The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources.
The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources.
Two new global urban products have recently appeared: the Global Urban Footprint (GUF) and the Global Human Settlement Layer (GHSL). This paper evaluates the GUF and GHSL for the city of Milan, Italy through comparison with two European Union (EU) land use/cover reference products, namely the Urban Atlas and LUCAS. The results demonstrate that the GUF and GHSL are very similar to each other and, with some exceptions, show overall good agreement with the reference datasets. This study will be extended to other European cities in the future.
In the sector of Geographic Information (GI) there is a gap between the education and training currently being offered by European universities and the knowledge and skills required by enterprises and public authorities. New forms of collaboration based on innovative methods are needed to cope with the challenges derived from the fast technological developments in the geospatial and ICT field. This paper presents the approach and the first findings of the EU Erasmus+ project giCASES – Creating a University-Enterprise Alliance for a Spatially Enabled Society (2016–2018) which addresses this challenge by introducing new methods for case-based and collaborative learning, and for the co-creation, management and sharing of knowledge between universities and enterprises. The aim of the project is to develop new training material and create innovative, multi-disciplinary learning processes based on real-world case studies (case-based learning). The paper focuses on the methodological approach developed during the first half of the project, and presents the 6 case studies where this approach will be tested during the second half. Despite the diversity of application domains (indoor mapping, environmental hazards, e-Government, utility networks, energy saving policies, and forestry), the case studies are all relevant to open source software and FOSS4G technologies will play a key role in their implementation, thus demonstrating their matureness and flexibility not only as GI teaching tools at the universities, but also as powerful means to develop innovative new services at the companies.
Minghini, M., Brovelli, M. A., Vandenbroucke, D., Carbonaro, M., Prüller, S., Painho, M., . Frigne, D. (2017). FOSS4G as a key building block for case-based learning in geographic information education. In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives): FOSS4G-Europe 2017 – Academic Track (Vol. 42, pp. 129-135) https://doi.org/10.5194/isprs-archives-XLII-4-W2-129-2017 ; In the sector of Geographic Information (GI) there is a gap between the education and training currently being offered by European universities and the knowledge and skills required by enterprises and public authorities. New forms of collaboration based on innovative methods are needed to cope with the challenges derived from the fast technological developments in the geospatial and ICT field. This paper presents the approach and the first findings of the EU Erasmus+ project giCASES - Creating a University-Enterprise Alliance for a Spatially Enabled Society (2016-2018) which addresses this challenge by introducing new methods for case-based and collaborative learning, and for the co-creation, management and sharing of knowledge between universities and enterprises. The aim of the project is to develop new training material and create innovative, multi-disciplinary learning processes based on real-world case studies (case-based learning). The paper focuses on the methodological approach developed during the first half of the project, and presents the 6 case studies where this approach will be tested during the second half. Despite the diversity of application domains (indoor mapping, environmental hazards, e-Government, utility networks, energy saving policies, and forestry), the case studies are all relevant to open source software and FOSS4G technologies will play a key role in their implementation, thus demonstrating their matureness and flexibility not only as GI teaching tools at the universities, but also as powerful means to develop innovative new services at the companies. ; publishersversion ; published
In the sector of Geographic Information (GI) there is a gap between the education and training currently being offered by European universities and the knowledge and skills required by enterprises and public authorities. New forms of collaboration based on innovative methods are needed to cope with the challenges derived from the fast technological developments in the geospatial and ICT field. This paper presents the approach and the first findings of the EU Erasmus+ project giCASES – Creating a University-Enterprise Alliance for a Spatially Enabled Society (2016–2018) which addresses this challenge by introducing new methods for case-based and collaborative learning, and for the co-creation, management and sharing of knowledge between universities and enterprises. The aim of the project is to develop new training material and create innovative, multi-disciplinary learning processes based on real-world case studies (case-based learning). The paper focuses on the methodological approach developed during the first half of the project, and presents the 6 case studies where this approach will be tested during the second half. Despite the diversity of application domains (indoor mapping, environmental hazards, e-Government, utility networks, energy saving policies, and forestry), the case studies are all relevant to open source software and FOSS4G technologies will play a key role in their implementation, thus demonstrating their matureness and flexibility not only as GI teaching tools at the universities, but also as powerful means to develop innovative new services at the companies.
In the sector of Geographic Information (GI) there is a gap between the education and training currently being offered by European universities and the knowledge and skills required by enterprises and public authorities. New forms of collaboration based on innovative methods are needed to cope with the challenges derived from the fast technological developments in the geospatial and ICT field. This paper presents the approach and the first findings of the EU Erasmus+ project giCASES – Creating a University-Enterprise Alliance for a Spatially Enabled Society (2016–2018) which addresses this challenge by introducing new methods for case-based and collaborative learning, and for the co-creation, management and sharing of knowledge between universities and enterprises. The aim of the project is to develop new training material and create innovative, multi-disciplinary learning processes based on real-world case studies (case-based learning). The paper focuses on the methodological approach developed during the first half of the project, and presents the 6 case studies where this approach will be tested during the second half. Despite the diversity of application domains (indoor mapping, environmental hazards, e-Government, utility networks, energy saving policies, and forestry), the case studies are all relevant to open source software and FOSS4G technologies will play a key role in their implementation, thus demonstrating their matureness and flexibility not only as GI teaching tools at the universities, but also as powerful means to develop innovative new services at the companies.
Nel settore dell'Informazione Geografica (GI), esiste in generale un gap a livello europeo tra l'istruzione e la preparazione offerte dalle università e le competenze e capacità richieste sul mercato da aziende ed enti pubblici. Per far fronte alle nuove sfide poste dai continui sviluppi tecnologici in atto (basti pensare a temi quali Geo Big Data, posizionamento indoor, Internet of Things, ecc.) è perciò necessario introdurre nuove forme di collaborazione università-impresa. giCASES – Creation of a University-Enterprise Alliance for a Spatially Enabled Society (http://www.gicases.eu) è un'Alleanza per le Conoscenze, co-finanziata dal Programma UE Erasmus+, che affronta questo problema con l'obiettivo di sviluppare approcci innovativi e multidisciplinari all'insegnamento e all'apprendimento nel settore GI facilitando lo scambio, il flusso e la co-creazione di conoscenza. L'approccio consiste nello sviluppo collaborativo e condiviso, tra università ed imprese, di nuovi materiali didattici e processi di apprendimento basati su casi reali (case-based learning). In maniera innovativa rispetto alle tradizionali forme di collaborazione tra università ed imprese (spesso limitate a semplici tirocini e allo sviluppo di tesi presso le imprese), la collaborazione con le università finalizzata alla co-creazione di conoscenza si esplica sin dalla fase iniziale di progettazione del corso accademico e del processo di apprendimento. Il progetto, iniziato nel 2016 e formato da un consorzio di 14 partner da 8 diversi Paesi europei (con una componente bilanciata di università e imprese), ha visto una prima fase volta alla definizione della metodologia di case-based learning e alla progettazione dei casi di studio. Un questionario inizialmente distribuito tra università, imprese ed enti pubblici europei nel settore GI ha evidenziato che: a) la collaborazione tra il settore accademico e quello industriale è spesso organizzata in modo tradizionale; b) le competenze richieste dal mercato del lavoro (specialmente programmazione, analisi e modellazione spaziale) spesso non sono in linea con l'istruzione universitaria; c) l'apprendimento basato su casi reali è uno dei metodi suggeriti per rendere la preparazione degli studenti conforme alle richieste del mondo del lavoro. Utilizzando lo standard BPMN (Business Process Model and Notation), è stata quindi sviluppata una metodologia rigorosa per la modellazione degli schemi di co-creazione di conoscenza tra università ed imprese (ad esempio per lo sviluppo collaborativo del materiale didattico e la formazione congiunta degli studenti). Questi schemi descrivono analiticamente i processi di collaborazione utilizzati, i relativi attori e le loro reciproche interazioni. Un insieme di linee guida, modelli e bozze di convenzioni/accordi è stato prodotto per facilitare l'implementazione pratica degli schemi sviluppati. Parallelamente, è stata definita e condivisa una serie di strumenti software per garantire funzionalità collaborative (sviluppo congiunto di codice, produzione congiunta di materiale didattico, ecc.), facilitando così lo sviluppo pratico di conoscenze condivise e la messa in opera dei casi di studio. Il materiale didattico e la metodologia di apprendimento sviluppati sono infine sottoposti ad un'accurata fase di test e validazione (al momento in corso) tramite l'implementazione in 6 casi di studio (CS), ognuno dei quali prevede la partecipazione congiunta di un partner accademico ed uno industriale e si concentra su un tema attuale nel panorama GI: CS1 "Use of indoor GIS in healthcare"; CS2 "Environmental analysis using cloud service system"; CS3 "From INSPIRE to e-Government"; CS4 "Integrated management of the underground"; CS5 "Harmonizing data flows in Energy saving EU policies"; CS6 "GIS applications in Forestry". Per ognuno di essi è stato definito un dettagliato piano di lavoro comprendente la descrizione degli attori coinvolti (studenti, professori, tutor accademici, tutor industriali, ecc.), il contesto applicativo (ovvero la modalità con cui il CS è incluso nel corso/programma accademico), le tempistiche di svolgimento e i risultati attesi. Questi ultimi, che includono il materiale didattico e i processi collaborativi applicati, saranno resi disponibili con licenza aperta sulla piattaforma del progetto, in modo da massimizzarne l'adozione da parte di altre comunità e portatori di interesse. I risultati parziali ottenuti dall'implementazione dei CS stanno dimostrando, a giudizio non solo degli studenti ma di tutti gli attori coinvolti, elementi positivi in termini di innovazione ed efficacia. Benché l'uso di software open source (e in particolare FOSS4G) non fosse formalmente richiesto dalle specifiche del progetto, è interessante notare come in tutti i 6 CS sia largamente prevista l'adozione di tali tecnologie, in particolare di QGIS, GRASS GIS, PostGIS, GeoServer, OpenLayers, Leaflet e Geomajas. Ciò testimonia come le soluzioni open source siano già fortemente utilizzate tanto come strumenti didattici presso le università quanto, da parte delle imprese, come mezzi per realizzare prodotti da immettere sul mercato. Si può anzi affermare che il software open source (che, oltre all'ecosistema FOSS4G, comprende in questo contesto strumenti di condivisione e documentazione di codice, piattaforme di e-Learning e strumenti di Project Management) sia un elemento essenziale per il case-based learning. Non solo: le comunità ed i progetti open source sono per natura un habitat ideale per la co-creazione di conoscenza, fondandosi essi stessi sull'idea della creazione collaborativa del software per il bene comune. Il progetto giCASES, tra i cui partner figurano membri attivi della Open Source Geospatial Foundation (OSGeo), intende fare tesoro di queste esperienze per assicurare il successo dei propri risultati.
