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Chapter 5 ; The Shared Environmental Information System (SEIS) is a collaborative initiative of the European Commission (EC) and the European Environment Agency (EEA) aimed to establish an integrated and shared EU-wide environmental information system together with the Member States. SEIS presents the European vision on environmental information interoperability. It is a set of high-level principles & workflow-processes that organize the collection, exchange, and use of environmental data & information aimed to: • Modernise the way in which information required by environmental legislation is made available to member states or EC instruments; • Streamline reporting processes and repeal overlaps or obsolete reporting obligations; • Stimulate similar developments at international conventions; • Standardise according to INSPIRE when possible; and • Introduce the SDI (spatial database infrastructure) principle EU-wide. SEIS is a system and workflow of operations that offers technical capabilities geared to meet concept expectations. In that respect, SEIS shows the way and sets up the workflow effectively in a standardise way (e.g, INSPIRE) to: • Collect Data from Spatial Databases, in situ sensors, statistical databases, earth observation readings (e.g., EOS, GMES), marine observation using standard data transfer protocols (ODBC, SOS, ft p, etc). • Harmonise collected data (including data check/data integrity) according to best practices proven to perform well, according to the INSPIRE Directive 2007/2/EC (1) Annexes I: II: III: plus INSPIRE Implementation Rules for data not specified in above mentioned Annexes. • Harmonise collected data according to WISE (Water Information System from Europe) or Ozone-web. • Process, aggregate harmonise data so to extract information in a format understandable by wider audiences (e.g., Eurostat, enviro-indicators). • Document information to fulfi l national reporting obligations towards EU bodies (e.g., the JRC, EEA, DGENV, Eurostat) • Store and publish information for authorised end-users (e.g., citizens, institutions). This paper presents the development and integration of the SEIS-Malta Geoportal. The first section outlines EU Regulations on INSPIRE and Aarhus Directives. The second covers the architecture and the implementation of SEIS-Malta Geoportal. The third discusses the results and successful implementation of the Geoportal. ; peer-reviewed

SEIS-Malta system (Shared Environmental Information System (SEIS) and web-based GIS interface) forms part of a global project on environmental monitoring funded under the 2007- 2013 Structural Funds Programme for Malta. • The project "Developing national environmental infrastructure and capacity", is co-financed by the European Regional Development Fund (ERDF) which provides 85% of the project's funding and the Government of Malta, which finances the rest under Malta's Operational Programme I - Cohesion Policy 2007- 2013 "Investing in Competitiveness for a Better Quality of Life". ; peer-reviewed

This presentation was given at FOSS4G Europe 2017 conference (http://europe.foss4g.org/2017). It presents the first findings of the project giCASES - Creating a University-Enterprise Alliance for a Spatially Enabled Society (http://gicases.eu), which is a Knowledge Alliance project funded under the Erasmus+ Programme of the European Commission. The key point of giCASES approach is the introduction of a case-based learning approach in education, based on the co-creation of knowledge between universities and enterprises working in the field of Geographic Information. More information can be found in the paper submitted for the Academic Track of FOSS4G Europe 2017, which is available under a CC-BY 4.0 license at https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W2/129/2017. ; This work was supported by the project "giCASES – Creating a University-Enterprise Alliance for a Spatially Enabled Society", co-funded by the Erasmus+ Programme of the European Union, Knowledge Alliances N° 562657-EPP-A-2015-1-IT-EPPKA2-KA.

A bottom-up electricity characterisation methodology of the building stock at the local level is presented. It is based on the statistical learning analysis of aggregated energy consumption data, weather data, cadastre, and socioeconomic information. To demonstrate the validity of this methodology, the characterisation of the electricity consumption of the whole province of Lleida, located in northeast Spain, is implemented and tested. The geographical aggregation level considered is the postal code since it is the highest data resolution available through the open data sources used in the research work. The development and the experimental tests are supported by a web application environment formed by interactive user interfaces specifically developed for this purpose. The paper's novelty relies on the application of statistical data methods able to infer the main energy performance characteristics of a large number of urban districts without prior knowledge of their building characteristics and with the use of solely measured data coming from smart meters, cadastre databases and weather forecasting services. A data-driven technique disaggregates electricity consumption in multiple uses (space heating, cooling, holidays and baseload). In addition, multiple Key Performance Indicators (KPIs) are derived from this disaggregated energy uses to obtain the energy characterisation of the buildings within a specific area. The potential reuse of this methodology allows for a better understanding of the drivers of electricity use, with multiple applications for the public and private sector. ; This work emanated from research conducted with the fi-nancial support of the European Commission through the H2020project BIGG , grant agreement 957047, and the JRC Expert Con-tractCT-EX2017D306558-102.D.ChemisanathanksICREAfortheICREA Acadèmia. Dr J. Cipriano also thanks the Ministerio deCiencia e Innovación of the Spanish Government for the Juan dela Cierva Incorporación grant