License for data use
- Suggested Citation: How a user should cite the data, including authorship and source
- Published Title (if not English): Title in original language