1. BEDES & SEED Building Energy Data Exchange Specification & Standard Energy Efficiency Data Platform April 14, 2015 Robin Mitchell Lawrence Berkeley National Laboratory

2. BEDES Building Energy Data Exchange Specification

3. What is BEDES ? BEDES == Building Energy Data Exchange Specification BEDES provides a common set of data terms, definitions and field formats that can be used by public and private software tools, data schemas and databases working within the building energy performance sector.

4. Motivation for BEDES 4 Problem Ambiguity of data definitions (i.e. gross floor area) High transactions costs of sharing and aggregating data Stunted market by lack of empirical data Solution Enable exchange, comparison, and combination of data Provide common terms and definitions for data Reduce costs in the building efficiency sector Facilitate software development and interoperability

5. BEDES Use Cases -- Initial 5 Building Performance Tracking The implementation of disclosure policies for public or private buildings requires public officials to collect, clean and analyze massive amounts of data, then share portions of it with the public Energy Efficiency Investment Decision-Making Owners and managers use building energy performance information to assess capital and operational opportunities in individual buildings, develop energy strategies across portfolios, and identify trends in local real estate markets. Efficiency Program Implementation Evaluation Energy efficiency programs often provide incentives or technical assistance to support owners' data collection and analysis activities. They also use data to conduct program design and outreach, track project performance, and evaluate programs.

6. BEDES Beta developed for use by the DOE 6 Originally developed to improve interoperability of DOE's software tools and data collection efforts DOE scoping study confirmed that BEDES would be useful to stakeholders outside DOE Lawrence Berkeley National Lab led a technical working group process to develop BEDES Beta After 9 months of extensive review and feedback, BEDES 1.0 was released in October 2014

7. BEDES Dictionary 7 What it Is Data Terms Term Definitions Units of Measure Data Types “Dictionary” What it Is Not Database Schema – Relational – Hierarchical “Grammar Guide” BEDES Dictionary is a collection of terms and definitions designed to facilitate the use and sharing of empirical building characteristics and energy performance data among software tools and data collection and analysis activities more easily, consistently, and at lower cost.

8. BEDES Website: bedes.lbl.gov 8

9. Mapping to BEDES 9 Mapping documents the relationships between the terms and definitions used in a product and the associated BEDES terms. Multiple BEDES terms may be needed to fully define a field in an implementation.

10. BEDES Dictionary Scope 10 Fully Harmonized Partially Harmonized BEDES Dictionary Application Mapping BEDES Dictionary Application Mapping

11. BEDES Compliance 11 Mapping Compliance documents the relationship between BEDES terms and application fields Exchange Compliance establishes a schema for exchanging that information electronically.

12. BEDES Adoption / Mappings 12

13. Using BEDES 13

14. Get Involved ! 14 Develop BEDES-Compliant products – we can help! Become and Endorser Tell us how you’re using BEDES Share your thoughts on the BEDES Forum Develop terms & definitions for new areas Spread the word! bedes@ee.doe.gov buildings.energy.gov/bedes

15. SEED Standard Energy Efficiency Data Platform

16. The SEED Team!

17. SEED is designed to help state and local governments implement building performance policies and programs for private and/or public buildings. In the future it could be used by large portfolio owners, energy efficiency programs, utilities, and energy efficiency service providers. The Standard Energy Efficiency Data Platform San Francisco Los Angeles Washington D.C. New York City Philadelphia

18. Value of SEED GOAL – to make data and systems interoperable A free, open-source, web-enabled software application that helps organizations easily aggregate, clean, track, and share data on the energy performance of large groups of buildings. Reduces upfront cost of storing and managing data in a private, secure way Standard, vendor neutral, objective Addresses workflow management and relieves administrative burden Data cleansing process increases data quality and saves staff time Common format facilitates sharing and collaboration

19. U.S. Benchmarking Policy Landscape Berkeley

20. Seattle Benchmarking Example

21. Policy Progression Benchmarking often serves as the foundation for a complimentary suite of energy efficient policies Benchmarking Retro- commissioning Energy AuditsGreen LeasingSub-metering Certification of Building Operators Energy Efficient Municipal Portfolio Lighting Upgrades Energy Efficiency Upgrades Energy Code Compliance

22. Where you start… Building Use Information Utility Data Tax Assessor Data Audit Data Contact Information Retrocommissioning Benchmarking Results

24. Operational Information Utility Data SEED (Local or Cloud Instance) City/Organization Staff Tax records City/Organization Software Tools Third-Party Apps & Tools Audit Data Audit Tools SEED Plug-ins (Add-on features) Public SEED Workflow Direct entry/upload Automated connection User access API

25. Apps and Tools

26. Data editing, matching and updating Import, reconcile and match records from Portfolio Manager and other sources View/edit all data for given building and/or for select periods of time View which records do and do not meet a minimum set of compliance checks Audit trail to show history of data edits Ability to add new data fields Label and group records Data reporting and exporting Ability to export data in various formats Publishing to third-parties and the public via the API Platform Architecture Host on local servers or cloud Open-source software Plug-in framework for third-party software extensions Multiple levels of user access and control SEED v1.1

27. Core Use Case -- Benchmarking 5 pilot cities Working with them intensively Testing in parallel with existing system A lot of interest in other use cases Audit data Interval data Real estate data (MLS) Third party developers Several organizations looking at code Visualization / mapping Scalability No technical barriers Data Quality is an issue SEED 1.1

28. SEED Login Page

29. More information 29 email SEED-Support@lbl.gov for more information