3,019 research outputs found
La politica degli Anicii nel V secolo
No full textLa dialettica politica tra Anicii filopapali e Ceionii filobizantini tra Alarico e Teoderic
Livio e la storia universale
No full textThe Roman conception of history, extending from Cato down to the Augustan age and Livy, rejects the Hellenic idea of 'universal history', and embraces an alternative declination based on the postulate that the Romans were a 'chosen people', whose universal rule gathered the whole humankind and had to be willingly accepted. Rome's special place in world history derives from the gods and historians writing on Rome have to confirm that history is guided by a meta-historical will
Integrazione di dati on-demand
No full textSempre più spesso aziende e organizzazioni basano le proprie decisioni sui dati di cui dispongono. Garantire la qualità di tali dati è fondamentale per poter effettuare analisi accurate e affidabili. L'integrazione dei dati consiste nel combinare dati acquisiti da molteplici sorgenti eterogenee per fornire all'utente finale una vista unitaria e coerente su tali dati. Si tratta perciò di un processo fondamentale per incrementare il valore dei dati disponibili. In passato, operando su numeri limitati di sorgenti, il paradigma di riferimento, noto come ETL, richiedeva di estrarre i dati grezzi, pulirli e immagazzinarli in un data warehouse per poterli poi analizzare. Al giorno d'oggi, operando su milioni di sorgenti, è sempre più diffuso il paradigma noto invece come ELT, per il quale i dati grezzi vengono raccolti in grandi quantità e immagazzinati così come sono, ad esempio in un data lake. Gli utenti possono poi pulire le porzioni di dati utili per le loro applicazioni. È pertanto necessario studiare soluzioni innovative per l'integrazione dei dati, maggiormente adatte alle nuove sfide che tale modello comporta.
Uno dei processi fondamentali per l'integrazione dei dati è la riconciliazione di entità, che consiste nell'individuare i profili che descrivono la stessa entità reale (duplicati) per consolidarli in un unico profilo coerente. Tradizionalmente, questo processo viene effettuato sull'intero dataset prima di poter operare su di esso, risultando perciò spesso molto costoso. In molti casi, solo una porzione delle entità pulite si rivela utile per l'applicazione dell'utente finale. Ad esempio, operando su dati raccolti dal Web, è fondamentale poter filtrare le entità d'interesse senza dover pulire l'intera mole di dati, in continua crescita. Allo stesso modo, quando si effettuano interrogazioni su un data lake, si vuole pulire su richiesta solo la porzione di interesse, ottenendo i relativi risultati nel minor tempo possibile. Per rispondere a tali esigenze presentiamo BrewER, un framework per eseguire interrogazioni SQL su dati sporchi emettendo progressivamente i risultati come se fossero stati ottenuti sui dati puliti. BrewER focalizza il processo di pulizia su un'entità alla volta, in base a una priorità definita dall'utente nella clausola ORDER BY. Per molte applicazioni, come l'esplorazione dei dati, BrewER consente di risparmiare una grande quantità di tempo e risorse.
I duplicati non esistono però solo a livello di singoli profili, ma anche a livello di dataset. È infatti comune ad esempio che un data scientist per le proprie analisi effettui trasformazioni su un dataset presente nel data lake aziendale, immagazzinando poi anche la nuova versione ottenuta all'interno del data lake stesso. Situazioni simili si verificano nel Web, ad esempio su Wikipedia, dove le tabelle vengono spesso duplicate e le copie ottenute hanno uno sviluppo indipendente, con la possibile insorgenza di inconsistenze. Individuare automaticamente queste tabelle duplicate consente di renderle coerenti con operazione di pulizia dei dati o propagazione delle modifiche, oppure di rimuovere le copie ridondanti per liberare spazio di archiviazione o risparmiare futuro lavoro agli editori. La ricerca di tabelle duplicate è stata perlopiù ignorata dalla letteratura esistente. Per colmare questa mancanza presentiamo Sloth, un framework che, date due tabelle, consente di determinarne la più grande sottotabella in comune, consentendo di quantificarne la similarità e di rilevare le possibili inconsistenze.
BrewER e Sloth rappresentano soluzioni innovative per l'integrazione dei dati nello scenario ELT, utilizzando le risorse a disposizione su richiesta e indirizzando il processo di integrazione dei dati verso un approccio orientato alle applicazioni.Companies and organizations depend heavily on their data to make informed business decisions. Therefore, guaranteeing high data quality is critical to ensure the reliability of data analysis. Data integration, which aims to combine data acquired from several heterogeneous sources to provide users with a unified consistent view, plays a fundamental role to enhance the value of the data at hand. In the past, when data integration involved a limited number of sources, ETL (extract, transform, load) established as the most popular paradigm: once collected, raw data is cleaned, then stored in a data warehouse to perform analysis on it. Nowadays, big data integration needs to deal with millions of sources; thus, the paradigm is more and more moving towards ELT (extract, load, transform). A huge amount of raw data is collected and directly stored (e.g., in a data lake), then different users can transform portions of it according to the task at hand. Hence, novel approaches to data integration need to be explored to address the challenges raised by this paradigm.
One of the fundamental building blocks for data integration is entity resolution (ER), which aims at detecting profiles that describe the same real-world entity, to consolidate them into a single consistent representation. ER is typically employed as an expensive offline cleaning step on the entire data before consuming it. Yet, determining which entities are useful once cleaned depends solely on the user's application, which may need only a fraction of them. For instance, when dealing with Web data, we would like to be able to filter the entities of interest gathered from multiple sources without cleaning the entire continuously growing data. Similarly, when querying data lakes, we want to transform data on-demand and return results in a timely manner. Hence, we propose BrewER, a framework to evaluate SQL SP queries on dirty data while progressively returning results as if they were issued on cleaned data. BrewER tries to focus the cleaning effort on one entity at a time, according to the priority defined by the user through the ORDER BY clause. For a wide range of applications (e.g., data exploration), a significant amount of resources can therefore be saved.
Further, duplicates not only exist at profile level, as in the case for ER, but also at dataset level. In the ELT scenario, it is common for data scientists to retrieve datasets from the enterprise’s data lake, perform transformations for their analysis, then store back the new datasets into the data lake. Similarly, in Web contexts such as Wikipedia, a table can be duplicated at a given time, with the different copies having independent development, possibly leading to the insurgence of inconsistencies. Automatically detecting duplicate tables would allow to guarantee their consistency through data cleaning or change propagation, but also to eliminate redundancy to free up storage space or to save additional work for the editors. While dataset discovery research developed efficient tools to retrieve unionable or joinable tables, the problem of detecting duplicate tables has been mostly overlooked in the existing literature. To fill this gap, we therefore present Sloth, a framework to efficiently determine the largest overlap (i.e., the largest common subtable) between two tables. The detection of the largest overlap allows to quantify the similarity between the two tables and spot their inconsistencies.
BrewER and Sloth represent novel solutions to perform big data integration in the ELT scenario, fostering on-demand use of available resources and shifting this fundamental task towards a task-driven paradigm
La Grecia negli scritti di Pierviviano Zecchini
No full textPierviviano Zecchini, medico formatosi a Padova, rappresenta il viaggiatore vissuto tra Settecento e Ottocento che raggiunse la Grecia per motivi professionali e contribuì alla conoscenza di quel mondo attraverso la sua opera, I Quadri della Grecia. L’opera dello Zecchini aggiunge una nota a quella corrente filellenica che caratterizza il periodo di fine Settecento e testimonia dell'interesse a un momento storico di riscoperta del mondo antico e delle vicende ad esso connesse. Fu anche in rapporto con Besenghi degli Ughi e il Tommaseo
Task-Driven Big Data Integration
No full textData integration aims at combining data acquired from different autonomous sources to provide the user with a unified view of this data. One of the main challenges in data integration processes is entity resolution, whose goal is to detect the different representations of the same real-world entity across the sources, in order to produce a unique and consistent representation for it. The advent of big data has challenged traditional data integration paradigms, making the offline batch approach to entity resolution no longer suitable for several scenarios (e.g., when performing data exploration or dealing with datasets that change with a high frequency). Therefore, it becomes of primary importance to produce new solutions capable of operating effectively in such situations.
In this paper, I present some contributions made during the first half of my PhD program, mainly focusing on the design of a framework to perform entity resolution in an on-demand fashion, building on the results achieved by the progressive and query-driven approaches to this task. Moreover, I also briefly describe two projects in which I took part as a member of my research group, touching on some real-world applications of big data integration techniques, to conclude with some ideas on the future directions of my research
Big Data Integration & Data-Centric AI for eHealth
No full textLa big data integration, ovvero l’integrazione di grandi quantità di dati provenienti da molteplici sorgenti, rappresenta una delle principali sfide per l’impiego di tecniche e strumenti basati sull’intelligenza artificiale in ambito medico (eHealth). In questo contesto risulta inoltre di primaria importanza garantire la qualità dei dati su cui operano tali strumenti e tecniche (Data-Centric AI), che rivestono un ruolo ormai centrale nel settore. Le attività di ricerca del Database Group (DBGroup) del Dipartimento di Ingegneria "Enzo Ferrari" dell’Università degli Studi di Modena e Reggio Emilia si muovono in questa direzione. Presentiamo quindi i principali progetti di ricerca del DBGroup nel campo dell’eHealth, che si inseriscono nell’ambito di collaborazioni in diversi settori applicativi
Progressive Query-Driven Entity Resolution
No full textEntity Resolution (ER) aims to detect in a dirty dataset the records that refer to the same real-world entity, playing a fundamental role in data cleaning and integration tasks. Often, a data scientist is only interested in a portion of the dataset (e.g., data exploration); this interest can be expressed through a query. The traditional batch approach is far from optimal, since it requires to perform ER on the whole dataset before executing a query on its cleaned version, performing a huge number of useless comparisons. This causes a waste of time, resources and money. Proposed solutions to this problem follow a query-driven approach (perform ER only on the useful data) or a progressive one (the entities in the result are emitted as soon as they are solved), but these two aspects have never been reconciled. This paper introduces BrewER framework, which allows to execute clean queries on dirty datasets in a query-driven and progressive way, thanks to a preliminary filtering and an iteratively managed sorted list that defines emission priority. Early results obtained by first BrewER prototype on real-world datasets from different domains confirm the benefits of this combined solution, paving the way for a new and more comprehensive approach to ER
Analysis of the driver's stress level while driving in Truck Platooning
No full textThe logistic is interested by changes and truck manufacturers are investing in solutions such as truck platooning. This system leads to benefits (fuel consumption, safety, traffic efficiency). The paper presents the analysis of the psychophysical state of drivers during real tests in truck platooning. The peaks in the LF/HF (Low Frequency/High Frequency) parameter are considered, as they are linked to feelings of discomfort. Their occurrence may indicate whether the psychophysical state of the drivers is influenced by the different phases of driving in platoon. A method is defined to monitor and process the HRV (Heart Rate Variability) physiological parameter and the LF/HF ratio, based on the use of commercial smartwatches. An experimental activity, part of the European project C-Roads, allowed the collection of the physiological parameters of drivers and of the data featuring the vehicles in platoon. In general, the correlation between the two data sets revealed that drivers were not negatively affected by driving in platoon. The monitoring of the Follower driver, compared to the Leader, showed a higher level of stress. Peaks in the LF/HF parameter (i.e. high levels of stress) were associated in the 85 % of the cases to punctual situations that were expected to be stressful. Further possible applications of the method are presented, such as the investigation of the C-ITS impacts on the drivers
An assessment of the impact of possible CAP reform scenarios on Romanian agriculture
No full textUsing a simplified model, with key-variable the prices of two different possible scenarios of CAP reform after 2013 (moderate and radical), this paper present a comparison between the price effects of implementation of each reform scenario at 2015 horizon on Romanian agriculture. This short analysis shows that, under the presented hypotheses, the net welfare effect, due to the price changes, for the selected products, is positive in both reform scenarios, yet greater in the case of the radical reform. Integrated in the large context of Romanian development, it seems that the influence of CAP reform upon agriculture and rural areas will be most likely a gradual one: an interpenetration between the two scenarios is foreseeable, starting with the moderate reform that will dominate the period around 2013, the reform measures acquiring a more radical character afterwards.CAP reform, Romania, welfare effects, Agricultural and Food Policy,
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